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diff --git a/AR/data/bucket_sampler.py b/AR/data/bucket_sampler.py
new file mode 100644
index 0000000000000000000000000000000000000000..ee5947982f16d9f12a2875006e753846c8625f62
--- /dev/null
+++ b/AR/data/bucket_sampler.py
@@ -0,0 +1,157 @@
+# modified from https://github.com/feng-yufei/shared_debugging_code/blob/main/bucketsampler.py
+import itertools
+import math
+import random
+from random import shuffle
+from typing import Iterator
+from typing import Optional
+from typing import TypeVar
+
+import torch
+import torch.distributed as dist
+from torch.utils.data import Dataset
+from torch.utils.data import Sampler
+
+__all__ = [
+    "DistributedBucketSampler",
+]
+
+T_co = TypeVar('T_co', covariant=True)
+
+
+class DistributedBucketSampler(Sampler[T_co]):
+    r"""
+    sort the dataset wrt. input length
+    divide samples into buckets
+    sort within buckets
+    divide buckets into batches
+    sort batches
+    """
+
+    def __init__(self,
+                 dataset: Dataset,
+                 num_replicas: Optional[int]=None,
+                 rank: Optional[int]=None,
+                 shuffle: bool=True,
+                 seed: int=0,
+                 drop_last: bool=False,
+                 batch_size: int=32) -> None:
+        if num_replicas is None:
+            if not dist.is_available():
+                raise RuntimeError(
+                    "Requires distributed package to be available")
+            num_replicas = dist.get_world_size()
+        if rank is None:
+            if not dist.is_available():
+                raise RuntimeError(
+                    "Requires distributed package to be available")
+            rank = dist.get_rank()
+            torch.cuda.set_device(rank)
+        if rank >= num_replicas or rank < 0:
+            raise ValueError("Invalid rank {}, rank should be in the interval"
+                             " [0, {}]".format(rank, num_replicas - 1))
+        self.dataset = dataset
+        self.num_replicas = num_replicas
+        self.rank = rank
+        self.epoch = 0
+        self.drop_last = drop_last
+        # If the dataset length is evenly divisible by # of replicas, then there
+        # is no need to drop any data, since the dataset will be split equally.
+        if self.drop_last and len(
+                self.
+                dataset) % self.num_replicas != 0:  # type: ignore[arg-type]
+            # Split to nearest available length that is evenly divisible.
+            # This is to ensure each rank receives the same amount of data when
+            # using this Sampler.
+            self.num_samples = math.ceil(
+                (len(self.dataset) - self.num_replicas) /
+                self.num_replicas  # type: ignore[arg-type]
+            )
+        else:
+            self.num_samples = math.ceil(
+                len(self.dataset) / self.num_replicas)  # type: ignore[arg-type]
+        self.total_size = self.num_samples * self.num_replicas
+        self.shuffle = shuffle
+        self.seed = seed
+        self.batch_size = batch_size
+        self.id_with_length = self._get_sample_lengths()
+        self.id_buckets = self.make_buckets(bucket_width=2.0)
+
+    def _get_sample_lengths(self):
+        id_with_lengths = []
+        for i in range(len(self.dataset)):
+            id_with_lengths.append((i, self.dataset.get_sample_length(i)))
+        id_with_lengths.sort(key=lambda x: x[1])
+        return id_with_lengths
+
+    def make_buckets(self, bucket_width: float=2.0):
+        buckets = []
+        cur = []
+        max_sec = bucket_width
+        for id, sec in self.id_with_length:
+            if sec < max_sec:
+                cur.append(id)
+            else:
+                buckets.append(cur)
+                cur = [id]
+                max_sec += bucket_width
+        if len(cur) > 0:
+            buckets.append(cur)
+        return buckets
+
+    def __iter__(self) -> Iterator[T_co]:
+        if self.shuffle:
+            # deterministically shuffle based on epoch and seed
+            g = torch.Generator()
+            g.manual_seed(self.seed + self.epoch)
+            random.seed(self.epoch + self.seed)
+            shuffled_bucket = []
+            for buc in self.id_buckets:
+                buc_copy = buc.copy()
+                shuffle(buc_copy)
+                shuffled_bucket.append(buc_copy)
+            grouped_batch_size = self.batch_size * self.num_replicas
+            shuffled_bucket = list(itertools.chain(*shuffled_bucket))
+            n_batch = int(math.ceil(len(shuffled_bucket) / grouped_batch_size))
+            batches = [
+                shuffled_bucket[b * grouped_batch_size:(b + 1) *
+                                grouped_batch_size] for b in range(n_batch)
+            ]
+            shuffle(batches)
+            indices = list(itertools.chain(*batches))
+        else:
+            # type: ignore[arg-type]
+            indices = list(range(len(self.dataset)))
+
+        if not self.drop_last:
+            # add extra samples to make it evenly divisible
+            padding_size = self.total_size - len(indices)
+            if padding_size <= len(indices):
+                indices += indices[:padding_size]
+            else:
+                indices += (indices * math.ceil(padding_size /
+                                                len(indices)))[:padding_size]
+        else:
+            # remove tail of data to make it evenly divisible.
+            indices = indices[:self.total_size]
+        assert len(indices) == self.total_size
+
+        # subsample
+        indices = indices[self.rank:self.total_size:self.num_replicas]
+        assert len(indices) == self.num_samples
+
+        return iter(indices)
+
+    def __len__(self) -> int:
+        return self.num_samples
+
+    def set_epoch(self, epoch: int) -> None:
+        r"""
+        Sets the epoch for this sampler. When :attr:`shuffle=True`, this ensures all replicas
+        use a different random ordering for each epoch. Otherwise, the next iteration of this
+        sampler will yield the same ordering.
+
+        Args:
+            epoch (int): Epoch number.
+        """
+        self.epoch = epoch
diff --git a/AR/data/data_module.py b/AR/data/data_module.py
new file mode 100644
index 0000000000000000000000000000000000000000..4c300f1b400cbf94cae4f1179d7de2b9af5afe4a
--- /dev/null
+++ b/AR/data/data_module.py
@@ -0,0 +1,66 @@
+# modified from https://github.com/feng-yufei/shared_debugging_code/blob/main/data_module.py
+from pytorch_lightning import LightningDataModule
+from AR.data.bucket_sampler import DistributedBucketSampler
+from AR.data.dataset import Text2SemanticDataset
+from torch.utils.data import DataLoader
+
+
+class Text2SemanticDataModule(LightningDataModule):
+    def __init__(self, config, train_semantic_path, train_phoneme_path,dev_semantic_path=None, dev_phoneme_path=None):
+        super().__init__()
+        self.config = config
+        self.train_semantic_path = train_semantic_path
+        self.train_phoneme_path = train_phoneme_path
+        self.dev_semantic_path = dev_semantic_path
+        self.dev_phoneme_path = dev_phoneme_path
+        self.num_workers = self.config['data']['num_workers']
+
+    def prepare_data(self):
+        pass
+
+    def setup(self, stage=None, output_logs=False):
+        self._train_dataset = Text2SemanticDataset(
+            phoneme_path=self.train_phoneme_path,
+            semantic_path=self.train_semantic_path,
+            max_sec=self.config['data']['max_sec'],
+            pad_val=self.config['data']['pad_val'])
+        self._dev_dataset = self._train_dataset
+        # self._dev_dataset = Text2SemanticDataset(
+        #     phoneme_path=self.dev_phoneme_path,
+        #     semantic_path=self.dev_semantic_path,
+        #     max_sample=self.config['data']['max_eval_sample'],
+        #     max_sec=self.config['data']['max_sec'],
+        #     pad_val=self.config['data']['pad_val'])
+
+    def train_dataloader(self):
+        batch_size = self.config['train']['batch_size']
+        sampler = DistributedBucketSampler(
+            self._train_dataset, batch_size=batch_size)
+        return DataLoader(
+            self._train_dataset,
+            batch_size=batch_size,
+            sampler=sampler,
+            collate_fn=self._train_dataset.collate,
+            num_workers=self.num_workers,
+            persistent_workers=True,
+            prefetch_factor=16
+        )
+
+    def val_dataloader(self):
+        return DataLoader(
+            self._dev_dataset,
+            batch_size=1,
+            shuffle=False,
+            collate_fn=self._train_dataset.collate,
+            num_workers=max(self.num_workers,12),
+            persistent_workers=True,
+            prefetch_factor=16
+        )
+
+    # 这个会使用到嘛？
+    def test_dataloader(self):
+        return DataLoader(
+            self._dev_dataset,
+            batch_size=1,
+            shuffle=False,
+            collate_fn=self._train_dataset.collate)
diff --git a/AR/data/dataset.py b/AR/data/dataset.py
new file mode 100644
index 0000000000000000000000000000000000000000..72c9e2e296723d6c4bb07430a1f1deee8fa8818f
--- /dev/null
+++ b/AR/data/dataset.py
@@ -0,0 +1,302 @@
+# modified from https://github.com/feng-yufei/shared_debugging_code/blob/main/t2s_dataset.py
+import pdb
+import sys
+# sys.path.append("/data/docker/liujing04/gpt-vits/mq-vits-s1bert_no_bert")
+import traceback,os
+from typing import Dict
+from typing import List
+
+import numpy as np
+import pandas as pd
+import torch,json
+from torch.utils.data import DataLoader
+from torch.utils.data import Dataset
+from transformers import AutoTokenizer
+
+from text import cleaned_text_to_sequence
+# from config import exp_dir
+
+def batch_sequences(sequences: List[np.array], axis: int = 0, pad_value: int = 0):
+    seq = sequences[0]
+    ndim = seq.ndim
+    if axis < 0:
+        axis += ndim
+    dtype = seq.dtype
+    pad_value = dtype.type(pad_value)
+    seq_lengths = [seq.shape[axis] for seq in sequences]
+    max_length = np.max(seq_lengths)
+
+    padded_sequences = []
+    for seq, length in zip(sequences, seq_lengths):
+        padding = [(0, 0)] * axis + [(0, max_length - length)] + [(0, 0)] * (
+                ndim - axis - 1)
+        padded_seq = np.pad(
+            seq, padding, mode='constant', constant_values=pad_value)
+        padded_sequences.append(padded_seq)
+    batch = np.stack(padded_sequences)
+    return batch
+
+class Text2SemanticDataset(Dataset):
+    """dataset class for text tokens to semantic model training."""
+
+    def __init__(self,
+                 phoneme_path: str,
+                 semantic_path: str,
+                 max_sample: int = None,
+                 max_sec: int = 100,
+                 pad_val: int = 1024,
+                 # min value of phoneme/sec
+                 min_ps_ratio: int = 3,
+                 # max value of phoneme/sec
+                 max_ps_ratio: int = 25) -> None:
+        super().__init__()
+
+        self.semantic_data = pd.read_csv(semantic_path, delimiter='\t', encoding="utf-8")
+        # get dict
+        self.path2=phoneme_path#"%s/2-name2text.txt"%exp_dir#phoneme_path
+        self.path3="%s/3-bert"%(os.path.basename(phoneme_path))#"%s/3-bert"%exp_dir#bert_dir
+        self.path6=semantic_path#"%s/6-name2semantic.tsv"%exp_dir#semantic_path
+        assert os.path.exists(self.path2)
+        assert os.path.exists(self.path6)
+        self.phoneme_data={}
+        with open(self.path2,"r",encoding="utf8")as f:
+            lines=f.read().strip("\n").split("\n")
+
+        for line in lines:
+            tmp=line.split("\t")
+            if(len(tmp)!=4):continue
+            self.phoneme_data[tmp[0]]=[tmp[1],tmp[2],tmp[3]]
+
+        # self.phoneme_data = np.load(phoneme_path, allow_pickle=True).item()
+        # pad for semantic tokens
+        self.PAD: int = pad_val
+        # self.hz = 25
+        # with open("/data/docker/liujing04/gpt-vits/mq-vits-s1bert_no_bert/configs/s2.json", "r") as f:data = f.read()
+        # data=json.loads(data)["model"]["semantic_frame_rate"]#50hz
+        # self.hz=int(data[:-2])#
+        self.hz=int(os.environ.get("hz","25hz")[:-2])
+
+        # max seconds of semantic token
+        self.max_sec = max_sec
+        self.min_ps_ratio = min_ps_ratio
+        self.max_ps_ratio = max_ps_ratio
+
+        if max_sample is not None:
+            self.semantic_data = self.semantic_data[:max_sample]
+
+        # {idx: (semantic, phoneme)}
+        # semantic list, phoneme list
+        self.semantic_phoneme = []
+        self.item_names = []
+
+        self.inited = False
+
+        if not self.inited:
+            # 调用初始化函数
+            self.init_batch()
+            self.inited = True
+            del self.semantic_data
+            del self.phoneme_data
+        # self.tokenizer = AutoTokenizer.from_pretrained("hfl/chinese-roberta-wwm-ext-large")
+        # self.tokenizer = AutoTokenizer.from_pretrained("/data/docker/liujing04/bert-vits2/Bert-VITS2-master20231106/bert/chinese-roberta-wwm-ext-large")
+
+
+    def init_batch(self):
+        semantic_data_len = len(self.semantic_data)
+        phoneme_data_len = len(self.phoneme_data.keys())
+        print("semantic_data_len:", semantic_data_len)
+        print("phoneme_data_len:", phoneme_data_len)
+        idx = 0
+        num_not_in = 0
+        num_deleted_bigger = 0
+        num_deleted_ps = 0
+        for i in range(semantic_data_len):
+            # 先依次遍历
+            # get str
+            item_name = self.semantic_data['item_name'][i]
+            # print(self.phoneme_data)
+            try:
+                phoneme, word2ph, text = self.phoneme_data[item_name]
+            except Exception:
+                traceback.print_exc()
+                # print(f"{item_name} not in self.phoneme_data !")
+                num_not_in += 1
+                continue
+
+            semantic_str = self.semantic_data['semantic_audio'][i]
+            # get token list
+            semantic_ids = [int(idx) for idx in semantic_str.split(' ')]
+            # (T), 是否需要变成 (1, T) -> 不需要，因为需要求 len
+            # 过滤掉太长的样本
+            if len(semantic_ids) > self.max_sec * self.hz:#########1###根据token个数推测总时长过滤时长60s（config里）#40*25=1k
+                num_deleted_bigger += 1
+                continue
+            # (T, ), 这个速度不会很慢，所以可以在一开始就处理，无需在 __getitem__ 里面单个处理####
+            phoneme = phoneme.split(' ')
+
+            try:
+                phoneme_ids = cleaned_text_to_sequence(phoneme)
+            except:
+                traceback.print_exc()
+                # print(f"{item_name} not in self.phoneme_data !")
+                num_not_in += 1
+                continue
+            # if len(phoneme_ids) >400:###########2：改为恒定限制为semantic/2.5就行
+            if len(phoneme_ids) >self.max_sec * self.hz/2.5:###########2：改为恒定限制为semantic/2.5就行
+                num_deleted_ps += 1
+                continue
+            # if len(semantic_ids) > 1000:###########3
+            #     num_deleted_bigger += 1
+            #     continue
+
+            ps_ratio = len(phoneme_ids) / (len(semantic_ids) / self.hz)
+
+            if ps_ratio > self.max_ps_ratio or ps_ratio < self.min_ps_ratio:##########4#3~25#每秒多少个phone
+                num_deleted_ps += 1
+                # print(item_name)
+                continue
+
+            self.semantic_phoneme.append((semantic_ids, phoneme_ids))
+            idx += 1
+            self.item_names.append(item_name)
+
+        min_num=100#20直接不补#30补了也不存ckpt
+        leng =len(self.semantic_phoneme)
+        if(leng<min_num):
+            tmp1=self.semantic_phoneme
+            tmp2=self.item_names
+            self.semantic_phoneme=[]
+            self.item_names=[]
+            for _ in range(max(2,int(min_num/leng))):
+                self.semantic_phoneme+=tmp1
+                self.item_names+=tmp2
+        if num_not_in > 0:
+            print(f"there are {num_not_in} semantic datas not in phoneme datas")
+        if num_deleted_bigger > 0:
+            print(
+                f"deleted {num_deleted_bigger} audios who's duration are bigger than {self.max_sec} seconds"
+            )
+        if num_deleted_ps > 0:
+            # 4702 for LibriTTS, LirbriTTS 是标注数据, 是否需要筛？=> 需要，有值为 100 的极端值
+            print(
+                f"deleted {num_deleted_ps} audios who's phoneme/sec are bigger than {self.max_ps_ratio} or smaller than {self.min_ps_ratio}"
+            )
+        '''
+        there are 31 semantic datas not in phoneme datas
+        deleted 34 audios who's duration are bigger than 54 seconds
+        deleted 3190 audios who's phoneme/sec are bigger than 25 or smaller than 3
+        dataset.__len__(): 366463
+
+        '''
+        # 345410 for LibriTTS
+        print("dataset.__len__():", self.__len__())
+
+    def __get_item_names__(self) -> List[str]:
+        return self.item_names
+
+    def __len__(self) -> int:
+        return len(self.semantic_phoneme)
+
+    def __getitem__(self, idx: int) -> Dict:
+        semantic_ids, phoneme_ids = self.semantic_phoneme[idx]
+        item_name = self.item_names[idx]
+        phoneme_ids_len = len(phoneme_ids)
+        # semantic tokens target
+        semantic_ids_len = len(semantic_ids)
+
+        flag=0
+        path_bert = "%s/%s.pt" % (self.path3, item_name)
+        if(os.path.exists(path_bert)==True):bert_feature = torch.load(path_bert,map_location="cpu")
+        else:flag=1
+        if(flag==1):
+            # bert_feature=torch.zeros_like(phoneme_ids,dtype=torch.float32)
+            bert_feature=None
+        else:
+            assert bert_feature.shape[-1] == len(phoneme_ids)
+        return {
+            'idx': idx,
+            'phoneme_ids': phoneme_ids,
+            'phoneme_ids_len': phoneme_ids_len,
+            'semantic_ids': semantic_ids,
+            'semantic_ids_len': semantic_ids_len,
+            'bert_feature': bert_feature,
+        }
+
+    def get_sample_length(self, idx: int):
+        semantic_ids = self.semantic_phoneme[idx][0]
+        sec = 1.0 * len(semantic_ids) / self.hz
+        return sec
+
+    def collate(self, examples: List[Dict]) -> Dict:
+        sample_index: List[int] = []
+        phoneme_ids: List[torch.Tensor] = []
+        phoneme_ids_lens: List[int] = []
+        semantic_ids: List[torch.Tensor] = []
+        semantic_ids_lens: List[int] = []
+        # return
+
+
+        for item in examples:
+            sample_index.append(item["idx"])
+            phoneme_ids.append(np.array(item["phoneme_ids"], dtype=np.int64))
+            semantic_ids.append(np.array(item["semantic_ids"], dtype=np.int64))
+            phoneme_ids_lens.append(item["phoneme_ids_len"])
+            semantic_ids_lens.append(item["semantic_ids_len"])
+
+        # pad 0
+        phoneme_ids = batch_sequences(phoneme_ids)
+        semantic_ids = batch_sequences(semantic_ids, pad_value=self.PAD)
+
+        # # convert each batch to torch.tensor
+        phoneme_ids = torch.tensor(phoneme_ids)
+        semantic_ids = torch.tensor(semantic_ids)
+        phoneme_ids_lens = torch.tensor(phoneme_ids_lens)
+        semantic_ids_lens = torch.tensor(semantic_ids_lens)
+        bert_padded = torch.FloatTensor(len(examples), 1024, max(phoneme_ids_lens))
+        bert_padded.zero_()
+
+        for idx, item in enumerate(examples):
+            bert = item['bert_feature']
+            if(bert!=None):
+                bert_padded[idx, :, :bert.shape[-1]] = bert
+
+        return {
+            # List[int]
+            "ids": sample_index,
+            # torch.Tensor (B, max_phoneme_length)
+            "phoneme_ids": phoneme_ids,
+            # torch.Tensor (B)
+            "phoneme_ids_len": phoneme_ids_lens,
+            # torch.Tensor (B, max_semantic_ids_length)
+            "semantic_ids": semantic_ids,
+            # torch.Tensor (B)
+            "semantic_ids_len": semantic_ids_lens,
+            # torch.Tensor (B, 1024, max_phoneme_length)
+            "bert_feature": bert_padded,
+        }
+
+
+if __name__ == '__main__':
+    root_dir = '/data/docker/liujing04/gpt-vits/prepare/dump_mix/'
+    dataset = Text2SemanticDataset(
+        phoneme_path=root_dir + 'phoneme_train.npy',
+        semantic_path=root_dir + 'semantic_train.tsv')
+
+    batch_size = 12
+    dataloader = DataLoader(
+        dataset,
+        batch_size=batch_size,
+        collate_fn=dataset.collate,
+        shuffle=False)
+    for i, batch in enumerate(dataloader):
+        if(i%1000==0):print(i)
+        # if i == 0:
+        #     print('batch["ids"]:', batch["ids"])
+            # print('batch["phoneme_ids"]:', batch["phoneme_ids"],
+            #       batch["phoneme_ids"].shape)
+            # print('batch["phoneme_ids_len"]:', batch["phoneme_ids_len"],
+            #       batch["phoneme_ids_len"].shape)
+            # print('batch["semantic_ids"]:', batch["semantic_ids"],
+            #       batch["semantic_ids"].shape)
+            # print('batch["semantic_ids_len"]:', batch["semantic_ids_len"],
+            #       batch["semantic_ids_len"].shape)
diff --git a/AR/exps/__init__.py b/AR/exps/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/AR/exps/beats/BEATs.py b/AR/exps/beats/BEATs.py
new file mode 100644
index 0000000000000000000000000000000000000000..3fd8ced1fe545e572b72532e9625b8291f65cb70
--- /dev/null
+++ b/AR/exps/beats/BEATs.py
@@ -0,0 +1,179 @@
+# --------------------------------------------------------
+# BEATs: Audio Pre-Training with Acoustic Tokenizers (https://arxiv.org/abs/2212.09058)
+# Github source: https://github.com/microsoft/unilm/tree/master/beats
+# Copyright (c) 2022 Microsoft
+# Licensed under The MIT License [see LICENSE for details]
+# Based on fairseq code bases
+# https://github.com/pytorch/fairseq
+# --------------------------------------------------------
+import logging
+from typing import Optional
+
+import torch
+import torch.nn as nn
+import torchaudio.compliance.kaldi as ta_kaldi
+from torch.nn import LayerNorm
+
+from .backbone import TransformerEncoder
+
+logger = logging.getLogger(__name__)
+
+
+class BEATsConfig:
+    def __init__(self, cfg=None):
+        self.input_patch_size: int = -1  # path size of patch embedding
+        self.embed_dim: int = 512  # patch embedding dimension
+        self.conv_bias: bool = False  # include bias in conv encoder
+
+        self.encoder_layers: int = 12  # num encoder layers in the transformer
+        self.encoder_embed_dim: int = 768  # encoder embedding dimension
+        self.encoder_ffn_embed_dim: int = 3072  # encoder embedding dimension for FFN
+        self.encoder_attention_heads: int = 12  # num encoder attention heads
+        self.activation_fn: str = "gelu"  # activation function to use
+
+        self.layer_wise_gradient_decay_ratio: float = 1.0  # ratio for layer-wise gradient decay
+        self.layer_norm_first: bool = False  # apply layernorm first in the transformer
+        self.deep_norm: bool = False  # apply deep_norm first in the transformer
+
+        # dropouts
+        self.dropout: float = 0.1  # dropout probability for the transformer
+        self.attention_dropout: float = 0.1  # dropout probability for attention weights
+        self.activation_dropout: float = 0.0  # dropout probability after activation in FFN
+        self.encoder_layerdrop: float = 0.0  # probability of dropping a tarnsformer layer
+        self.dropout_input: float = 0.0  # dropout to apply to the input (after feat extr)
+
+        # positional embeddings
+        self.conv_pos: int = 128  # number of filters for convolutional positional embeddings
+        self.conv_pos_groups: int = 16  # number of groups for convolutional positional embedding
+
+        # relative position embedding
+        self.relative_position_embedding: bool = False  # apply relative position embedding
+        self.num_buckets: int = 320  # number of buckets for relative position embedding
+        self.max_distance: int = 1280  # maximum distance for relative position embedding
+        self.gru_rel_pos: bool = False  # apply gated relative position embedding
+
+        # label predictor
+        self.finetuned_model: bool = False  # whether the model is a fine-tuned model.
+        self.predictor_dropout: float = 0.1  # dropout probability for the predictor
+        self.predictor_class: int = 527  # target class number for the predictor
+
+        if cfg is not None:
+            self.update(cfg)
+
+    def update(self, cfg: dict):
+        self.__dict__.update(cfg)
+
+
+class BEATs(nn.Module):
+    def __init__(
+            self,
+            cfg: BEATsConfig, ) -> None:
+        super().__init__()
+        logger.info(f"BEATs Config: {cfg.__dict__}")
+
+        self.cfg = cfg
+
+        self.embed = cfg.embed_dim
+        self.post_extract_proj = (nn.Linear(self.embed, cfg.encoder_embed_dim)
+                                  if self.embed != cfg.encoder_embed_dim else
+                                  None)
+
+        self.input_patch_size = cfg.input_patch_size
+        self.patch_embedding = nn.Conv2d(
+            1,
+            self.embed,
+            kernel_size=self.input_patch_size,
+            stride=self.input_patch_size,
+            bias=cfg.conv_bias)
+
+        self.dropout_input = nn.Dropout(cfg.dropout_input)
+
+        assert not cfg.deep_norm or not cfg.layer_norm_first
+        self.encoder = TransformerEncoder(cfg)
+        self.layer_norm = LayerNorm(self.embed)
+
+        if cfg.finetuned_model:
+            self.predictor_dropout = nn.Dropout(cfg.predictor_dropout)
+            self.predictor = nn.Linear(cfg.encoder_embed_dim,
+                                       cfg.predictor_class)
+        else:
+            self.predictor = None
+
+    def forward_padding_mask(
+            self,
+            features: torch.Tensor,
+            padding_mask: torch.Tensor, ) -> torch.Tensor:
+        extra = padding_mask.size(1) % features.size(1)
+        if extra > 0:
+            padding_mask = padding_mask[:, :-extra]
+        padding_mask = padding_mask.view(
+            padding_mask.size(0), features.size(1), -1)
+        padding_mask = padding_mask.all(-1)
+        return padding_mask
+
+    def preprocess(
+            self,
+            source: torch.Tensor,
+            fbank_mean: float=15.41663,
+            fbank_std: float=6.55582, ) -> torch.Tensor:
+        fbanks = []
+        for waveform in source:
+            waveform = waveform.unsqueeze(0) * 2**15
+            fbank = ta_kaldi.fbank(
+                waveform,
+                num_mel_bins=128,
+                sample_frequency=16000,
+                frame_length=25,
+                frame_shift=10)
+            fbanks.append(fbank)
+        fbank = torch.stack(fbanks, dim=0)
+        fbank = (fbank - fbank_mean) / (2 * fbank_std)
+        return fbank
+
+    def extract_features(
+            self,
+            source: torch.Tensor,
+            padding_mask: Optional[torch.Tensor]=None,
+            fbank_mean: float=15.41663,
+            fbank_std: float=6.55582, ):
+        fbank = self.preprocess(
+            source, fbank_mean=fbank_mean, fbank_std=fbank_std)
+
+        if padding_mask is not None:
+            padding_mask = self.forward_padding_mask(fbank, padding_mask)
+
+        fbank = fbank.unsqueeze(1)
+        features = self.patch_embedding(fbank)
+        features = features.reshape(features.shape[0], features.shape[1], -1)
+        features = features.transpose(1, 2)
+        features = self.layer_norm(features)
+
+        if padding_mask is not None:
+            padding_mask = self.forward_padding_mask(features, padding_mask)
+
+        if self.post_extract_proj is not None:
+            features = self.post_extract_proj(features)
+
+        x = self.dropout_input(features)
+
+        x, layer_results = self.encoder(
+            x,
+            padding_mask=padding_mask, )
+
+        if self.predictor is not None:
+            x = self.predictor_dropout(x)
+            logits = self.predictor(x)
+
+            if padding_mask is not None and padding_mask.any():
+                logits[padding_mask] = 0
+                logits = logits.sum(dim=1)
+                logits = logits / (~padding_mask).sum(
+                    dim=1).unsqueeze(-1).expand_as(logits)
+            else:
+                logits = logits.mean(dim=1)
+
+            lprobs = torch.sigmoid(logits)
+
+            return lprobs, padding_mask
+        else:
+            return x, padding_mask
diff --git a/AR/exps/beats/README.md b/AR/exps/beats/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..fd54e797a6ae5152c92fd2b37a8531f13e103f00
--- /dev/null
+++ b/AR/exps/beats/README.md
@@ -0,0 +1,127 @@
+
+# BEATs
+
+[**BEATs**](https://arxiv.org/abs/2212.09058): **Audio Pre-Training with Acoustic Tokenizers**
+
+Official PyTorch implementation and pretrained models of BEATs
+
+## Pre-Trained and Fine-Tuned Tokenizers and Models
+Iterations  | Tokenizer  | Pre-Trained Model | AudioSet Fine-Tuned Model 1 | AudioSet Fine-Tuned Model 2
+|---|---|---|---|---
+Iter1  |  Random Projection | [BEATs_iter1](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter1.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D)  | [Fine-tuned BEATs_iter1 (cpt1)](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter1_finetuned_on_AS2M_cpt1.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D) | [Fine-tuned BEATs_iter1 (cpt2)](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter1_finetuned_on_AS2M_cpt2.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D) | 
+Iter2  |  [Tokenizer_iter2](https://valle.blob.core.windows.net/share/BEATs/Tokenizer_iter2.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D)| [BEATs_iter2](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter2.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D)  | [Fine-tuned BEATs_iter2 (cpt1)](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter2_finetuned_on_AS2M_cpt1.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D) | [Fine-tuned BEATs_iter2 (cpt2)](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter2_finetuned_on_AS2M_cpt2.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D) | 
+Iter3  |  [Tokenizer_iter3](https://valle.blob.core.windows.net/share/BEATs/Tokenizer_iter3.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D)| [BEATs_iter3](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter3.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D)  | [Fine-tuned BEATs_iter3 (cpt1)](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter3_finetuned_on_AS2M_cpt1.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D) | [Fine-tuned BEATs_iter3 (cpt2)](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter3_finetuned_on_AS2M_cpt2.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D) | 
+Iter3+  |  [Tokenizer_iter3+ (AS20K)](https://valle.blob.core.windows.net/share/BEATs/Tokenizer_iter3_plus_AS20K.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D)| [BEATs_iter3+ (AS20K)](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter3_plus_AS20K.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D)  | [Fine-tuned BEATs_iter3+ (AS20K) (cpt1)](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter3_plus_AS20K_finetuned_on_AS2M_cpt1.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D) | [Fine-tuned BEATs_iter3+ (AS20K) (cpt2)](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter3_plus_AS20K_finetuned_on_AS2M_cpt2.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D) | 
+Iter3+  |  [Tokenizer_iter3+ (AS2M)](https://valle.blob.core.windows.net/share/BEATs/Tokenizer_iter3_plus_AS2M.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D)| [BEATs_iter3+ (AS2M)](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter3_plus_AS2M.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D)  | [Fine-tuned BEATs_iter3+ (AS2M) (cpt1)](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter3_plus_AS2M_finetuned_on_AS2M_cpt1.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D) | [Fine-tuned BEATs_iter3+ (AS2M) (cpt2)](https://valle.blob.core.windows.net/share/BEATs/BEATs_iter3_plus_AS2M_finetuned_on_AS2M_cpt2.pt?sv=2020-08-04&st=2023-03-01T07%3A51%3A05Z&se=2033-03-02T07%3A51%3A00Z&sr=c&sp=rl&sig=QJXmSJG9DbMKf48UDIU1MfzIro8HQOf3sqlNXiflY1I%3D) | 
+
+
+### Load Tokenizers
+
+```python
+import torch
+from Tokenizers import TokenizersConfig, Tokenizers
+
+# load the pre-trained checkpoints
+checkpoint = torch.load('/path/to/tokenizer.pt')
+
+cfg = TokenizersConfig(checkpoint['cfg'])
+BEATs_tokenizer = Tokenizers(cfg)
+BEATs_tokenizer.load_state_dict(checkpoint['model'])
+BEATs_tokenizer.eval()
+
+# tokenize the audio and generate the labels
+audio_input_16khz = torch.randn(1, 10000)
+padding_mask = torch.zeros(1, 10000).bool()
+
+labels = BEATs_tokenizer.extract_labels(audio_input_16khz, padding_mask=padding_mask)
+```
+
+
+### Load Pre-Trained Models
+
+```python
+import torch
+from BEATs import BEATs, BEATsConfig
+
+# load the pre-trained checkpoints
+checkpoint = torch.load('/path/to/model.pt')
+
+cfg = BEATsConfig(checkpoint['cfg'])
+BEATs_model = BEATs(cfg)
+BEATs_model.load_state_dict(checkpoint['model'])
+BEATs_model.eval()
+
+# extract the the audio representation
+audio_input_16khz = torch.randn(1, 10000)
+padding_mask = torch.zeros(1, 10000).bool()
+
+representation = BEATs_model.extract_features(audio_input_16khz, padding_mask=padding_mask)[0]
+```
+
+
+### Load Fine-tuned Models
+
+```python
+import torch
+from BEATs import BEATs, BEATsConfig
+
+# load the fine-tuned checkpoints
+checkpoint = torch.load('/path/to/model.pt')
+
+cfg = BEATsConfig(checkpoint['cfg'])
+BEATs_model = BEATs(cfg)
+BEATs_model.load_state_dict(checkpoint['model'])
+BEATs_model.eval()
+
+# predict the classification probability of each class
+audio_input_16khz = torch.randn(3, 10000)
+padding_mask = torch.zeros(3, 10000).bool()
+
+probs = BEATs_model.extract_features(audio_input_16khz, padding_mask=padding_mask)[0]
+
+for i, (top5_label_prob, top5_label_idx) in enumerate(zip(*probs.topk(k=5))):
+    top5_label = [checkpoint['label_dict'][label_idx.item()] for label_idx in top5_label_idx]
+    print(f'Top 5 predicted labels of the {i}th audio are {top5_label} with probability of {top5_label_prob}')
+```
+
+## Evaluation Results
+
+### Comparing with the SOTA Single Models
+![alt text](Evaluation_Results/Comparing_with_the_SOTA_Single_Models.png)
+
+
+### Comparing with the SOTA Ensemble Models
+![alt text](Evaluation_Results/Comparing_with_the_SOTA_Ensemble_Models.png)
+
+
+### Comparing Different BEATS Tokenizers
+![alt text](Evaluation_Results/Comparing_Different_BEATS_Tokenizers.png)
+
+
+### Comparing Different Pre-Training Targets
+![alt text](Evaluation_Results/Comparing_Different_Pre-Training_Targets.png)
+
+
+## License
+This project is licensed under the license found in the LICENSE file in the root directory of this source tree.
+Portions of the source code are based on the [FAIRSEQ](https://github.com/pytorch/fairseq) and [VQGAN](https://github.com/CompVis/taming-transformers) project.
+
+[Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct)
+
+
+### Reference
+If you find our work is useful in your research, please cite the following paper:
+``` latex
+@article{Chen2022beats,
+  title = {BEATs: Audio Pre-Training with Acoustic Tokenizers},
+  author  = {Sanyuan Chen and Yu Wu and Chengyi Wang and Shujie Liu and Daniel Tompkins and Zhuo Chen and Furu Wei},
+  eprint={2212.09058},
+  archivePrefix={arXiv},
+  year={2022}
+}
+```
+### Contact Information
+
+For help or issues using BEATs models, please submit a GitHub issue.
+
+For other communications related to  BEATs, please contact Yu Wu (`yuwu1@microsoft.com`).
diff --git a/AR/exps/beats/Tokenizers.py b/AR/exps/beats/Tokenizers.py
new file mode 100644
index 0000000000000000000000000000000000000000..503535cee5799722b6fa84945b4cf1d87d65e193
--- /dev/null
+++ b/AR/exps/beats/Tokenizers.py
@@ -0,0 +1,172 @@
+# --------------------------------------------------------
+# BEATs: Audio Pre-Training with Acoustic Tokenizers (https://arxiv.org/abs/2212.09058)
+# Github source: https://github.com/microsoft/unilm/tree/master/beats
+# Copyright (c) 2022 Microsoft
+# Licensed under The MIT License [see LICENSE for details]
+# Based on fairseq code bases
+# https://github.com/pytorch/fairseq
+# --------------------------------------------------------
+import logging
+from typing import Optional
+
+import torch
+import torch.nn as nn
+import torchaudio.compliance.kaldi as ta_kaldi
+from backbone import (
+    TransformerEncoder, )
+from quantizer import (
+    NormEMAVectorQuantizer, )
+from torch.nn import LayerNorm
+
+logger = logging.getLogger(__name__)
+
+
+class TokenizersConfig:
+    def __init__(self, cfg=None):
+        self.input_patch_size: int = -1  # path size of patch embedding
+        self.embed_dim: int = 512  # patch embedding dimension
+        self.conv_bias: bool = False  # include bias in conv encoder
+
+        self.encoder_layers: int = 12  # num encoder layers in the transformer
+        self.encoder_embed_dim: int = 768  # encoder embedding dimension
+        self.encoder_ffn_embed_dim: int = 3072  # encoder embedding dimension for FFN
+        self.encoder_attention_heads: int = 12  # num encoder attention heads
+        self.activation_fn: str = "gelu"  # activation function to use
+
+        self.layer_norm_first: bool = False  # apply layernorm first in the transformer
+        self.deep_norm: bool = False  # apply deep_norm first in the transformer
+
+        # dropouts
+        self.dropout: float = 0.1  # dropout probability for the transformer
+        self.attention_dropout: float = 0.1  # dropout probability for attention weights
+        self.activation_dropout: float = 0.0  # dropout probability after activation in FFN
+        self.encoder_layerdrop: float = 0.0  # probability of dropping a tarnsformer layer
+        self.dropout_input: float = 0.0  # dropout to apply to the input (after feat extr)
+
+        # positional embeddings
+        self.conv_pos: int = 128  # number of filters for convolutional positional embeddings
+        self.conv_pos_groups: int = 16  # number of groups for convolutional positional embedding
+
+        # relative position embedding
+        self.relative_position_embedding: bool = False  # apply relative position embedding
+        self.num_buckets: int = 320  # number of buckets for relative position embedding
+        self.max_distance: int = 1280  # maximum distance for relative position embedding
+        self.gru_rel_pos: bool = False  # apply gated relative position embedding
+
+        # quantizer
+        self.quant_n: int = 1024  # codebook number in quantizer
+        self.quant_dim: int = 256  # codebook dimension in quantizer
+
+        if cfg is not None:
+            self.update(cfg)
+
+    def update(self, cfg: dict):
+        self.__dict__.update(cfg)
+
+
+class Tokenizers(nn.Module):
+    def __init__(
+            self,
+            cfg: TokenizersConfig, ) -> None:
+        super().__init__()
+        logger.info(f"Tokenizers Config: {cfg.__dict__}")
+
+        self.cfg = cfg
+
+        self.embed = cfg.embed_dim
+        self.post_extract_proj = (nn.Linear(self.embed, cfg.encoder_embed_dim)
+                                  if self.embed != cfg.encoder_embed_dim else
+                                  None)
+
+        self.input_patch_size = cfg.input_patch_size
+        self.patch_embedding = nn.Conv2d(
+            1,
+            self.embed,
+            kernel_size=self.input_patch_size,
+            stride=self.input_patch_size,
+            bias=cfg.conv_bias)
+
+        self.dropout_input = nn.Dropout(cfg.dropout_input)
+
+        assert not cfg.deep_norm or not cfg.layer_norm_first
+        self.encoder = TransformerEncoder(cfg)
+        self.layer_norm = LayerNorm(self.embed)
+
+        self.quantize = NormEMAVectorQuantizer(
+            n_embed=cfg.quant_n,
+            embedding_dim=cfg.quant_dim,
+            beta=1.0,
+            kmeans_init=True,
+            decay=0.99, )
+        self.quant_n = cfg.quant_n
+        self.quantize_layer = nn.Sequential(
+            nn.Linear(cfg.encoder_embed_dim, cfg.encoder_embed_dim),
+            nn.Tanh(),
+            nn.Linear(cfg.encoder_embed_dim, cfg.quant_dim)  # for quantize
+        )
+
+    def forward_padding_mask(
+            self,
+            features: torch.Tensor,
+            padding_mask: torch.Tensor, ) -> torch.Tensor:
+        extra = padding_mask.size(1) % features.size(1)
+        if extra > 0:
+            padding_mask = padding_mask[:, :-extra]
+        padding_mask = padding_mask.view(
+            padding_mask.size(0), features.size(1), -1)
+        padding_mask = padding_mask.all(-1)
+        return padding_mask
+
+    def preprocess(
+            self,
+            source: torch.Tensor,
+            fbank_mean: float=15.41663,
+            fbank_std: float=6.55582, ) -> torch.Tensor:
+        fbanks = []
+        for waveform in source:
+            waveform = waveform.unsqueeze(0) * 2**15
+            fbank = ta_kaldi.fbank(
+                waveform,
+                num_mel_bins=128,
+                sample_frequency=16000,
+                frame_length=25,
+                frame_shift=10)
+            fbanks.append(fbank)
+        fbank = torch.stack(fbanks, dim=0)
+        fbank = (fbank - fbank_mean) / (2 * fbank_std)
+        return fbank
+
+    def extract_labels(
+            self,
+            source: torch.Tensor,
+            padding_mask: Optional[torch.Tensor]=None,
+            fbank_mean: float=15.41663,
+            fbank_std: float=6.55582, ):
+        fbank = self.preprocess(
+            source, fbank_mean=fbank_mean, fbank_std=fbank_std)
+
+        if padding_mask is not None:
+            padding_mask = self.forward_padding_mask(fbank, padding_mask)
+
+        fbank = fbank.unsqueeze(1)
+        features = self.patch_embedding(fbank)
+        features = features.reshape(features.shape[0], features.shape[1], -1)
+        features = features.transpose(1, 2)
+        features = self.layer_norm(features)
+
+        if padding_mask is not None:
+            padding_mask = self.forward_padding_mask(features, padding_mask)
+
+        if self.post_extract_proj is not None:
+            features = self.post_extract_proj(features)
+
+        x = self.dropout_input(features)
+
+        x, layer_results = self.encoder(
+            x,
+            padding_mask=padding_mask, )
+
+        quantize_input = self.quantize_layer(x)
+        quantize_feature, embed_loss, embed_ind = self.quantize(quantize_input)
+
+        return embed_ind
diff --git a/AR/exps/beats/__init__.py b/AR/exps/beats/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..275243c10fd9af9505faf45de02d42a8fd55229d
--- /dev/null
+++ b/AR/exps/beats/__init__.py
@@ -0,0 +1,2 @@
+# this folder is modified from https://github.com/microsoft/unilm/tree/master/beats
+# ontology.json is from https://github.com/audioset/ontology/
diff --git a/AR/exps/beats/backbone.py b/AR/exps/beats/backbone.py
new file mode 100644
index 0000000000000000000000000000000000000000..b9ec5c13e8df305bc9daab49b28f49a2175d4b54
--- /dev/null
+++ b/AR/exps/beats/backbone.py
@@ -0,0 +1,791 @@
+# --------------------------------------------------------
+# BEATs: Audio Pre-Training with Acoustic Tokenizers (https://arxiv.org/abs/2212.09058)
+# Github source: https://github.com/microsoft/unilm/tree/master/beats
+# Copyright (c) 2022 Microsoft
+# Licensed under The MIT License [see LICENSE for details]
+# Based on fairseq code bases
+# https://github.com/pytorch/fairseq
+# --------------------------------------------------------
+import math
+from typing import Dict
+from typing import Optional
+from typing import Tuple
+
+import numpy as np
+import torch
+import torch.nn.functional as F
+from torch import nn
+from torch import Tensor
+from torch.nn import LayerNorm
+from torch.nn import Parameter
+
+from .modules import get_activation_fn
+from .modules import GLU_Linear
+from .modules import GradMultiply
+from .modules import quant_noise
+from .modules import SamePad
+
+
+class TransformerEncoder(nn.Module):
+    def __init__(self, args):
+        super().__init__()
+
+        self.dropout = args.dropout
+        self.embedding_dim = args.encoder_embed_dim
+
+        self.pos_conv = nn.Conv1d(
+            self.embedding_dim,
+            self.embedding_dim,
+            kernel_size=args.conv_pos,
+            padding=args.conv_pos // 2,
+            groups=args.conv_pos_groups, )
+        dropout = 0
+        std = math.sqrt(
+            (4 * (1.0 - dropout)) / (args.conv_pos * self.embedding_dim))
+        nn.init.normal_(self.pos_conv.weight, mean=0, std=std)
+        nn.init.constant_(self.pos_conv.bias, 0)
+
+        self.pos_conv = nn.utils.weight_norm(
+            self.pos_conv, name="weight", dim=2)
+        self.pos_conv = nn.Sequential(self.pos_conv,
+                                      SamePad(args.conv_pos), nn.GELU())
+
+        if hasattr(args, "relative_position_embedding"):
+            self.relative_position_embedding = args.relative_position_embedding
+            self.num_buckets = args.num_buckets
+            self.max_distance = args.max_distance
+        else:
+            self.relative_position_embedding = False
+            self.num_buckets = 0
+            self.max_distance = 0
+
+        self.layers = nn.ModuleList([
+            TransformerSentenceEncoderLayer(
+                embedding_dim=self.embedding_dim,
+                ffn_embedding_dim=args.encoder_ffn_embed_dim,
+                num_attention_heads=args.encoder_attention_heads,
+                dropout=self.dropout,
+                attention_dropout=args.attention_dropout,
+                activation_dropout=args.activation_dropout,
+                activation_fn=args.activation_fn,
+                layer_norm_first=args.layer_norm_first,
+                deep_norm=args.deep_norm,
+                has_relative_attention_bias=self.relative_position_embedding,
+                num_buckets=self.num_buckets,
+                max_distance=self.max_distance,
+                gru_rel_pos=args.gru_rel_pos,
+                encoder_layers=args.encoder_layers, )
+            for i in range(args.encoder_layers)
+        ])
+        if self.relative_position_embedding:
+            for i in range(1, args.encoder_layers):
+                del self.layers[i].self_attn.relative_attention_bias
+                self.layers[i].self_attn.relative_attention_bias = self.layers[
+                    0].self_attn.relative_attention_bias
+
+        self.layer_norm_first = args.layer_norm_first
+        self.layer_norm = LayerNorm(self.embedding_dim)
+        self.layerdrop = args.encoder_layerdrop
+
+        self.apply(init_bert_params)
+
+        if args.deep_norm:
+            deep_norm_beta = math.pow(8 * args.encoder_layers, -1 / 4)
+            for i in range(args.encoder_layers):
+                nn.init.xavier_normal_(
+                    self.layers[i].self_attn.k_proj.weight, gain=1)
+                nn.init.xavier_normal_(
+                    self.layers[i].self_attn.v_proj.weight, gain=deep_norm_beta)
+                nn.init.xavier_normal_(
+                    self.layers[i].self_attn.q_proj.weight, gain=1)
+                nn.init.xavier_normal_(
+                    self.layers[i].self_attn.out_proj.weight,
+                    gain=deep_norm_beta)
+                nn.init.xavier_normal_(
+                    self.layers[i].fc1.weight, gain=deep_norm_beta)
+                nn.init.xavier_normal_(
+                    self.layers[i].fc2.weight, gain=deep_norm_beta)
+
+        self.layer_wise_gradient_decay_ratio = getattr(
+            args, "layer_wise_gradient_decay_ratio", 1)
+
+    def forward(self, x, padding_mask=None, layer=None):
+        x, layer_results = self.extract_features(x, padding_mask, layer)
+
+        if self.layer_norm_first and layer is None:
+            x = self.layer_norm(x)
+
+        return x, layer_results
+
+    def extract_features(self, x, padding_mask=None, tgt_layer=None):
+
+        if padding_mask is not None:
+            x[padding_mask] = 0
+
+        x_conv = self.pos_conv(x.transpose(1, 2))
+        x_conv = x_conv.transpose(1, 2)
+        x = x + x_conv
+
+        if not self.layer_norm_first:
+            x = self.layer_norm(x)
+
+        x = F.dropout(x, p=self.dropout, training=self.training)
+
+        # B x T x C -> T x B x C
+        x = x.transpose(0, 1)
+
+        layer_results = []
+        z = None
+        if tgt_layer is not None:
+            layer_results.append((x, z))
+        r = None
+        pos_bias = None
+        for i, layer in enumerate(self.layers):
+            if self.layer_wise_gradient_decay_ratio != 1.0:
+                x = GradMultiply.apply(x, self.layer_wise_gradient_decay_ratio)
+            dropout_probability = np.random.random()
+            if not self.training or (dropout_probability > self.layerdrop):
+                x, z, pos_bias = layer(
+                    x,
+                    self_attn_padding_mask=padding_mask,
+                    need_weights=False,
+                    pos_bias=pos_bias)
+            if tgt_layer is not None:
+                layer_results.append((x, z))
+            if i == tgt_layer:
+                r = x
+                break
+
+        if r is not None:
+            x = r
+
+        # T x B x C -> B x T x C
+        x = x.transpose(0, 1)
+
+        return x, layer_results
+
+
+class TransformerSentenceEncoderLayer(nn.Module):
+    def __init__(
+            self,
+            embedding_dim: float=768,
+            ffn_embedding_dim: float=3072,
+            num_attention_heads: float=8,
+            dropout: float=0.1,
+            attention_dropout: float=0.1,
+            activation_dropout: float=0.1,
+            activation_fn: str="relu",
+            layer_norm_first: bool=False,
+            deep_norm: bool=False,
+            has_relative_attention_bias: bool=False,
+            num_buckets: int=0,
+            max_distance: int=0,
+            rescale_init: bool=False,
+            gru_rel_pos: bool=False,
+            encoder_layers: int=0, ) -> None:
+
+        super().__init__()
+        self.embedding_dim = embedding_dim
+        self.dropout = dropout
+        self.activation_dropout = activation_dropout
+
+        self.activation_name = activation_fn
+        self.activation_fn = get_activation_fn(activation_fn)
+        self.self_attn = MultiheadAttention(
+            self.embedding_dim,
+            num_attention_heads,
+            dropout=attention_dropout,
+            self_attention=True,
+            has_relative_attention_bias=has_relative_attention_bias,
+            num_buckets=num_buckets,
+            max_distance=max_distance,
+            rescale_init=rescale_init,
+            gru_rel_pos=gru_rel_pos, )
+
+        self.dropout1 = nn.Dropout(dropout)
+        self.dropout2 = nn.Dropout(self.activation_dropout)
+        self.dropout3 = nn.Dropout(dropout)
+
+        self.layer_norm_first = layer_norm_first
+
+        self.self_attn_layer_norm = LayerNorm(self.embedding_dim)
+
+        if self.activation_name == "glu":
+            self.fc1 = GLU_Linear(self.embedding_dim, ffn_embedding_dim,
+                                  "swish")
+        else:
+            self.fc1 = nn.Linear(self.embedding_dim, ffn_embedding_dim)
+        self.fc2 = nn.Linear(ffn_embedding_dim, self.embedding_dim)
+
+        self.final_layer_norm = LayerNorm(self.embedding_dim)
+
+        self.deep_norm = deep_norm
+        if self.deep_norm:
+            self.deep_norm_alpha = math.pow(2 * encoder_layers, 1 / 4)
+        else:
+            self.deep_norm_alpha = 1
+
+    def forward(self,
+                x: torch.Tensor,
+                self_attn_mask: torch.Tensor=None,
+                self_attn_padding_mask: torch.Tensor=None,
+                need_weights: bool=False,
+                pos_bias=None):
+        residual = x
+
+        if self.layer_norm_first:
+            x = self.self_attn_layer_norm(x)
+            x, attn, pos_bias = self.self_attn(
+                query=x,
+                key=x,
+                value=x,
+                key_padding_mask=self_attn_padding_mask,
+                need_weights=False,
+                attn_mask=self_attn_mask,
+                position_bias=pos_bias)
+            x = self.dropout1(x)
+            x = residual + x
+
+            residual = x
+            x = self.final_layer_norm(x)
+            if self.activation_name == "glu":
+                x = self.fc1(x)
+            else:
+                x = self.activation_fn(self.fc1(x))
+            x = self.dropout2(x)
+            x = self.fc2(x)
+            x = self.dropout3(x)
+            x = residual + x
+        else:
+            x, attn, pos_bias = self.self_attn(
+                query=x,
+                key=x,
+                value=x,
+                key_padding_mask=self_attn_padding_mask,
+                need_weights=need_weights,
+                attn_mask=self_attn_mask,
+                position_bias=pos_bias)
+
+            x = self.dropout1(x)
+            x = residual * self.deep_norm_alpha + x
+
+            x = self.self_attn_layer_norm(x)
+
+            residual = x
+            if self.activation_name == "glu":
+                x = self.fc1(x)
+            else:
+                x = self.activation_fn(self.fc1(x))
+            x = self.dropout2(x)
+            x = self.fc2(x)
+            x = self.dropout3(x)
+            x = residual * self.deep_norm_alpha + x
+            x = self.final_layer_norm(x)
+
+        return x, attn, pos_bias
+
+
+class MultiheadAttention(nn.Module):
+    """Multi-headed attention.
+
+    See "Attention Is All You Need" for more details.
+    """
+
+    def __init__(
+            self,
+            embed_dim,
+            num_heads,
+            kdim=None,
+            vdim=None,
+            dropout=0.0,
+            bias=True,
+            add_bias_kv=False,
+            add_zero_attn=False,
+            self_attention=False,
+            encoder_decoder_attention=False,
+            q_noise=0.0,
+            qn_block_size=8,
+            has_relative_attention_bias=False,
+            num_buckets=32,
+            max_distance=128,
+            gru_rel_pos=False,
+            rescale_init=False, ):
+        super().__init__()
+        self.embed_dim = embed_dim
+        self.kdim = kdim if kdim is not None else embed_dim
+        self.vdim = vdim if vdim is not None else embed_dim
+        self.qkv_same_dim = self.kdim == embed_dim and self.vdim == embed_dim
+
+        self.num_heads = num_heads
+        self.dropout_module = nn.Dropout(dropout)
+
+        self.has_relative_attention_bias = has_relative_attention_bias
+        self.num_buckets = num_buckets
+        self.max_distance = max_distance
+        if self.has_relative_attention_bias:
+            self.relative_attention_bias = nn.Embedding(num_buckets, num_heads)
+
+        self.head_dim = embed_dim // num_heads
+        self.q_head_dim = self.head_dim
+        self.k_head_dim = self.head_dim
+        assert (self.head_dim * num_heads == self.embed_dim
+                ), "embed_dim must be divisible by num_heads"
+        self.scaling = self.head_dim**-0.5
+
+        self.self_attention = self_attention
+        self.encoder_decoder_attention = encoder_decoder_attention
+
+        assert not self.self_attention or self.qkv_same_dim, (
+            "Self-attention requires query, key and "
+            "value to be of the same size")
+
+        k_bias = True
+        if rescale_init:
+            k_bias = False
+
+        k_embed_dim = embed_dim
+        q_embed_dim = embed_dim
+
+        self.k_proj = quant_noise(
+            nn.Linear(self.kdim, k_embed_dim, bias=k_bias), q_noise,
+            qn_block_size)
+        self.v_proj = quant_noise(
+            nn.Linear(self.vdim, embed_dim, bias=bias), q_noise, qn_block_size)
+        self.q_proj = quant_noise(
+            nn.Linear(embed_dim, q_embed_dim, bias=bias), q_noise,
+            qn_block_size)
+
+        self.out_proj = quant_noise(
+            nn.Linear(embed_dim, embed_dim, bias=bias), q_noise, qn_block_size)
+
+        if add_bias_kv:
+            self.bias_k = Parameter(torch.Tensor(1, 1, embed_dim))
+            self.bias_v = Parameter(torch.Tensor(1, 1, embed_dim))
+        else:
+            self.bias_k = self.bias_v = None
+
+        self.add_zero_attn = add_zero_attn
+
+        self.gru_rel_pos = gru_rel_pos
+        if self.gru_rel_pos:
+            self.grep_linear = nn.Linear(self.q_head_dim, 8)
+            self.grep_a = nn.Parameter(torch.ones(1, num_heads, 1, 1))
+
+        self.reset_parameters()
+
+    def reset_parameters(self):
+        if self.qkv_same_dim:
+            # Empirically observed the convergence to be much better with
+            # the scaled initialization
+            nn.init.xavier_uniform_(self.k_proj.weight, gain=1 / math.sqrt(2))
+            nn.init.xavier_uniform_(self.v_proj.weight, gain=1 / math.sqrt(2))
+            nn.init.xavier_uniform_(self.q_proj.weight, gain=1 / math.sqrt(2))
+        else:
+            nn.init.xavier_uniform_(self.k_proj.weight)
+            nn.init.xavier_uniform_(self.v_proj.weight)
+            nn.init.xavier_uniform_(self.q_proj.weight)
+
+        nn.init.xavier_uniform_(self.out_proj.weight)
+        if self.out_proj.bias is not None:
+            nn.init.constant_(self.out_proj.bias, 0.0)
+        if self.bias_k is not None:
+            nn.init.xavier_normal_(self.bias_k)
+        if self.bias_v is not None:
+            nn.init.xavier_normal_(self.bias_v)
+        if self.has_relative_attention_bias:
+            nn.init.xavier_normal_(self.relative_attention_bias.weight)
+
+    def _relative_positions_bucket(self, relative_positions,
+                                   bidirectional=True):
+        num_buckets = self.num_buckets
+        max_distance = self.max_distance
+        relative_buckets = 0
+
+        if bidirectional:
+            num_buckets = num_buckets // 2
+            relative_buckets += (
+                relative_positions > 0).to(torch.long) * num_buckets
+            relative_positions = torch.abs(relative_positions)
+        else:
+            relative_positions = -torch.min(
+                relative_positions, torch.zeros_like(relative_positions))
+
+        max_exact = num_buckets // 2
+        is_small = relative_positions < max_exact
+
+        relative_postion_if_large = max_exact + (
+            torch.log(relative_positions.float() / max_exact) / math.log(
+                max_distance / max_exact) *
+            (num_buckets - max_exact)).to(torch.long)
+        relative_postion_if_large = torch.min(
+            relative_postion_if_large,
+            torch.full_like(relative_postion_if_large, num_buckets - 1))
+
+        relative_buckets += torch.where(is_small, relative_positions,
+                                        relative_postion_if_large)
+        return relative_buckets
+
+    def compute_bias(self, query_length, key_length):
+        context_position = torch.arange(query_length, dtype=torch.long)[:, None]
+        memory_position = torch.arange(key_length, dtype=torch.long)[None, :]
+        relative_position = memory_position - context_position
+        relative_position_bucket = self._relative_positions_bucket(
+            relative_position, bidirectional=True)
+        relative_position_bucket = relative_position_bucket.to(
+            self.relative_attention_bias.weight.device)
+        values = self.relative_attention_bias(relative_position_bucket)
+        values = values.permute([2, 0, 1])
+        return values
+
+    def forward(self,
+                query,
+                key: Optional[Tensor],
+                value: Optional[Tensor],
+                key_padding_mask: Optional[Tensor]=None,
+                incremental_state: Optional[Dict[str, Dict[str, Optional[
+                    Tensor]]]]=None,
+                need_weights: bool=True,
+                static_kv: bool=False,
+                attn_mask: Optional[Tensor]=None,
+                before_softmax: bool=False,
+                need_head_weights: bool=False,
+                position_bias: Optional[Tensor]=None
+                ) -> Tuple[Tensor, Optional[Tensor], Optional[Tensor]]:
+        """Input shape: Time x Batch x Channel
+
+        Args:
+            key_padding_mask (ByteTensor, optional): mask to exclude
+                keys that are pads, of shape `(batch, src_len)`, where
+                padding elements are indicated by 1s.
+            need_weights (bool, optional): return the attention weights,
+                averaged over heads (default: False).
+            attn_mask (ByteTensor, optional): typically used to
+                implement causal attention, where the mask prevents the
+                attention from looking forward in time (default: None).
+            before_softmax (bool, optional): return the raw attention
+                weights and values before the attention softmax.
+            need_head_weights (bool, optional): return the attention
+                weights for each head. Implies *need_weights*. Default:
+                return the average attention weights over all heads.
+        """
+        if need_head_weights:
+            need_weights = True
+
+        is_tpu = query.device.type == "xla"
+
+        tgt_len, bsz, embed_dim = query.size()
+        src_len = tgt_len
+        assert embed_dim == self.embed_dim
+        assert list(query.size()) == [tgt_len, bsz, embed_dim]
+        if key is not None:
+            src_len, key_bsz, _ = key.size()
+            if not torch.jit.is_scripting():
+                assert key_bsz == bsz
+                assert value is not None
+                assert src_len, bsz == value.shape[:2]
+
+        if self.has_relative_attention_bias and position_bias is None:
+            position_bias = self.compute_bias(tgt_len, src_len)
+            position_bias = position_bias.unsqueeze(0).repeat(
+                bsz, 1, 1, 1).view(bsz * self.num_heads, tgt_len, src_len)
+
+        if incremental_state is not None:
+            saved_state = self._get_input_buffer(incremental_state)
+            if saved_state is not None and "prev_key" in saved_state:
+                # previous time steps are cached - no need to recompute
+                # key and value if they are static
+                if static_kv:
+                    assert self.encoder_decoder_attention and not self.self_attention
+                    key = value = None
+        else:
+            saved_state = None
+
+        if self.self_attention:
+            q = self.q_proj(query)
+            k = self.k_proj(query)
+            v = self.v_proj(query)
+        elif self.encoder_decoder_attention:
+            # encoder-decoder attention
+            q = self.q_proj(query)
+            if key is None:
+                assert value is None
+                k = v = None
+            else:
+                k = self.k_proj(key)
+                v = self.v_proj(key)
+
+        else:
+            assert key is not None and value is not None
+            q = self.q_proj(query)
+            k = self.k_proj(key)
+            v = self.v_proj(value)
+        q *= self.scaling
+        alpha = 32
+        q *= 1 / alpha
+
+        if self.bias_k is not None:
+            assert self.bias_v is not None
+            k = torch.cat([k, self.bias_k.repeat(1, bsz, 1)])
+            v = torch.cat([v, self.bias_v.repeat(1, bsz, 1)])
+            if attn_mask is not None:
+                attn_mask = torch.cat(
+                    [attn_mask, attn_mask.new_zeros(attn_mask.size(0), 1)],
+                    dim=1)
+            if key_padding_mask is not None:
+                key_padding_mask = torch.cat(
+                    [
+                        key_padding_mask,
+                        key_padding_mask.new_zeros(key_padding_mask.size(0), 1),
+                    ],
+                    dim=1, )
+
+        q = (q.contiguous().view(tgt_len, bsz * self.num_heads, self.q_head_dim)
+             .transpose(0, 1))
+        if k is not None:
+            k = (k.contiguous().view(-1, bsz * self.num_heads, self.k_head_dim)
+                 .transpose(0, 1))
+        if v is not None:
+            v = (v.contiguous().view(-1, bsz * self.num_heads, self.head_dim)
+                 .transpose(0, 1))
+
+        if saved_state is not None:
+            # saved states are stored with shape (bsz, num_heads, seq_len, head_dim)
+            if "prev_key" in saved_state:
+                _prev_key = saved_state["prev_key"]
+                assert _prev_key is not None
+                prev_key = _prev_key.view(bsz * self.num_heads, -1,
+                                          self.head_dim)
+                if static_kv:
+                    k = prev_key
+                else:
+                    assert k is not None
+                    k = torch.cat([prev_key, k], dim=1)
+                src_len = k.size(1)
+            if "prev_value" in saved_state:
+                _prev_value = saved_state["prev_value"]
+                assert _prev_value is not None
+                prev_value = _prev_value.view(bsz * self.num_heads, -1,
+                                              self.head_dim)
+                if static_kv:
+                    v = prev_value
+                else:
+                    assert v is not None
+                    v = torch.cat([prev_value, v], dim=1)
+            prev_key_padding_mask: Optional[Tensor] = None
+            if "prev_key_padding_mask" in saved_state:
+                prev_key_padding_mask = saved_state["prev_key_padding_mask"]
+            assert k is not None and v is not None
+            key_padding_mask = MultiheadAttention._append_prev_key_padding_mask(
+                key_padding_mask=key_padding_mask,
+                prev_key_padding_mask=prev_key_padding_mask,
+                batch_size=bsz,
+                src_len=k.size(1),
+                static_kv=static_kv, )
+
+            saved_state["prev_key"] = k.view(bsz, self.num_heads, -1,
+                                             self.head_dim)
+            saved_state["prev_value"] = v.view(bsz, self.num_heads, -1,
+                                               self.head_dim)
+            saved_state["prev_key_padding_mask"] = key_padding_mask
+            # In this branch incremental_state is never None
+            assert incremental_state is not None
+            incremental_state = self._set_input_buffer(incremental_state,
+                                                       saved_state)
+        assert k is not None
+        assert k.size(1) == src_len
+
+        # This is part of a workaround to get around fork/join parallelism
+        # not supporting Optional types.
+        if key_padding_mask is not None and key_padding_mask.dim() == 0:
+            key_padding_mask = None
+
+        if key_padding_mask is not None:
+            assert key_padding_mask.size(0) == bsz
+            assert key_padding_mask.size(1) == src_len
+
+        if self.add_zero_attn:
+            assert v is not None
+            src_len += 1
+            k = torch.cat(
+                [k, k.new_zeros((k.size(0), 1) + k.size()[2:])], dim=1)
+            v = torch.cat(
+                [v, v.new_zeros((v.size(0), 1) + v.size()[2:])], dim=1)
+            if attn_mask is not None:
+                attn_mask = torch.cat(
+                    [attn_mask, attn_mask.new_zeros(attn_mask.size(0), 1)],
+                    dim=1)
+            if key_padding_mask is not None:
+                key_padding_mask = torch.cat(
+                    [
+                        key_padding_mask,
+                        torch.zeros(key_padding_mask.size(0),
+                                    1).type_as(key_padding_mask),
+                    ],
+                    dim=1, )
+
+        attn_weights = torch.bmm(q, k.transpose(1, 2))
+        attn_weights = (
+            attn_weights - attn_weights.max(dim=-1, keepdim=True)[0]) * alpha
+        attn_weights = self.apply_sparse_mask(attn_weights, tgt_len, src_len,
+                                              bsz)
+
+        assert list(
+            attn_weights.size()) == [bsz * self.num_heads, tgt_len, src_len]
+
+        if attn_mask is not None:
+            attn_mask = attn_mask.unsqueeze(0)
+            attn_weights += attn_mask
+
+        if key_padding_mask is not None:
+            # don't attend to padding symbols
+            attn_weights = attn_weights.view(bsz, self.num_heads, tgt_len,
+                                             src_len)
+            if not is_tpu:
+                attn_weights = attn_weights.masked_fill(
+                    key_padding_mask.unsqueeze(1).unsqueeze(2).to(torch.bool),
+                    float("-inf"), )
+            else:
+                attn_weights = attn_weights.transpose(0, 2)
+                attn_weights = attn_weights.masked_fill(key_padding_mask,
+                                                        float("-inf"))
+                attn_weights = attn_weights.transpose(0, 2)
+            attn_weights = attn_weights.view(bsz * self.num_heads, tgt_len,
+                                             src_len)
+
+        if before_softmax:
+            return attn_weights, v, position_bias
+
+        if position_bias is not None:
+            attn_mask_rel_pos = position_bias
+            if self.gru_rel_pos == 1:
+                query_layer = q.view(bsz, self.num_heads, tgt_len,
+                                     self.q_head_dim) * alpha / self.scaling
+                _B, _H, _L, __ = query_layer.size()
+                gate_a, gate_b = torch.sigmoid(
+                    self.grep_linear(query_layer).view(_B, _H, _L, 2, 4).sum(
+                        -1, keepdim=False)).chunk(
+                            2, dim=-1)
+                gate_a_1 = gate_a * (gate_b * self.grep_a - 1.0) + 2.0
+                attn_mask_rel_pos = gate_a_1.view(bsz * self.num_heads, tgt_len,
+                                                  1) * position_bias
+
+            attn_mask_rel_pos = attn_mask_rel_pos.view(attn_weights.size())
+
+            attn_weights = attn_weights + attn_mask_rel_pos
+
+        attn_weights_float = F.softmax(attn_weights, dim=-1)
+        attn_weights = attn_weights_float.type_as(attn_weights)
+        attn_probs = self.dropout_module(attn_weights)
+
+        assert v is not None
+        attn = torch.bmm(attn_probs, v)
+        assert list(
+            attn.size()) == [bsz * self.num_heads, tgt_len, self.head_dim]
+        attn = attn.transpose(0, 1).contiguous().view(tgt_len, bsz, embed_dim)
+        attn = self.out_proj(attn)
+        attn_weights: Optional[Tensor] = None
+        if need_weights:
+            attn_weights = attn_weights_float.view(bsz, self.num_heads, tgt_len,
+                                                   src_len).transpose(1, 0)
+            if not need_head_weights:
+                # average attention weights over heads
+                attn_weights = attn_weights.mean(dim=0)
+
+        return attn, attn_weights, position_bias
+
+    @staticmethod
+    def _append_prev_key_padding_mask(
+            key_padding_mask: Optional[Tensor],
+            prev_key_padding_mask: Optional[Tensor],
+            batch_size: int,
+            src_len: int,
+            static_kv: bool, ) -> Optional[Tensor]:
+        # saved key padding masks have shape (bsz, seq_len)
+        if prev_key_padding_mask is not None and static_kv:
+            new_key_padding_mask = prev_key_padding_mask
+        elif prev_key_padding_mask is not None and key_padding_mask is not None:
+            new_key_padding_mask = torch.cat(
+                [prev_key_padding_mask.float(), key_padding_mask.float()],
+                dim=1)
+        # During incremental decoding, as the padding token enters and
+        # leaves the frame, there will be a time when prev or current
+        # is None
+        elif prev_key_padding_mask is not None:
+            if src_len > prev_key_padding_mask.size(1):
+                filler = torch.zeros(
+                    (batch_size, src_len - prev_key_padding_mask.size(1)),
+                    device=prev_key_padding_mask.device, )
+                new_key_padding_mask = torch.cat(
+                    [prev_key_padding_mask.float(), filler.float()], dim=1)
+            else:
+                new_key_padding_mask = prev_key_padding_mask.float()
+        elif key_padding_mask is not None:
+            if src_len > key_padding_mask.size(1):
+                filler = torch.zeros(
+                    (batch_size, src_len - key_padding_mask.size(1)),
+                    device=key_padding_mask.device, )
+                new_key_padding_mask = torch.cat(
+                    [filler.float(), key_padding_mask.float()], dim=1)
+            else:
+                new_key_padding_mask = key_padding_mask.float()
+        else:
+            new_key_padding_mask = prev_key_padding_mask
+        return new_key_padding_mask
+
+    def _get_input_buffer(
+            self,
+            incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]]
+    ) -> Dict[str, Optional[Tensor]]:
+        result = self.get_incremental_state(incremental_state, "attn_state")
+        if result is not None:
+            return result
+        else:
+            empty_result: Dict[str, Optional[Tensor]] = {}
+            return empty_result
+
+    def _set_input_buffer(
+            self,
+            incremental_state: Dict[str, Dict[str, Optional[Tensor]]],
+            buffer: Dict[str, Optional[Tensor]], ):
+        return self.set_incremental_state(incremental_state, "attn_state",
+                                          buffer)
+
+    def apply_sparse_mask(self,
+                          attn_weights,
+                          tgt_len: int,
+                          src_len: int,
+                          bsz: int):
+        return attn_weights
+
+
+def init_bert_params(module):
+    """
+    Initialize the weights specific to the BERT Model.
+    This overrides the default initializations depending on the specified arguments.
+        1. If normal_init_linear_weights is set then weights of linear
+           layer will be initialized using the normal distribution and
+           bais will be set to the specified value.
+        2. If normal_init_embed_weights is set then weights of embedding
+           layer will be initialized using the normal distribution.
+        3. If normal_init_proj_weights is set then weights of
+           in_project_weight for MultiHeadAttention initialized using
+           the normal distribution (to be validated).
+    """
+
+    def normal_(data):
+        # with FSDP, module params will be on CUDA, so we cast them back to CPU
+        # so that the RNG is consistent with and without FSDP
+        data.copy_(data.cpu().normal_(mean=0.0, std=0.02).to(data.device))
+
+    if isinstance(module, nn.Linear):
+        normal_(module.weight.data)
+        if module.bias is not None:
+            module.bias.data.zero_()
+    if isinstance(module, nn.Embedding):
+        normal_(module.weight.data)
+        if module.padding_idx is not None:
+            module.weight.data[module.padding_idx].zero_()
+    if isinstance(module, MultiheadAttention):
+        normal_(module.q_proj.weight.data)
+        normal_(module.k_proj.weight.data)
+        normal_(module.v_proj.weight.data)
diff --git a/AR/exps/beats/config.py b/AR/exps/beats/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..2115f7fa1509bd3e78c778b874c1a362dcd8d7f8
--- /dev/null
+++ b/AR/exps/beats/config.py
@@ -0,0 +1,19 @@
+import json
+import os
+
+# 获取当前脚本的所在目录
+script_dir = os.path.dirname(os.path.abspath(__file__))
+
+# JSON 文件的文件名
+json_filename = "ontology.json"
+
+# 构建 JSON 文件的完整路径
+json_path = os.path.join(script_dir, json_filename)
+
+id_name_dict = {}
+
+with open(json_path, 'r') as f:
+    json_items = json.load(f)
+# '/m/0dgw9r' -> 'Human sounds' and etc.
+for item in json_items:
+    id_name_dict[item['id']] = item['name']
diff --git a/AR/exps/beats/modules.py b/AR/exps/beats/modules.py
new file mode 100644
index 0000000000000000000000000000000000000000..1eb042717628e3f497242d1c0114dfab01af10f1
--- /dev/null
+++ b/AR/exps/beats/modules.py
@@ -0,0 +1,220 @@
+# --------------------------------------------------------
+# BEATs: Audio Pre-Training with Acoustic Tokenizers (https://arxiv.org/abs/2212.09058)
+# Github source: https://github.com/microsoft/unilm/tree/master/beats
+# Copyright (c) 2022 Microsoft
+# Licensed under The MIT License [see LICENSE for details]
+# Based on fairseq code bases
+# https://github.com/pytorch/fairseq
+# --------------------------------------------------------
+import math
+import warnings
+
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+
+class GradMultiply(torch.autograd.Function):
+    @staticmethod
+    def forward(ctx, x, scale):
+        ctx.scale = scale
+        res = x.new(x)
+        return res
+
+    @staticmethod
+    def backward(ctx, grad):
+        return grad * ctx.scale, None
+
+
+class SamePad(nn.Module):
+    def __init__(self, kernel_size, causal=False):
+        super().__init__()
+        if causal:
+            self.remove = kernel_size - 1
+        else:
+            self.remove = 1 if kernel_size % 2 == 0 else 0
+
+    def forward(self, x):
+        if self.remove > 0:
+            x = x[:, :, :-self.remove]
+        return x
+
+
+class Swish(nn.Module):
+    def __init__(self):
+        super(Swish, self).__init__()
+        self.act = torch.nn.Sigmoid()
+
+    def forward(self, x):
+        return x * self.act(x)
+
+
+class GLU_Linear(nn.Module):
+    def __init__(self,
+                 input_dim,
+                 output_dim,
+                 glu_type="sigmoid",
+                 bias_in_glu=True):
+        super(GLU_Linear, self).__init__()
+
+        self.glu_type = glu_type
+        self.output_dim = output_dim
+
+        if glu_type == "sigmoid":
+            self.glu_act = torch.nn.Sigmoid()
+        elif glu_type == "swish":
+            self.glu_act = Swish()
+        elif glu_type == "relu":
+            self.glu_act = torch.nn.ReLU()
+        elif glu_type == "gelu":
+            self.glu_act = torch.nn.GELU()
+
+        if bias_in_glu:
+            self.linear = nn.Linear(input_dim, output_dim * 2, True)
+        else:
+            self.linear = nn.Linear(input_dim, output_dim * 2, False)
+
+    def forward(self, x):
+        # to be consistent with GLU_Linear, we assume the input always has the #channel (#dim) in the last dimension of the tensor, so need to switch the dimension first for 1D-Conv case
+        x = self.linear(x)
+
+        if self.glu_type == "bilinear":
+            x = (x[:, :, 0:self.output_dim] *
+                 x[:, :, self.output_dim:self.output_dim * 2])
+        else:
+            x = (x[:, :, 0:self.output_dim] *
+                 self.glu_act(x[:, :, self.output_dim:self.output_dim * 2]))
+
+        return x
+
+
+def gelu_accurate(x):
+    if not hasattr(gelu_accurate, "_a"):
+        gelu_accurate._a = math.sqrt(2 / math.pi)
+    return (0.5 * x * (1 + torch.tanh(gelu_accurate._a *
+                                      (x + 0.044715 * torch.pow(x, 3)))))
+
+
+def gelu(x: torch.Tensor) -> torch.Tensor:
+    return torch.nn.functional.gelu(x.float()).type_as(x)
+
+
+def get_activation_fn(activation: str):
+    """Returns the activation function corresponding to `activation`"""
+
+    if activation == "relu":
+        return F.relu
+    elif activation == "gelu":
+        return gelu
+    elif activation == "gelu_fast":
+        warnings.warn(
+            "--activation-fn=gelu_fast has been renamed to gelu_accurate")
+        return gelu_accurate
+    elif activation == "gelu_accurate":
+        return gelu_accurate
+    elif activation == "tanh":
+        return torch.tanh
+    elif activation == "linear":
+        return lambda x: x
+    elif activation == "glu":
+        return lambda x: x
+    else:
+        raise RuntimeError(
+            "--activation-fn {} not supported".format(activation))
+
+
+def quant_noise(module, p, block_size):
+    """
+    Wraps modules and applies quantization noise to the weights for
+    subsequent quantization with Iterative Product Quantization as
+    described in "Training with Quantization Noise for Extreme Model Compression"
+
+    Args:
+        - module: nn.Module
+        - p: amount of Quantization Noise
+        - block_size: size of the blocks for subsequent quantization with iPQ
+
+    Remarks:
+        - Module weights must have the right sizes wrt the block size
+        - Only Linear, Embedding and Conv2d modules are supported for the moment
+        - For more detail on how to quantize by blocks with convolutional weights,
+          see "And the Bit Goes Down: Revisiting the Quantization of Neural Networks"
+        - We implement the simplest form of noise here as stated in the paper
+          which consists in randomly dropping blocks
+    """
+
+    # if no quantization noise, don't register hook
+    if p <= 0:
+        return module
+
+    # supported modules
+    assert isinstance(module, (nn.Linear, nn.Embedding, nn.Conv2d))
+
+    # test whether module.weight has the right sizes wrt block_size
+    is_conv = module.weight.ndim == 4
+
+    # 2D matrix
+    if not is_conv:
+        assert (
+            module.weight.size(1) %
+            block_size == 0), "Input features must be a multiple of block sizes"
+
+    # 4D matrix
+    else:
+        # 1x1 convolutions
+        if module.kernel_size == (1, 1):
+            assert (module.in_channels % block_size == 0
+                    ), "Input channels must be a multiple of block sizes"
+        # regular convolutions
+        else:
+            k = module.kernel_size[0] * module.kernel_size[1]
+            assert k % block_size == 0, "Kernel size must be a multiple of block size"
+
+    def _forward_pre_hook(mod, input):
+        # no noise for evaluation
+        if mod.training:
+            if not is_conv:
+                # gather weight and sizes
+                weight = mod.weight
+                in_features = weight.size(1)
+                out_features = weight.size(0)
+
+                # split weight matrix into blocks and randomly drop selected blocks
+                mask = torch.zeros(
+                    in_features // block_size * out_features,
+                    device=weight.device)
+                mask.bernoulli_(p)
+                mask = mask.repeat_interleave(block_size, -1).view(-1,
+                                                                   in_features)
+
+            else:
+                # gather weight and sizes
+                weight = mod.weight
+                in_channels = mod.in_channels
+                out_channels = mod.out_channels
+
+                # split weight matrix into blocks and randomly drop selected blocks
+                if mod.kernel_size == (1, 1):
+                    mask = torch.zeros(
+                        int(in_channels // block_size * out_channels),
+                        device=weight.device, )
+                    mask.bernoulli_(p)
+                    mask = mask.repeat_interleave(block_size, -1).view(
+                        -1, in_channels)
+                else:
+                    mask = torch.zeros(
+                        weight.size(0), weight.size(1), device=weight.device)
+                    mask.bernoulli_(p)
+                    mask = (
+                        mask.unsqueeze(2).unsqueeze(3)
+                        .repeat(1, 1, mod.kernel_size[0], mod.kernel_size[1]))
+
+            # scale weights and apply mask
+            mask = mask.to(
+                torch.
+                bool)  # x.bool() is not currently supported in TorchScript
+            s = 1 / (1 - p)
+            mod.weight.data = s * weight.masked_fill(mask, 0)
+
+    module.register_forward_pre_hook(_forward_pre_hook)
+    return module
diff --git a/AR/exps/beats/ontology.json b/AR/exps/beats/ontology.json
new file mode 100644
index 0000000000000000000000000000000000000000..cee2c5055a4778833dd165cae4010086e6d4bdc5
--- /dev/null
+++ b/AR/exps/beats/ontology.json
@@ -0,0 +1,5690 @@
+[
+  {
+    "id": "/m/0dgw9r",
+    "name": "Human sounds",
+    "description": "Sounds produced by the human body through the actions of the individual.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/09l8g", "/m/01w250", "/m/09hlz4", "/m/0bpl036", "/m/0160x5", "/m/0k65p", "/m/01jg02", "/m/04xp5v", "/t/dd00012"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/09l8g",
+    "name": "Human voice",
+    "description": "The human voice consists of sound made by a human being using the vocal folds for talking, singing, laughing, crying, screaming, etc. The human voice is specifically a part of human sound production in which the vocal folds are the primary sound source.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Human_voice",
+    "positive_examples": [],
+    "child_ids": ["/m/09x0r", "/m/07p6fty", "/m/03qc9zr", "/m/02rtxlg", "/m/01j3sz", "/m/0463cq4", "/m/07qw_06", "/m/07plz5l", "/m/015lz1", "/m/02fxyj", "/m/07s2xch", "/m/07r4k75", "/m/01j423"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/09x0r",
+    "name": "Speech",
+    "description": "Speech is the vocalized form of human communication, created out of the phonetic combination of a limited set of vowel and consonant speech sound units.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Speech",
+    "positive_examples": ["youtu.be/8uI9H5jGRV8?start=30&end=40", "youtu.be/cz8QIJHjZh4?start=30&end=40", "youtu.be/91FIbeKyIhw?start=30&end=40", "youtu.be/V3HdocEv8gw?start=220&end=230", "youtu.be/a8igK2oWlVY?start=30&end=40", "youtu.be/2hvTtM7VdJg?start=30&end=40", "youtu.be/S7ytQItOrkk?start=30&end=40", "youtu.be/Zyl2Q3GepPA?start=30&end=40", "youtu.be/CU1qRm_Bcps?start=30&end=40"],
+    "child_ids": ["/m/05zppz", "/m/02zsn", "/m/0ytgt", "/m/01h8n0", "/m/02qldy", "/m/0261r1", "/m/0brhx"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05zppz",
+    "name": "Male speech, man speaking",
+    "description": "Speech uttered by an adult male human.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/6niRPYpLOpQ?start=30&end=40", "youtu.be/fPgUDHwQOmM?start=320&end=330", "youtu.be/g3YNJ3ESIW0?start=30&end=40", "youtu.be/Dys9DJoFnGA?start=30&end=40", "youtu.be/3PESOesDniw?start=30&end=40", "youtu.be/E8RfeFAzHK4?start=30&end=40", "youtu.be/A_WSbkJozPs?start=90&end=100", "youtu.be/-yZuFZRojYA?start=30&end=40", "youtu.be/ECOK21oFttk?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02zsn",
+    "name": "Female speech, woman speaking",
+    "description": "Speech uttered by an adult female human.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/4l05nCOnIRg?start=30&end=40", "youtu.be/5zyOhZsvIzI?start=30&end=40", "youtu.be/q0wv9AOl4r0?start=100&end=110", "youtu.be/AyPqm-tm2y4?start=30&end=40", "youtu.be/1xXqIpjxYG4?start=30&end=40", "youtu.be/xYPZJkfiyjk?start=90&end=100", "youtu.be/46lVxNflfDw?start=30&end=40", "youtu.be/8OpLsWMn6P0?start=30&end=40", "youtu.be/WLi5_z61zCE?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0ytgt",
+    "name": "Child speech, kid speaking",
+    "description": "Speech uttered by a human child, i.e. a human whose voice does not yet resemble that of an adult.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/iPIGoScYduI?start=210&end=220", "youtu.be/DiJgMH7vg1E?start=30&end=40", "youtu.be/yy0LZBmZRvE?start=60&end=70", "youtu.be/arz0xujSWdY?start=230&end=240", "youtu.be/-oC3FVOx62g?start=210&end=220", "youtu.be/5-R8zaohZrU?start=10&end=20", "youtu.be/OXJ77G_TqDc?start=40&end=50", "youtu.be/koW60o-aLjI?start=470&end=480", "youtu.be/uBVLhywbCQk?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01h8n0",
+    "name": "Conversation",
+    "description": "Interactive, spontaneous spoken communication between two or more people.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Conversation",
+    "positive_examples": ["youtu.be/4FQxw_49xAk?start=30&end=40", "youtu.be/0WcG16XxghA?start=30&end=40", "youtu.be/RHfaNoYg8vs?start=170&end=180", "youtu.be/twGajApu-7g?start=560&end=570", "youtu.be/A0Lpt0VWYCA?start=50&end=60", "youtu.be/ermWzXxDjOQ?start=110&end=120", "youtu.be/sEF1KNfvY90?start=230&end=240", "youtu.be/DhlPa8lUosM?start=300&end=310"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02qldy",
+    "name": "Narration, monologue",
+    "description": "Speech by a single human aimed at an audience (either present or assumed, as in a video blog).",
+    "citation_uri": "http://en.wikipedia.org/wiki/Narration",
+    "positive_examples": ["youtu.be/8maPz8qrmnM?start=30&end=40", "youtu.be/8vmb60ydHtY?start=30&end=40", "youtu.be/fL52Quhhomc?start=30&end=40", "youtu.be/6tXGhWY1I8I?start=30&end=40", "youtu.be/FwRo7yXVnL0?start=30&end=40", "youtu.be/TKPjvQtnELU?start=360&end=370", "youtu.be/Cf6AAX-r6wk?start=30&end=40", "youtu.be/EmLsodfGoes?start=30&end=40", "youtu.be/20lm7Ow9RSY?start=30&end=40", "youtu.be/25K0bryItv4?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0261r1",
+    "name": "Babbling",
+    "description": "Speech-like sounds uttered by a human that lack the deeper structure and meaning of conventional speech. Babbling is a stage in a child's development of language.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Babbling",
+    "positive_examples": ["youtu.be/ZR48r_8OhUI?start=50&end=60", "youtu.be/2ZxE0uMIfa0?start=10&end=20", "youtu.be/vFbu0dH7f-U?start=10&end=20", "youtu.be/soXBLBCaClA?start=90&end=100", "youtu.be/ICajcUYAan8?start=410&end=420", "youtu.be/lluzItlOMlQ?start=10&end=20", "youtu.be/EyCpVw_Xn60?start=130&end=140"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0brhx",
+    "name": "Speech synthesizer",
+    "description": "Artificially-produced human speech.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Speech_synthesis",
+    "positive_examples": ["youtu.be/Y1ywO5WfUqE?start=90&end=100", "youtu.be/-2Krnsj-edU?start=40&end=50", "youtu.be/0npIcSXb1Bc?start=13&end=23", "youtu.be/0wVUdVYmZ5A?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07p6fty",
+    "name": "Shout",
+    "description": "Talk in a loud voice to deliberately command attention or overcome interfering sounds. Does not have the stronger emotional connotations of Yell or Scream.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=shout",
+    "positive_examples": ["youtu.be/-aY64NxBVas?start=480&end=490", "youtu.be/mPr3kCL5y10?start=210&end=220", "youtu.be/5YB13i75Nr4?start=60&end=70", "youtu.be/X04FOAQFn5I?start=130&end=140"],
+    "child_ids": ["/m/07q4ntr", "/m/07rwj3x", "/m/07sr1lc", "/m/04gy_2", "/t/dd00135"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07q4ntr",
+    "name": "Bellow",
+    "description": "A very loud utterance by a person that seems more animal than human.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=bellow",
+    "positive_examples": ["youtu.be/EquXTta7QU0?start=230&end=240", "youtu.be/gLl7DnPIZd4?start=20&end=30", "youtu.be/bCqNjZRWogs?start=30&end=40", "youtu.be/EzIa5SQC7R0?start=30&end=40", "youtu.be/rGbppkm9MYs?start=90&end=100"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rwj3x",
+    "name": "Whoop",
+    "description": "A loud hooting cry of exultation or excitement.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=whoop",
+    "positive_examples": ["youtu.be/TKwuq-O67VE?start=9&end=19", "youtu.be/yfwQgGVZtqI?start=30&end=40", "youtu.be/2Z0FSALnSmM?start=30&end=40", "youtu.be/TDJ746q3sAU?start=170&end=180", "youtu.be/pB4Bh36b1Ss?start=30&end=40", "youtu.be/4Gw8jFlJyLI?start=50&end=60", "youtu.be/7yGHDT7r2u8?start=1&end=11", "youtu.be/5yD_YeSuTzQ?start=150&end=160", "youtu.be/NPkO63FcFXM?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07sr1lc",
+    "name": "Yell",
+    "description": "Utter or declare in a very loud voice that seems excessive or involuntary, or that is deliberately startling in order to command attention, as distinct from the pragmatically raised voice of Shout.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=yell",
+    "positive_examples": ["youtu.be/YMeuw-x86KU?start=30&end=40", "youtu.be/NMn-9tvzQZA?start=30&end=40", "youtu.be/AperXKEnTJ4?start=30&end=40", "youtu.be/pXawVUjQLok?start=30&end=40", "youtu.be/vOEF-FzwSlM?start=100&end=110"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04gy_2",
+    "name": "Battle cry",
+    "description": "A yell or chant taken up in battle, usually by members of the same combatant group, aiming at arousing aggression on one's own side and intimidating the enemy.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Battle_cry",
+    "positive_examples": ["youtu.be/iEfkkyrecGA?start=210&end=220", "youtu.be/8-xVEzStUkg?start=10&end=20", "youtu.be/aNhVWZI5DXY?start=130&end=140", "youtu.be/4Gz_dmk3v_A?start=30&end=40", "youtu.be/RATOmpfWqUo?start=180&end=190", "youtu.be/DRQPYwom_mY?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00135",
+    "name": "Children shouting",
+    "description": "The boisterous vocalizations of a group of children, for instance in a playground.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/W4AptCGYj5w?start=30&end=40", "youtu.be/w4VqralR-6E?start=10&end=20", "youtu.be/vsgHNEEOKxk?start=150&end=160", "youtu.be/7koyNkRHO8U?start=20&end=30", "youtu.be/Q8NC8aHonOU?start=70&end=80"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03qc9zr",
+    "name": "Screaming",
+    "description": "A sharp, high-pitched human vocalization; often an instinctive action indicating fear, pain, surprise, joy, anger, etc. Verbal content is absent or overwhelmed, unlike Shout and Yell.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Screaming",
+    "positive_examples": ["youtu.be/ZHrf_y9q96Q?start=20&end=30", "youtu.be/GqTExeZqXzw?start=20&end=30", "youtu.be/vgpAqgBIpdM?start=220&end=230", "youtu.be/GUsI_2tYVYM?start=29&end=39", "youtu.be/52waxTykuLc?start=30&end=40", "youtu.be/auC_LgwFF8g?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02rtxlg",
+    "name": "Whispering",
+    "description": "Unvoiced speech, usually intended to be quieter to avoid causing disturbance or being overheard.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Whispering",
+    "positive_examples": ["youtu.be/Tr6NMYItPJk?start=490&end=500", "youtu.be/wTjxa7yFyXQ?start=90&end=100", "youtu.be/a3xzicvE4Yk?start=270&end=280", "youtu.be/wAFz-WuuJ4o?start=210&end=220", "youtu.be/-26vNAAFWH0?start=350&end=360", "youtu.be/7S_iHrdfrvQ?start=30&end=40", "youtu.be/cus68zSHXDA?start=90&end=100", "youtu.be/CVGwF_-HXdo?start=540&end=550"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01j3sz",
+    "name": "Laughter",
+    "description": "The sound of rhythmical contractions of the diaphragm in response to stimuli such as tickling, or from humorous stories or thoughts.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Laughter",
+    "positive_examples": ["youtu.be/37hqUFpvl6A?start=40&end=50", "youtu.be/sjAKBnCgKt8?start=220&end=230", "youtu.be/ULTB6y2aj8I?start=40&end=50", "youtu.be/c0V_HAul7rI?start=30&end=40", "youtu.be/SwZ0V8bc2QY?start=350&end=360", "youtu.be/aXS2iHSQE6g?start=10&end=20", "youtu.be/O1snVHXG2j4?start=390&end=400", "youtu.be/4e-qMxrus0A?start=80&end=90", "youtu.be/rPV1mbwWms0?start=60&end=70"],
+    "child_ids": ["/t/dd00001", "/m/07r660_", "/m/07s04w4", "/m/07sq110", "/m/07rgt08"],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00001",
+    "name": "Baby laughter",
+    "description": "Laughter that is produced by a baby or infant.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/2ZqInEYQDOM?start=30&end=40", "youtu.be/BRtGk2YmdJ0?start=20&end=30", "youtu.be/T89y6lwH1Zg?start=30&end=40", "youtu.be/lwb96iGdhZs?start=210&end=220", "youtu.be/m2OBZqJ8qgI?start=90&end=100", "youtu.be/kykRU_67e94?start=20&end=30", "youtu.be/RLiHf1zIuXY?start=50&end=60", "youtu.be/3dh5bfCN4Hs?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r660_",
+    "name": "Giggle",
+    "description": "A foolish or nervous laugh.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=giggle",
+    "positive_examples": ["youtu.be/XviVGrbiUmE?start=240&end=250", "youtu.be/UW7ioxBkBvc?start=410&end=420", "youtu.be/RDAnjeHmW5o?start=30&end=40", "youtu.be/fvg6SM8hnwM?start=30&end=40", "youtu.be/Ts-Y1-FHnUo?start=30&end=40", "youtu.be/K4sqsDcUfGM?start=30&end=40", "youtu.be/8DTw8Udr4rA?start=80&end=90"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07s04w4",
+    "name": "Snicker",
+    "description": "A disrespectful laugh.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=snicker",
+    "positive_examples": ["youtu.be/0Xsny5M-hyE?start=140&end=150", "youtu.be/2sDFQiVB67I?start=80&end=90", "youtu.be/PgiVYe0HbNg?start=290&end=300", "youtu.be/ZMwa1h1Aa8I?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07sq110",
+    "name": "Belly laugh",
+    "description": "Very loud and abrupt laughter that encompasses much of the body.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=belly%20laugh",
+    "positive_examples": ["youtu.be/x2guhF8m53o?start=90&end=100", "youtu.be/og_nfmnT-xA?start=180&end=190", "youtu.be/NUNcvnesc2I?start=310&end=320", "youtu.be/sWXpzTZWNAI?start=30&end=40", "youtu.be/I-XNolOQ1JQ?start=330&end=340", "youtu.be/h_zv_bxqtAM?start=440&end=450"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rgt08",
+    "name": "Chuckle, chortle",
+    "description": "Laugh quietly or with restraint.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=chuckle",
+    "positive_examples": ["youtu.be/C9WWt3dS1I8?start=50&end=60", "youtu.be/-iq2dAKozlc?start=50&end=60", "youtu.be/B_6FPEmhH70?start=40&end=50", "youtu.be/_zkfG4uVqA4?start=110&end=120", "youtu.be/XeKzuoN62QM?start=40&end=50", "youtu.be/3Ri8_DHI4fQ?start=30&end=40", "youtu.be/0WOwZJ9G2N8?start=110&end=120"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0463cq4",
+    "name": "Crying, sobbing",
+    "description": "Sound associated with the shedding of tears in response to an emotional state, arising from slow but erratic inhalation, occasional instances of breath holding and muscular tremor.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Crying",
+    "positive_examples": ["youtu.be/RM6ekNDE2wc?start=15&end=25", "youtu.be/8Y2VGN-QsEs?start=10&end=20", "youtu.be/kEuZE_uu1rs?start=10&end=20", "youtu.be/5Fnc7yYDDvM?start=10&end=20", "youtu.be/rYyKWyIfVpU?start=10&end=20", "youtu.be/5KgGTZEsMsQ?start=10&end=20", "youtu.be/x9vxPUVx40Y?start=30&end=40", "youtu.be/fpWdNeGCKqc?start=40&end=50", "youtu.be/SfG3IkOprQc?start=60&end=70"],
+    "child_ids": ["/t/dd00002", "/m/07qz6j3"],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00002",
+    "name": "Baby cry, infant cry",
+    "description": "The sound of a young child crying or bawling.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/6T2jEKesKXY?start=30&end=40", "youtu.be/-mvGA8duqKM?start=29&end=39", "youtu.be/qc8n-R16jqI?start=30&end=40", "youtu.be/YFK6RwUBpHg?start=10&end=20", "youtu.be/VbtgXizyof4?start=30&end=40", "youtu.be/R6-KBbwNo1Q?start=30&end=40", "youtu.be/CmXA759VLZo?start=7&end=17", "youtu.be/qK4ag_CDBq4?start=30&end=40", "youtu.be/d-1zfgzgBgc?start=14&end=24"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qz6j3",
+    "name": "Whimper",
+    "description": "A plaintive, whining vocalization with some abrupt changes in loudness.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=whimper",
+    "positive_examples": ["youtu.be/Paa2p-PWR_A?start=110&end=120", "youtu.be/ym17PNCgwbQ?start=11&end=21", "youtu.be/ZucQqoFyibg?start=80&end=90", "youtu.be/DLKDQyjlmMc?start=30&end=40", "youtu.be/bEah4B4VQwg?start=30&end=40", "youtu.be/NLoDz8kI6hA?start=22&end=32", "youtu.be/YCvOvWQjUuw?start=50&end=60", "youtu.be/dFNG62WLBMk?start=70&end=80"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qw_06",
+    "name": "Wail, moan",
+    "description": "A weak or soft emotional vocalization, possibly indicating pain, sadness, or pleasure.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=wail",
+    "positive_examples": ["youtu.be/kLElQSpQEdI?start=110&end=120", "youtu.be/1SH36SQZxG4?start=510&end=520", "youtu.be/sArGQfiV2Ro?start=400&end=410", "youtu.be/7nZcwE5VxgM?start=470&end=480", "youtu.be/uiPxvdr6S8c?start=60&end=70", "youtu.be/VCOQOjLdIj0?start=510&end=520"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07plz5l",
+    "name": "Sigh",
+    "description": "An utterance made by exhaling audibly.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=sigh",
+    "positive_examples": ["youtu.be/XOphuM8ZUhM?start=560&end=570", "youtu.be/giY25pWyJxM?start=140&end=150"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/015lz1",
+    "name": "Singing",
+    "description": "Musical sounds produced with the human voice, including sustained tonality, rhythm, and a variety of other vocal techniques.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Singing",
+    "positive_examples": ["youtu.be/tYsnQUR-Ovg?start=210&end=220", "youtu.be/qo2MBnTtMrs?start=30&end=40", "youtu.be/XgPZjCl7Mog?start=110&end=120", "youtu.be/nJwUDaURmEU?start=160&end=170", "youtu.be/0ejZ-FIdeOE?start=80&end=90", "youtu.be/CzoJ3saJ4pw?start=70&end=80", "youtu.be/-62ed8TfM9E?start=100&end=110", "youtu.be/GpMPvnxkibA?start=190&end=200", "youtu.be/ZgxmMjcGBIk?start=30&end=40"],
+    "child_ids": ["/m/0l14jd", "/m/01swy6", "/m/02bk07", "/t/dd00003", "/t/dd00004", "/t/dd00005", "/t/dd00006", "/m/06bxc"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0l14jd",
+    "name": "Choir",
+    "description": "A musical ensemble of singers.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Choir",
+    "positive_examples": ["youtu.be/BwSECmEnch0?start=30&end=40", "youtu.be/7KBnHYkfr88?start=280&end=290", "youtu.be/T1fzAEVrunY?start=40&end=50", "youtu.be/jvEf_n4skHM?start=210&end=220", "youtu.be/Kb8aE3C4aSw?start=370&end=380", "youtu.be/dZiS2K2eqhs?start=30&end=40", "youtu.be/OdhXgzLFed0?start=130&end=140", "youtu.be/Gx7yso0V26E?start=300&end=310", "youtu.be/94zsWCi4C6g?start=190&end=200"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01swy6",
+    "name": "Yodeling",
+    "description": "A form of singing that involves repeated and rapid changes of pitch between the low-pitch chest register and the high-pitch head register or falsetto.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Yodeling",
+    "positive_examples": ["youtu.be/2eSbUlbLTKw?start=70&end=80", "youtu.be/DTzl8RG1oqA?start=70&end=80", "youtu.be/h3qfNR2JJdI?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02bk07",
+    "name": "Chant",
+    "description": "The rhythmic speaking or singing of words or sounds, often primarily on one or two main pitches called reciting tones.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Chant",
+    "positive_examples": [],
+    "child_ids": ["/m/01c194"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01c194",
+    "name": "Mantra",
+    "description": "A melodic sacred utterance believed to have spiritual powers.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Mantra",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00003",
+    "name": "Male singing",
+    "description": "Singing produced by an adult human male.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/3MyiiJVkmZc?start=30&end=40", "youtu.be/Cxe11hqO8xM?start=40&end=50", "youtu.be/zwU8MqFhtLo?start=180&end=190", "youtu.be/7QYUijb6wEg?start=30&end=40", "youtu.be/5mvUQdbVvIs?start=30&end=40", "youtu.be/1Ct9cLEumKQ?start=30&end=40", "youtu.be/-KN8aM8jlRo?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00004",
+    "name": "Female singing",
+    "description": "Singing produced by an adult human female.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/6Mp3JkuGIiI?start=30&end=40", "youtu.be/w9a0J7_9zN8?start=30&end=40", "youtu.be/-7xRJ-Osv1E?start=30&end=40", "youtu.be/G0wvmTxaLl4?start=30&end=40", "youtu.be/5j9weh6E9Yc?start=30&end=40", "youtu.be/-Y77HcFQZRo?start=30&end=40", "youtu.be/4MLHuuh6Al0?start=30&end=40", "youtu.be/6_YVfDV_GSA?start=6&end=16", "youtu.be/0ow_OtEBvRM?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00005",
+    "name": "Child singing",
+    "description": "Singing produced by a young human whose voice has not yet reached its adult state.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/0aqR4zaYEn4?start=30&end=40", "youtu.be/RmaUdIhQhsI?start=60&end=70", "youtu.be/5pIdH6p3kuo?start=30&end=40", "youtu.be/hnJhbClGpNI?start=90&end=100", "youtu.be/4d9EfAmGVFs?start=30&end=40", "youtu.be/77ojcYuZn7A?start=30&end=40", "youtu.be/B8wfW-vq_Pk?start=60&end=70", "youtu.be/-UFvq4-iS-Y?start=560&end=570", "youtu.be/265WZznzbko?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00006",
+    "name": "Synthetic singing",
+    "description": "Singing-like sounds produced by artificial means, such as an electronic synthesizer.  Does not include pre-recorded sounds that originate in a human voice.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/d6-bQMCz7j0?start=30&end=40", "youtu.be/-NC5li0b4eY?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06bxc",
+    "name": "Rapping",
+    "description": "The sound of \"spoken or chanted rhyming lyrics\", serving the role of a vocal line in music but with normal speech intonation instead of a melodic line.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Rapping",
+    "positive_examples": ["youtu.be/o0UkYQyz7Go?start=10&end=20", "youtu.be/TlAoG8vYhZc?start=110&end=120", "youtu.be/x7RGnBNjxUc?start=40&end=50", "youtu.be/oqkwwyS91MU?start=100&end=110", "youtu.be/vUgzSosGFl0?start=100&end=110", "youtu.be/n75IvFxTnPc?start=500&end=510", "youtu.be/rQZOndx4yQk?start=220&end=230", "youtu.be/UABPePYISsQ?start=30&end=40", "youtu.be/gAX5Kae75y0?start=30&end=40", "youtu.be/IDhovk37whw?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02fxyj",
+    "name": "Humming",
+    "description": "A wordless tone produced by forcing the sound to emerge from the nose, often with a melody.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Humming",
+    "positive_examples": ["youtu.be/rDybDMElvEQ?start=30&end=40", "youtu.be/fDk8UFZFPqQ?start=30&end=40", "youtu.be/KRb26VscbJ8?start=120&end=130"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07s2xch",
+    "name": "Groan",
+    "description": "An utterance expressing pain or disapproval. Specifically refers to humans.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=groan",
+    "positive_examples": ["youtu.be/UfJczyLcB40?start=170&end=180", "youtu.be/NrD9vrfyBLc?start=40&end=50", "youtu.be/AjQpqRcpG4E?start=30&end=40", "youtu.be/OHIIpJzP8_8?start=20&end=30", "youtu.be/Dp0FeEXOdgM?start=260&end=270", "youtu.be/vL1goz4n82k?start=140&end=150", "youtu.be/DkK4GuqTzHw?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r4k75",
+    "name": "Grunt",
+    "description": "A short low gruff noise, resembling the sound made by animals such as pigs. Specifically refers to humans.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=grunt",
+    "positive_examples": ["youtu.be/qt6ffKY0Vhs?start=160&end=170", "youtu.be/IUcXh9Zz0cQ?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01j423",
+    "name": "Yawn",
+    "description": "The sound of a reflex consisting of the simultaneous inhalation of air and the stretching of the eardrums, followed by an exhalation of breath, commonly associated with tiredness. Specifically refers to humans.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Yawn",
+    "positive_examples": ["youtu.be/nKdPjkVUbzc?start=90&end=100", "youtu.be/yMmc3uMa5xY?start=30&end=40", "youtu.be/C6Dh2wI6yss?start=70&end=80", "youtu.be/m5UQZ-zHd6I?start=13&end=23"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01w250",
+    "name": "Whistling",
+    "description": "High-pitched tone produced by blowing or sucking air through a small opening between the lips. Used to draw attention, as a personal tic, and to reproduce a melody.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Whistling",
+    "positive_examples": ["youtu.be/MJJv-SQVbQY?start=140&end=150", "youtu.be/snXiUKVgEVI?start=30&end=40", "youtu.be/7lqma04srnA?start=380&end=390", "youtu.be/78F0DHyl8BU?start=30&end=40", "youtu.be/_UahfxFAx0g?start=10&end=20", "youtu.be/EJr6MusXp-o?start=26&end=36", "youtu.be/zhTVzULeZQU?start=12&end=22"],
+    "child_ids": ["/m/079vc8"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/079vc8",
+    "name": "Wolf-whistling",
+    "description": "A two-toned whistle commonly made to show high interest or approval of something or someone (typically sexual).",
+    "citation_uri": "http://en.wikipedia.org/wiki/Wolf-whistling",
+    "positive_examples": ["youtu.be/wE527Sqn0E8?start=12&end=22", "youtu.be/YykyGidfpfw?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/09hlz4",
+    "name": "Respiratory sounds",
+    "description": "Sounds generated by the movement of air through the respiratory system (nose, mouth, trachea, and lungs).",
+    "citation_uri": "http://en.wikipedia.org/wiki/Respiratory_sounds",
+    "positive_examples": [],
+    "child_ids": ["/m/0lyf6", "/m/01b_21", "/m/01hsr_", "/m/07ppn3j"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/0lyf6",
+    "name": "Breathing",
+    "description": "Air being moved in and out of the lungs in order to sustain life.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Breathing",
+    "positive_examples": ["youtu.be/hd2yDnpnkUU?start=30&end=40", "youtu.be/1PFsaGB6rIw?start=220&end=230", "youtu.be/ncyIS2o9m74?start=30&end=40", "youtu.be/fBLIOyO67Ro?start=90&end=100", "youtu.be/YhSBpiBlIec?start=10&end=20", "youtu.be/e1urSpgRg7M?start=40&end=50", "youtu.be/XUPDODziWEw?start=80&end=90"],
+    "child_ids": ["/m/07mzm6", "/m/01d3sd", "/m/07s0dtb", "/m/07pyy8b", "/m/07q0yl5"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07mzm6",
+    "name": "Wheeze",
+    "description": "A continuous, coarse, whistling sound produced by obstruction of the respiratory airways during breathing.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Wheeze",
+    "positive_examples": ["youtu.be/NPVIL-WOOM4?start=30&end=40", "youtu.be/IvfCYhQXLd0?start=3&end=13", "youtu.be/6J9XeiKqzw0?start=18&end=28", "youtu.be/SVz7X1gqlcw?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01d3sd",
+    "name": "Snoring",
+    "description": "The sound resulting from obstructed respiratory airways during breathing while sleeping.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Snoring",
+    "positive_examples": ["youtu.be/mn824q6UoMg?start=140&end=150", "youtu.be/TiJ-Szo9yHQ?start=20&end=30", "youtu.be/oFiA12sNPyo?start=20&end=30", "youtu.be/c5DPrfjcnsw?start=100&end=110", "youtu.be/9LoDdANZIwg?start=50&end=60", "youtu.be/qWLuleckhOc?start=110&end=120", "youtu.be/3553HVNfiP8?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07s0dtb",
+    "name": "Gasp",
+    "description": "A short labored intake of breath with the mouth open. Often indicates shock or surprise.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=gasp",
+    "positive_examples": ["youtu.be/4bU0HWzCXMc?start=170&end=180", "youtu.be/soVRoIbewMM?start=50&end=60", "youtu.be/EvkxkkJp-v8?start=190&end=200"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pyy8b",
+    "name": "Pant",
+    "description": "Fast and noisy breathing, often associated with physical exertion.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=pant",
+    "positive_examples": ["youtu.be/LCB8rW5cvWk?start=30&end=40", "youtu.be/rgOSgFy0S3Q?start=350&end=360", "youtu.be/gOB0nM0PRTc?start=30&end=40", "youtu.be/e90rd071P-E?start=20&end=30", "youtu.be/jRcrVp2LZTo?start=50&end=60", "youtu.be/Kn-WVGzPVZg?start=20&end=30", "youtu.be/JWP10M-t0jo?start=110&end=120", "youtu.be/yOO9UmPZfns?start=460&end=470"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07q0yl5",
+    "name": "Snort",
+    "description": "The sound of a single, hard exhalation through the nose.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=snort",
+    "positive_examples": ["youtu.be/2PXcJCAVf38?start=50&end=60", "youtu.be/AJIRlmjloBo?start=300&end=310", "youtu.be/3xvs8X-u8NA?start=140&end=150", "youtu.be/fSilzq77oTE?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01b_21",
+    "name": "Cough",
+    "description": "A sudden and often repetitively occurring reflex which consists of an inhalation, a forced exhalation against a closed glottis, and a violent release of air following opening of the glottis.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cough",
+    "positive_examples": ["youtu.be/c-yI09r8D5w?start=70&end=80", "youtu.be/NIzPRH3ko6s?start=50&end=60", "youtu.be/cLBKVLHFABc?start=40&end=50", "youtu.be/WkaNCu_1l68?start=10&end=20", "youtu.be/vA_AIILl76w?start=20&end=30"],
+    "child_ids": ["/m/0dl9sf8"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0dl9sf8",
+    "name": "Throat clearing",
+    "description": "Forced exhalation through a partially-closed glottis to disrupt built-up mucus, or used as a social signal to draw attention to one's presence.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/xAj1xof1FeU?start=510&end=520", "youtu.be/D40HPmkVjEU?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01hsr_",
+    "name": "Sneeze",
+    "description": "A convulsive expulsion of air from the lungs through the nose and mouth, usually caused by foreign particles irritating the nasal mucous.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sneeze",
+    "positive_examples": ["youtu.be/8714J5_siEY?start=40&end=50", "youtu.be/SG3MrCBKskE?start=70&end=80", "youtu.be/gyF_tG0M9cM?start=10&end=20", "youtu.be/qDXFW2kemrE?start=250&end=260", "youtu.be/StJLcW5FKoI?start=20&end=30", "youtu.be/HMmbLN0NoYo?start=130&end=140"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07ppn3j",
+    "name": "Sniff",
+    "description": "Inhale audibly through the nose.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=sniff",
+    "positive_examples": ["youtu.be/BDrbBzzJ3hg?start=210&end=220", "youtu.be/MH33LSP9CiI?start=120&end=130", "youtu.be/-xyTvA1F16M?start=590&end=600"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0bpl036",
+    "name": "Human locomotion",
+    "description": "Sounds resulting from human body actions involved in changing location.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/06h7j", "/m/07qv_x_", "/m/07pbtc8"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/06h7j",
+    "name": "Run",
+    "description": "Move fast by using one's feet.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Running",
+    "positive_examples": ["youtu.be/F4Rqp8W59rY?start=30&end=40", "youtu.be/Q_29jnpYobY?start=30&end=40", "youtu.be/5uXUyEf8bzY?start=30&end=40", "youtu.be/9TDFjw6eF5M?start=30&end=40", "youtu.be/3cjFmZe9muo?start=300&end=310", "youtu.be/_rABcqr2InE?start=250&end=260"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qv_x_",
+    "name": "Shuffle",
+    "description": "Walk while dragging the feet, often indicating impaired mobility.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=shuffle",
+    "positive_examples": ["youtu.be/SJRNlFrlL6I?start=1&end=11", "youtu.be/u-xy9MsPuAI?start=7&end=17"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pbtc8",
+    "name": "Walk, footsteps",
+    "description": "The sound of feet or shoes contacting the ground in conventional human locomotion.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=walk",
+    "positive_examples": ["youtu.be/Dl_-9HuKqD0?start=220&end=230", "youtu.be/ulYCw2ZEiz4?start=50&end=60", "youtu.be/0qes0wPqdEs?start=30&end=40", "youtu.be/XYm5hJfJaFo?start=80&end=90", "youtu.be/DBRvVR2KHeg?start=230&end=240", "youtu.be/V851WPfpbwA?start=230&end=240", "youtu.be/Ix5uPjC1gHI?start=70&end=80", "youtu.be/2Z4THg6VA1A?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0160x5",
+    "name": "Digestive",
+    "description": "Sounds associated with the human function of eating and processing nutrition (food).",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/03cczk", "/m/07pdhp0", "/m/0939n_", "/m/01g90h", "/m/03q5_w", "/m/02p3nc", "/m/02_nn"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/03cczk",
+    "name": "Chewing, mastication",
+    "description": "Food being crushed and ground by teeth.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Mastication",
+    "positive_examples": ["youtu.be/EBnrA85wsc4?start=530&end=540", "youtu.be/EkCIh67xI_w?start=30&end=40", "youtu.be/fCQMflXjGU8?start=460&end=470", "youtu.be/A7MnWIjUVw8?start=40&end=50", "youtu.be/q2m5ChTEe4k?start=450&end=460", "youtu.be/mE092i7zPqY?start=19&end=29", "youtu.be/G3it26Z8E8U?start=30&end=40", "youtu.be/5xAEW3g6en8?start=100&end=110", "youtu.be/9lKmiUIJfGc?start=280&end=290"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pdhp0",
+    "name": "Biting",
+    "description": "Gripping or chewing off with the teeth and jaws.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=biting",
+    "positive_examples": ["youtu.be/3CkwNL_UGoA?start=30&end=40", "youtu.be/WoA9_cYAlfc?start=240&end=250", "youtu.be/XMGG2w26ea4?start=30&end=40", "youtu.be/PRsBCvps7D0?start=30&end=40", "youtu.be/BH4UwESvYw8?start=160&end=170", "youtu.be/X8ulg-9etoU?start=80&end=90"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0939n_",
+    "name": "Gargling",
+    "description": "Air from the lungs bubbling through a liquid in the mouth.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Gargling",
+    "positive_examples": ["youtu.be/Dz8filbrC98?start=60&end=70", "youtu.be/e8saB9V1UXo?start=70&end=80", "youtu.be/SVSjNao4ZFQ?start=80&end=90", "youtu.be/Rk6O2IWjwFg?start=520&end=530", "youtu.be/ACNcxeQ-Rns?start=20&end=30", "youtu.be/bQR7moK_WZg?start=30&end=40", "youtu.be/QS--7Slaacc?start=30&end=40", "youtu.be/AbNB97ANUDA?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01g90h",
+    "name": "Stomach rumble",
+    "description": "A rumbling, growling or gurgling noise produced by movement of the contents of the gastro-intestinal tract.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Stomach_rumble",
+    "positive_examples": ["youtu.be/Gq9nl91baGg?start=110&end=120", "youtu.be/kCXc7_Xie2s?start=12&end=22", "youtu.be/Fk8-06ipZYo?start=400&end=410", "youtu.be/2_Z3pMnrWKY?start=400&end=410"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03q5_w",
+    "name": "Burping, eructation",
+    "description": "The release of gas from the digestive tract through the mouth.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Burping",
+    "positive_examples": ["youtu.be/IsnR6Ck3j44?start=160&end=170", "youtu.be/8xMdlr7YTr4?start=70&end=80", "youtu.be/uhOh3x9I6bw?start=20&end=30", "youtu.be/cQAiS0dk8Zc?start=130&end=140", "youtu.be/1WI9921OeRc?start=570&end=580", "youtu.be/N_ggss-wQmQ?start=40&end=50", "youtu.be/Xo6WBR_cFXQ?start=80&end=90", "youtu.be/X9oZGgZij0c?start=220&end=230", "youtu.be/IP-zbN5rVNs?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02p3nc",
+    "name": "Hiccup",
+    "description": "A strong, involuntary contraction of the diaphragm that may repeat several times per minute.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Hiccup",
+    "positive_examples": ["youtu.be/m8yH5TLD1oQ?start=190&end=200", "youtu.be/g1mJnZVGQkk?start=30&end=40", "youtu.be/JQ2XH_Ci_tk?start=80&end=90", "youtu.be/7gdSJ30FfNU?start=460&end=470", "youtu.be/VMdN2OuP6fk?start=90&end=100"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02_nn",
+    "name": "Fart",
+    "description": "The release of gasses produced by digestion through the anus; flatulence.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Fart",
+    "positive_examples": ["youtu.be/xOkFu3ahJAs?start=50&end=60", "youtu.be/O9kJ6tBGGR0?start=70&end=80", "youtu.be/DKnViWndkPc?start=10&end=20", "youtu.be/qtLaibhO5hI?start=30&end=40", "youtu.be/ZMi9XHLZzSk?start=20&end=30", "youtu.be/Le9QaCTQFQ4?start=150&end=160"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0k65p",
+    "name": "Hands",
+    "description": "Sounds originating primarily from the hands and fingers of humans.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/tHASgPEwR_4?start=60&end=70", "youtu.be/s9ODY2HdI7g?start=30&end=40", "youtu.be/qPsooNWBc90?start=40&end=50", "youtu.be/S-n7Rkg32tE?start=230&end=240", "youtu.be/nGmhfmCVnnc?start=30&end=40", "youtu.be/O9z0AAuWG20?start=420&end=430", "youtu.be/PU-4TfhBjrA?start=60&end=70", "youtu.be/cJAm1VXhvGA?start=150&end=160", "youtu.be/KSOxq1eovtw?start=30&end=40"],
+    "child_ids": ["/m/025_jnm", "/m/0l15bq"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/025_jnm",
+    "name": "Finger snapping",
+    "description": "A snapping or clicking sound usually caused by building tension between the thumb and another finger and then moving the other finger forcefully downward to hits the palm at high speed.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Finger_snapping",
+    "positive_examples": ["youtu.be/Q6hIvsdfCF8?start=10&end=20", "youtu.be/p42W37beu88?start=90&end=100", "youtu.be/vxrM-HU9ITQ?start=30&end=40", "youtu.be/UPJl7MtJwhw?start=30&end=40", "youtu.be/p6VIZQAV5PQ?start=30&end=40", "youtu.be/lmSmwPsWvII?start=83&end=93", "youtu.be/JwWoO-dafDc?start=190&end=200", "youtu.be/_e7dRfvWLPo?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0l15bq",
+    "name": "Clapping",
+    "description": "A percussive sound made by a human striking together the palms of their two hands, often quickly and repeatedly to express appreciation or approval. This category is to be used for distinct claps by a single person; for a group of people clapping together, use Applause.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Clapping",
+    "positive_examples": ["youtu.be/ATHjFAM3ehk?start=80&end=90", "youtu.be/TCI_qydc554?start=20&end=30", "youtu.be/8byxt0IjVcQ?start=30&end=40", "youtu.be/0aSF6X4-Ksg?start=50&end=60", "youtu.be/-FRGpQEpEWM?start=30&end=40", "youtu.be/ikdaGO5jUYU?start=80&end=90", "youtu.be/3qEb6Y-D7Mw?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01jg02",
+    "name": "Heart sounds, heartbeat",
+    "description": "Noises generated by the beating heart and the resultant flow of blood through it.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Heart_sounds",
+    "positive_examples": ["youtu.be/40YB3ROwAbE?start=30&end=40", "youtu.be/g9IEEN6Zm8E?start=100&end=110", "youtu.be/T9I8C9l3fR0?start=30&end=40", "youtu.be/nFjBft9nEhs?start=30&end=40", "youtu.be/PkgYuDzOvnc?start=30&end=40", "youtu.be/sbcqHphoMDA?start=100&end=110"],
+    "child_ids": ["/m/01jg1z"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01jg1z",
+    "name": "Heart murmur",
+    "description": "Heart sounds produced by abnormal blood flow across one of the heart valves, typically detected by a stethoscope.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Heart_murmur",
+    "positive_examples": ["youtu.be/tpvMXSfxGOg?start=30&end=40", "youtu.be/m_QTr-0Y_Ek?start=110&end=120"],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/04xp5v",
+    "name": "Otoacoustic emission",
+    "description": "A sound generated within the inner ear, generally understood to result from positive feedback in the highly-sensitive ear mechanism.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Otoacoustic_emission",
+    "positive_examples": [],
+    "child_ids": ["/m/0pv6y"],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0pv6y",
+    "name": "Tinnitus, ringing in the ears",
+    "description": "A sound perceived when no external sound is present, often described as ringing, usually related to short-term trauma or longer-lasting damage to the ear.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Tinnitus",
+    "positive_examples": ["youtu.be/4XBH8x2mcZk?start=60&end=70", "youtu.be/8WFmDgu2Z9Y?start=10&end=20", "youtu.be/ZEHdCaVwtvs?start=270&end=280", "youtu.be/eCWPT9pS7so?start=40&end=50", "youtu.be/OE5fIoveLoM?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/t/dd00012",
+    "name": "Human group actions",
+    "description": "Sounds produced by groups of humans rather than individuals.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/0l15bq", "/m/053hz1", "/m/028ght", "/m/07rkbfh", "/m/03qtwd", "/m/07qfr4h", "/m/04v5dt", "/t/dd00013", "/t/dd00135"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/053hz1",
+    "name": "Cheering",
+    "description": "Encouraging, stimulating, or exciting vocalizations indicating approval or welcoming persons, announcements, etc.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cheering",
+    "positive_examples": ["youtu.be/YtItqbSzKBs?start=190&end=200", "youtu.be/7yntRBheP3M?start=30&end=40", "youtu.be/rJ20qPKtLnU?start=70&end=80", "youtu.be/HxPdX8caIaM?start=10&end=20", "youtu.be/Sdl9uYLySyU?start=30&end=40", "youtu.be/OqpuMxjAYTs?start=180&end=190", "youtu.be/oxBsRnUc_6U?start=250&end=260", "youtu.be/4ul8uXkumZM?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/028ght",
+    "name": "Applause",
+    "description": "Group expression of approval by the collective act of clapping by a group.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Applause",
+    "positive_examples": ["youtu.be/lAD74Ey6bL4?start=510&end=520", "youtu.be/7WSH77zPigA?start=30&end=40", "youtu.be/kqzL3xznfiU?start=350&end=360", "youtu.be/0-ygGIzPk6Y?start=30&end=40", "youtu.be/Uzj6a_Btyqs?start=450&end=460", "youtu.be/e1gdVg7DcV4?start=360&end=370", "youtu.be/Rb2L0PmwcvA?start=420&end=430", "youtu.be/ep3rfNAyXGs?start=40&end=50", "youtu.be/rpoTKm-QB7Y?start=15&end=25"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rkbfh",
+    "name": "Chatter",
+    "description": "The combined sound of casual speech by many people in individual simultaneous conversations.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=chatter",
+    "positive_examples": ["youtu.be/ViYMLK4dujU?start=200&end=210", "youtu.be/XXsfmD0Bss0?start=400&end=410", "youtu.be/NyEcj25jlSY?start=40&end=50", "youtu.be/Fvbyp4w6EaM?start=220&end=230", "youtu.be/3YCmyruGOK8?start=140&end=150", "youtu.be/VmPeBqOwI-Y?start=140&end=150"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03qtwd",
+    "name": "Crowd",
+    "description": "The sound of a large group of people gathered together.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Crowd",
+    "positive_examples": ["youtu.be/kUKWkSKQEJY?start=310&end=320", "youtu.be/V5PKN1kIPh8?start=120&end=130", "youtu.be/y_betJ7lbvs?start=190&end=200", "youtu.be/xGPtos-dfDU?start=360&end=370", "youtu.be/qlsptFT16nA?start=350&end=360", "youtu.be/yNkD_yqgUk0?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qfr4h",
+    "name": "Hubbub, speech noise, speech babble",
+    "description": "Loud, disordered, unintelligible speech noise from many sources.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=hubbub",
+    "positive_examples": ["youtu.be/7kw_my9mSSY?start=30&end=40", "youtu.be/9heeSXrNtXY?start=60&end=70", "youtu.be/_frFEY2PG-8?start=140&end=150", "youtu.be/WIKHKccnhCg?start=190&end=200", "youtu.be/DTmnaeDISTY?start=20&end=30", "youtu.be/4Csr25pn41Q?start=30&end=40", "youtu.be/c8CsTpDQlaE?start=280&end=290", "youtu.be/ca5yYSLOcpY?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04v5dt",
+    "name": "Booing",
+    "description": "Vocal display of displeasure for someone or something, generally an entertainer, by loudly yelling \"boo!\" or making other noises of disparagement.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Booing",
+    "positive_examples": ["youtu.be/-Cz0muXWdeU?start=310&end=320", "youtu.be/X6xMdMyx4Q8?start=190&end=200", "youtu.be/07ckQxmU9KM?start=23&end=33"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00013",
+    "name": "Children playing",
+    "description": "The sound of children at play, including any of vocalization or the sounds of their activities.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/oxj5zL56UNQ?start=400&end=410", "youtu.be/MkLjgMq-XWo?start=20&end=30", "youtu.be/ZUu13n3vyT8?start=290&end=300", "youtu.be/H867X9MA2x4?start=130&end=140", "youtu.be/SjkBir6CfV8?start=20&end=30", "youtu.be/sQDMqzfpd-Q?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0jbk",
+    "name": "Animal",
+    "description": "All sound produced by the bodies and actions of nonhuman animals.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/kECE3qqOknU?start=240&end=250", "youtu.be/gDGP5i3GeGM?start=30&end=40", "youtu.be/Fup9UWyLXjA?start=190&end=200", "youtu.be/YCJs-dwWEks?start=30&end=40", "youtu.be/DNfdqCO9P18?start=30&end=40", "youtu.be/-oRgzBsFneA?start=22&end=32", "youtu.be/ao4g6YKxso8?start=20&end=30", "youtu.be/7j1G8xvOlYw?start=15&end=25", "youtu.be/7nC42YgzxrA?start=120&end=130"],
+    "child_ids": ["/m/068hy", "/m/0ch8v", "/m/01280g"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/068hy",
+    "name": "Domestic animals, pets",
+    "description": "Sounds of animals kept in close proximity to humans for company, protection, and entertainment.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Pet",
+    "positive_examples": ["youtu.be/3SQwwK4JU2I?start=50&end=60", "youtu.be/88AWuXFZkTU?start=17&end=27", "youtu.be/Byo0kKnIASM?start=10&end=20", "youtu.be/6Flj55tSIQE?start=10&end=20", "youtu.be/3Cu8KEB9C74?start=70&end=80", "youtu.be/bTLrBsAy-cE?start=30&end=40", "youtu.be/xwJUplydiuw?start=70&end=80"],
+    "child_ids": ["/m/0bt9lr", "/m/01yrx"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0bt9lr",
+    "name": "Dog",
+    "description": "Any sounds coming from the familiar domesticated canid which has been selectively bred over millennia for companionship, protection, as well as for superior sensory capabilities, and other useful behaviors.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Dog",
+    "positive_examples": ["youtu.be/2M9XExD5qZc?start=30&end=40", "youtu.be/x5Z7h8G-tYs?start=30&end=40", "youtu.be/8UQNzfJX-O8?start=80&end=90", "youtu.be/7h0FRbJSy7I?start=30&end=40", "youtu.be/iyg_5TVi7_Q?start=450&end=460", "youtu.be/1spRiYwd09c?start=70&end=80", "youtu.be/TsePRLNK3Ho?start=40&end=50", "youtu.be/7ajTgyQVczE?start=50&end=60", "youtu.be/azavLi-x9Cw?start=310&end=320"],
+    "child_ids": ["/m/05tny_", "/m/07r_k2n", "/m/07qf0zm", "/m/07rc7d9", "/m/0ghcn6", "/t/dd00136", "/m/07srf8z"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05tny_",
+    "name": "Bark",
+    "description": "Principal communication sound produced by dogs. Often transliterated as woof, especially for large dogs.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bark_(sound)",
+    "positive_examples": ["youtu.be/PGfUJCl4M2E?start=80&end=90", "youtu.be/o-a6xZnOvP4?start=40&end=50", "youtu.be/G8BSfIQcDI0?start=110&end=120", "youtu.be/NKfyi7q0JNU?start=20&end=30", "youtu.be/IYFq35F80hY?start=20&end=30", "youtu.be/YlgYRxOe7vA?start=170&end=180", "youtu.be/RVKEE-0WdLM?start=30&end=40", "youtu.be/CecFyrZB-FM?start=60&end=70"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r_k2n",
+    "name": "Yip",
+    "description": "A sharp high-pitched bark or cry, typically from a miniature dog.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=yip",
+    "positive_examples": ["youtu.be/5ROJv9qD0e8?start=30&end=40", "youtu.be/9_5DNgJO-Gs?start=15&end=25", "youtu.be/-5IoPSM59xM?start=9&end=19"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qf0zm",
+    "name": "Howl",
+    "description": "The long plaintive cry of a dog, wolf, or other canidae.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=howl",
+    "positive_examples": ["youtu.be/i0j8eJ97eBg?start=20&end=30", "youtu.be/ZhgQ8G03Zjw?start=10&end=20", "youtu.be/UT43tXUgAqk?start=50&end=60", "youtu.be/TmcPW-sbKUw?start=30&end=40", "youtu.be/PWiI1jGK8kQ?start=60&end=70", "youtu.be/5ztulE7OhaA?start=50&end=60", "youtu.be/-hDuDDv0lbQ?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rc7d9",
+    "name": "Bow-wow",
+    "description": "Dog communication sound that is more tonal and less abrupt than a classic bark.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=bow-wow",
+    "positive_examples": ["youtu.be/c8T5BXR0Oxo?start=30&end=40", "youtu.be/2D-Zq-hS5vY?start=30&end=40", "youtu.be/FtqlvNd8meU?start=230&end=240", "youtu.be/N-5sU5MnwtE?start=90&end=100"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0ghcn6",
+    "name": "Growling",
+    "description": "A low, guttural vocalization produced by animals as a warning, a sign of aggression, or to express anger.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Growling",
+    "positive_examples": ["youtu.be/awGgmjI0oaI?start=19&end=29", "youtu.be/a9R4pBS_nnM?start=10&end=20", "youtu.be/goy6XN59IFY?start=490&end=500", "youtu.be/H-BEdsuYFFw?start=40&end=50", "youtu.be/YfxejAWkNcY?start=20&end=30", "youtu.be/jL6K_C9hRFs?start=80&end=90", "youtu.be/kPkat62eHrc?start=10&end=20", "youtu.be/xdl3MP9X1DM?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00136",
+    "name": "Whimper (dog)",
+    "description": "Muted dog vocalization indicating submission, fear, or pain.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/2VwfCvSyQ2U?start=30&end=40", "youtu.be/pstdKyySdbQ?start=30&end=40", "youtu.be/-PveIRMYamI?start=15&end=25", "youtu.be/-BL3E3sLc78?start=30&end=40", "youtu.be/63VwvFLgIak?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07srf8z",
+    "name": "Bay",
+    "description": "The sound made by a hound on the scent.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=bay",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/01yrx",
+    "name": "Cat",
+    "description": "Sounds associated with the familiar, furry, domestic carnivorous mammal.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cat",
+    "positive_examples": ["youtu.be/5abeJmVq3hU?start=100&end=110", "youtu.be/NdJ910zuXrk?start=40&end=50", "youtu.be/_DkdN717Pj8?start=10&end=20", "youtu.be/ZJcDVzElozo?start=120&end=130", "youtu.be/mGcIhQw0d5U?start=40&end=50", "youtu.be/hsAnIv1pOx0?start=30&end=40", "youtu.be/nAKQA8W1Vqs?start=27&end=37", "youtu.be/fgdBZgILLzs?start=30&end=40"],
+    "child_ids": ["/m/02yds9", "/m/07qrkrw", "/m/07rjwbb", "/m/0f25s6", "/m/07r81j2", "/m/0ghcn6"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02yds9",
+    "name": "Purr",
+    "description": "A tonal fluttering sound made by cats to indicate contentment or relaxed pleasure.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Purr",
+    "positive_examples": ["youtu.be/suUMt34qu5c?start=30&end=40", "youtu.be/U80msVD7UwY?start=370&end=380", "youtu.be/RJcWUsq9S7k?start=90&end=100", "youtu.be/IEMsniLsvrg?start=20&end=30", "youtu.be/FFUPnvY3dXA?start=270&end=280", "youtu.be/OEHhFtvE50A?start=30&end=40", "youtu.be/I_tDt5W2x2Y?start=10&end=20", "youtu.be/EHziu6xjukk?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qrkrw",
+    "name": "Meow",
+    "description": "The classic tonal communication sound made by cats.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=meow",
+    "positive_examples": ["youtu.be/b3dYlDbU_78?start=30&end=40", "youtu.be/wDbhmulc2Lk?start=30&end=40", "youtu.be/8y_kK7fV1QU?start=10&end=20", "youtu.be/_zgFmCdbFSk?start=16&end=26", "youtu.be/95EUjkKsr1c?start=2&end=12", "youtu.be/AOj_Kpbg9xU?start=30&end=40", "youtu.be/T-7ed-4B_oc?start=30&end=40", "youtu.be/-w3qkf-V-PY?start=30&end=40", "youtu.be/3n--reua_a0?start=27&end=37"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rjwbb",
+    "name": "Hiss",
+    "description": "A fricative sound, such as from a cat giving warning, or an audience indicating disapproval.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=hiss",
+    "positive_examples": ["youtu.be/7fuyNj3y8z8?start=30&end=40", "youtu.be/sNFrUosKoq4?start=140&end=150", "youtu.be/3GkJeelJCB0?start=30&end=40", "youtu.be/uN4LHeFWBHY?start=30&end=40", "youtu.be/l4fED3GwuwY?start=30&end=40", "youtu.be/-dN7rnGYtNQ?start=30&end=40", "youtu.be/5wScdWqlS0c?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0f25s6",
+    "name": "Cat communication",
+    "description": "Other sound deliberately made by cats to communicate with other animals.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cat_communication",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/07r81j2",
+    "name": "Caterwaul",
+    "description": "The yowling sound made by a cat in heat.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=caterwaul",
+    "positive_examples": ["youtu.be/02dEE23cyGU?start=2&end=12", "youtu.be/u3huL-igOL0?start=160&end=170", "youtu.be/1tC7bTilFWk?start=30&end=40", "youtu.be/Vvyroqu2QN4?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0ch8v",
+    "name": "Livestock, farm animals, working animals",
+    "description": "Sound made by animals associated with farms and agriculture.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Livestock",
+    "positive_examples": ["youtu.be/T5xYIPkOfXc?start=60&end=70", "youtu.be/lug9rO_5UGU?start=50&end=60", "youtu.be/rm9Bwksyl_A?start=30&end=40", "youtu.be/o58iPCU6vOs?start=60&end=70", "youtu.be/rs4Bpk_OXfc?start=30&end=40", "youtu.be/zUinGkfkq7Y?start=20&end=30", "youtu.be/RqYjn1aDHLY?start=50&end=60"],
+    "child_ids": ["/m/03k3r", "/m/0ffhf", "/m/01xq0k1", "/m/068zj", "/m/03fwl", "/m/07bgp", "/m/025rv6n"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03k3r",
+    "name": "Horse",
+    "description": "Sounds associated with the familiar domesticated large, fast, and strong ungulate mammal.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Horse",
+    "positive_examples": ["youtu.be/yajlx6BNbPI?start=160&end=170", "youtu.be/Da48zrkaU3E?start=340&end=350", "youtu.be/14ZSZeRJiG4?start=300&end=310", "youtu.be/dzSssD-ITNo?start=30&end=40", "youtu.be/5cCq9hL1Jxg?start=2&end=12", "youtu.be/3cc2GDUvdHo?start=14&end=24"],
+    "child_ids": ["/m/07rv9rh", "/m/07q5rw0", "/t/dd00139", "/t/dd00140"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rv9rh",
+    "name": "Clip-clop",
+    "description": "The sound of a horse's hoofs hitting on a hard surface.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=clip-clop",
+    "positive_examples": ["youtu.be/06JrdfCNSso?start=3&end=13", "youtu.be/HRFAq0D6ROY?start=30&end=40", "youtu.be/-qbPc4nh5ac?start=13&end=23", "youtu.be/DuWkYCyOrN0?start=30&end=40", "youtu.be/Ej-VJMQVxuc?start=30&end=40", "youtu.be/0O5xF0PdtBg?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07q5rw0",
+    "name": "Neigh, whinny",
+    "description": "The characteristic communication sound made by a horse.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=neigh",
+    "positive_examples": ["youtu.be/8I88xIoT3qM?start=110&end=120", "youtu.be/7wfM1zUa_zo?start=30&end=40", "youtu.be/CRlC9US2Vgs?start=30&end=40", "youtu.be/6L_HclNjdWg?start=30&end=40", "youtu.be/DcNVcRK4F4g?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00139",
+    "name": "Snort (horse)",
+    "description": "The sound of a rapid exhale through a horse's nose.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=snort",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00140",
+    "name": "Nicker",
+    "description": "A soft neighing sound made by a horse.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=nicker",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0ffhf",
+    "name": "Donkey, ass",
+    "description": "Sounds associated with the domesticated working animal that is a smaller member of the horse family.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sheep",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01xq0k1",
+    "name": "Cattle, bovinae",
+    "description": "Sounds associated with the most common type of large domesticated ungulates.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cattle",
+    "positive_examples": ["youtu.be/6Sny_-shK20?start=100&end=110", "youtu.be/pX9hIaLLBHU?start=20&end=30", "youtu.be/fSQaU5F914s?start=60&end=70", "youtu.be/ZyP7RBGTrgk?start=420&end=430", "youtu.be/Yu7FiBS9Qjg?start=50&end=60", "youtu.be/oLm3xrAkH0c?start=70&end=80", "youtu.be/rae7_kchsho?start=4&end=14", "youtu.be/LC4vDpnkDtM?start=90&end=100"],
+    "child_ids": ["/m/07rpkh9", "/m/0239kh", "/m/01hhp3"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rpkh9",
+    "name": "Moo",
+    "description": "The classic communication sound made by a cow or bull.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=moo",
+    "positive_examples": ["youtu.be/nWhh5mJP-x0?start=13&end=23", "youtu.be/ev_fiaC03oQ?start=29&end=39", "youtu.be/eXLPS2FHCaQ?start=25&end=35", "youtu.be/8lIh0qRN7PE?start=220&end=230", "youtu.be/GSAd8G_JsFs?start=8&end=18", "youtu.be/wDxqpIVXXEU?start=19&end=29", "youtu.be/s_SLQwB8PlI?start=7&end=17", "youtu.be/eI7IkWkGEpY?start=16&end=26"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0239kh",
+    "name": "Cowbell",
+    "description": "A simple metal bell historically tied around the necks of cattle to keep track of their whereabouts.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cowbell_(instrument)",
+    "positive_examples": ["youtu.be/uXyeDpCw83c?start=50&end=60", "youtu.be/NSrLZ4Dc_FI?start=60&end=70", "youtu.be/bFGQQRHryuk?start=70&end=80", "youtu.be/KWRI6Lj8GEk?start=11&end=21", "youtu.be/pdOskdFwRPg?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01hhp3",
+    "name": "Yak",
+    "description": "The sound of the long-haired bovid found throughout the Himalaya region of southern Central Asia.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Yak",
+    "positive_examples": ["youtu.be/BV3sltuQaJE?start=20&end=30", "youtu.be/ZcULeCFl-1o?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/068zj",
+    "name": "Pig",
+    "description": "Sounds associated with the highly intelligent, very common, domesticated relative of the boar.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Pig",
+    "positive_examples": ["youtu.be/nV9B3G4L51c?start=80&end=90", "youtu.be/DX2WJrS04rU?start=270&end=280", "youtu.be/4C1WjCNy3i8?start=520&end=530", "youtu.be/rLhXPcqUK8A?start=40&end=50", "youtu.be/-pDS3yN4B1s?start=50&end=60", "youtu.be/FK9IFAJyD7w?start=100&end=110", "youtu.be/HuKFVWSbXK8?start=120&end=130"],
+    "child_ids": ["/t/dd00018"],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00018",
+    "name": "Oink",
+    "description": "Common vocalization sound associated with pigs.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/5Dl9LrilWZ4?start=30&end=40", "youtu.be/NG204aLoF1A?start=30&end=40", "youtu.be/p48WaCOxqfk?start=30&end=40", "youtu.be/l-N4TZ2y-5c?start=10&end=20", "youtu.be/r-uANPTedEA?start=30&end=40", "youtu.be/_YbVlWmj-jA?start=30&end=40", "youtu.be/sVnc5_CN3K0?start=4&end=14", "youtu.be/SMQfBU8YhUY?start=30&end=40", "youtu.be/jqAfRUCPONk?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03fwl",
+    "name": "Goat",
+    "description": "Sounds of the medium-sized domesticated bovidae.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Goat",
+    "positive_examples": ["youtu.be/pa8vtRejCe0?start=250&end=260", "youtu.be/s1-fRJvMRjU?start=340&end=350", "youtu.be/TYu_V6-nH68?start=130&end=140", "youtu.be/CFD5LdJ4c6g?start=240&end=250", "youtu.be/HflbP7GyruI?start=360&end=370", "youtu.be/Jftp72Bumqs?start=60&end=70", "youtu.be/gsljeuRL8B8?start=40&end=50", "youtu.be/oDUlhlroLJ4?start=370&end=380"],
+    "child_ids": ["/m/07q0h5t"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07q0h5t",
+    "name": "Bleat",
+    "description": "Communicative vocalization of sheep and goats.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=bleat",
+    "positive_examples": ["youtu.be/MUuAhLSHoIk?start=30&end=40", "youtu.be/czUsMpKy3cI?start=30&end=40", "youtu.be/T2YD9v6ae5U?start=4&end=14", "youtu.be/do67PhyvEy4?start=30&end=40", "youtu.be/jY58mai0TEY?start=8&end=18", "youtu.be/xgya66dtxqk?start=400&end=410", "youtu.be/fuHQHczH3qw?start=24&end=34"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07bgp",
+    "name": "Sheep",
+    "description": "Sounds associated with the familiar quadrupedal, ruminant mammal typically kept as livestock.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sheep",
+    "positive_examples": ["youtu.be/P2UCPNoBdag?start=30&end=40", "youtu.be/WLxh17NMGA4?start=9&end=19", "youtu.be/6LC34Fb6G0Y?start=30&end=40", "youtu.be/Ee8uGUrgy9w?start=30&end=40", "youtu.be/97KbMMfCle4?start=30&end=40", "youtu.be/TdHQYarFtTk?start=11&end=21"],
+    "child_ids": ["/m/07q0h5t"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/025rv6n",
+    "name": "Fowl",
+    "description": "Sounds associated with the bird species commonly raised for human consumption.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Fowl",
+    "positive_examples": ["youtu.be/McKxt245g4w?start=30&end=40", "youtu.be/GBNj5Bsy6Fk?start=30&end=40", "youtu.be/X31JvVFCg-w?start=510&end=520", "youtu.be/gLdEFc0LNhI?start=100&end=110", "youtu.be/pd1CH9ukqEw?start=140&end=150", "youtu.be/V1F-0D3G0wc?start=220&end=230", "youtu.be/r2zp3mOVp0g?start=30&end=40", "youtu.be/XZzicSdJnIE?start=10&end=20", "youtu.be/JjGjX6lI-V8?start=230&end=240", "youtu.be/WTKUjbur9_c?start=30&end=40", "youtu.be/cU9AJygC17I?start=130&end=140", "youtu.be/B1TLRcWkYEI?start=20&end=30", "youtu.be/CLlaHYLiThk?start=30&end=40"],
+    "child_ids": ["/m/09b5t", "/m/01rd7k", "/m/09ddx", "/m/0dbvp"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/09b5t",
+    "name": "Chicken, rooster",
+    "description": "Sounds of the very common and widespread domesticated fowl, raised for its eggs and meat.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Chicken",
+    "positive_examples": ["youtu.be/jmcpNukZnxA?start=400&end=410", "youtu.be/ky48d3dPjuE?start=20&end=30", "youtu.be/LFscB8kM8Rg?start=22&end=32", "youtu.be/Jur2s-PBjrw?start=26&end=36", "youtu.be/AAsnk4u8lWk?start=60&end=70", "youtu.be/dzNfwINix_I?start=20&end=30", "youtu.be/8mgRjPyCf1E?start=180&end=190", "youtu.be/AfIilScU_Vg?start=10&end=20", "youtu.be/Mb5le4wgNw4?start=27&end=37"],
+    "child_ids": ["/m/07st89h", "/m/07qn5dc"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07st89h",
+    "name": "Cluck",
+    "description": "The soft, low-pitched, and repetitive sound made by chickens.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=cluck",
+    "positive_examples": ["youtu.be/kf9UZ4KULLE?start=70&end=80", "youtu.be/3xAjsgDxa-k?start=30&end=40", "youtu.be/h10aRwbbCII?start=230&end=240", "youtu.be/pDYOiUrK08c?start=60&end=70", "youtu.be/HmMyQjUUYXI?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qn5dc",
+    "name": "Crowing, cock-a-doodle-doo",
+    "description": "The multi-syllable warning call made by a rooster (male chicken).",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=cock-a-doodle-doo",
+    "positive_examples": ["youtu.be/iYv9pCf8EGg?start=210&end=220", "youtu.be/onu5WVubMBc?start=170&end=180", "youtu.be/RXo_RIfsF5w?start=220&end=230", "youtu.be/aQZoGTQPAss?start=30&end=40", "youtu.be/U9zltf0ENc0?start=30&end=40", "youtu.be/a_Lz2H2hwuE?start=1&end=11", "youtu.be/dX-hbl17gPA?start=5&end=15", "youtu.be/EMVnxrYkzoM?start=13&end=23", "youtu.be/Q7d8Cpmd-Iw?start=25&end=35", "youtu.be/HdgmT8_o5zQ?start=60&end=70"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01rd7k",
+    "name": "Turkey",
+    "description": "Sounds associated with the large poultry bird, originally domesticated in the Americas.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Domesticated_turkey",
+    "positive_examples": ["youtu.be/g13AFjJIpMU?start=19&end=29", "youtu.be/V1F-0D3G0wc?start=220&end=230", "youtu.be/r2zp3mOVp0g?start=30&end=40", "youtu.be/XZzicSdJnIE?start=10&end=20", "youtu.be/JjGjX6lI-V8?start=230&end=240"],
+    "child_ids": ["/m/07svc2k"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07svc2k",
+    "name": "Gobble",
+    "description": "The characteristic sound made by a turkey cock.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=gobble",
+    "positive_examples": ["youtu.be/Y-q_sD0qBFY?start=30&end=40", "youtu.be/0jWAWkL8Pfw?start=11&end=21", "youtu.be/d5qR0aff0Kk?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/09ddx",
+    "name": "Duck",
+    "description": "Sounds associated with this collection of waterfowl species.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Duck",
+    "positive_examples": ["youtu.be/ACBC8no-jDs?start=140&end=150", "youtu.be/7v0S0E5ROXU?start=30&end=40", "youtu.be/L9AKbLaXCWs?start=40&end=50", "youtu.be/UiqRyK6SJjI?start=13&end=23", "youtu.be/320LuZSMlio?start=200&end=210", "youtu.be/320LuZSMlio?start=50&end=60", "youtu.be/S9cndpKCDTE?start=40&end=50"],
+    "child_ids": ["/m/07qdb04"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qdb04",
+    "name": "Quack",
+    "description": "The harsh communication sound made by a duck.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=quack",
+    "positive_examples": ["youtu.be/rBod0icgIsE?start=28&end=38", "youtu.be/k8O07-MW96Q?start=30&end=40", "youtu.be/h2GONUHtAe0?start=29&end=39", "youtu.be/OWFFBIDXwt0?start=30&end=40", "youtu.be/7OSkKoylZmo?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0dbvp",
+    "name": "Goose",
+    "description": "Sounds associated with this species of larger waterfowl.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Goose",
+    "positive_examples": ["youtu.be/WTKUjbur9_c?start=30&end=40", "youtu.be/cU9AJygC17I?start=130&end=140", "youtu.be/B1TLRcWkYEI?start=20&end=30", "youtu.be/CLlaHYLiThk?start=30&end=40", "youtu.be/ImKzYS6swjg?start=430&end=440", "youtu.be/8UJKZE773Ro?start=110&end=120", "youtu.be/s9sbPkAALxw?start=110&end=120"],
+    "child_ids": ["/m/07qwf61"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qwf61",
+    "name": "Honk",
+    "description": "The cry of a goose.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=honk",
+    "positive_examples": ["youtu.be/Yvd3CNp4kT8?start=30&end=40", "youtu.be/DnMzD1SMmsY?start=13&end=23", "youtu.be/Cz1TdU8GjiA?start=30&end=40", "youtu.be/4JTY-UtZLPg?start=30&end=40", "youtu.be/VRJQZQcnv5s?start=30&end=40", "youtu.be/o5dJd0ZXHrc?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01280g",
+    "name": "Wild animals",
+    "description": "Sounds associated with animals not normally raised by humans.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Wildlife",
+    "positive_examples": ["youtu.be/89IuqwavDU8?start=10&end=20", "youtu.be/8R6H_3neiL8?start=20&end=30", "youtu.be/kQ0eoHaF9X8?start=60&end=70", "youtu.be/bSusH6RqC64?start=360&end=370", "youtu.be/Ku1l5EnaZAQ?start=170&end=180", "youtu.be/UKZrOQfUlIM?start=30&end=40", "youtu.be/JZuwem3Y9Rc?start=250&end=260", "youtu.be/hxnKQk51cMg?start=70&end=80"],
+    "child_ids": ["/m/0cdnk", "/m/015p6", "/m/01z5f", "/m/06hps", "/m/03vt0", "/m/09ld4", "/m/078jl", "/m/032n05"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0cdnk",
+    "name": "Roaring cats (lions, tigers)",
+    "description": "Sounds associated with the larger and more ferocious wild relatives of cats.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Panthera",
+    "positive_examples": ["youtu.be/R7LrWG51wi4?start=190&end=200", "youtu.be/rSu1Cr43S2s?start=10&end=20", "youtu.be/ztymBfhfdPY?start=10&end=20", "youtu.be/5e_s-Aaic4k?start=90&end=100", "youtu.be/__-8wVOYH3c?start=70&end=80", "youtu.be/pQBQBVcSjLk?start=290&end=300", "youtu.be/OrKEBfUj95I?start=120&end=130"],
+    "child_ids": ["/m/04cvmfc", "/m/0ghcn6"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04cvmfc",
+    "name": "Roar",
+    "description": "A deep, bellowing outburst of sound forced through an open mouth, made by a lion or other \"big cat\" species.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Roar_(utterance)",
+    "positive_examples": ["youtu.be/V_K53wcR_hc?start=200&end=210", "youtu.be/IFQGJ_jeTMQ?start=370&end=380", "youtu.be/JbPNmYKs7P0?start=38&end=48"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/015p6",
+    "name": "Bird",
+    "description": "Sounds associated with the large group of flying vertebrates.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bird",
+    "positive_examples": ["youtu.be/UPYKFMdmkBI?start=30&end=40", "youtu.be/h3DVqb55DRQ?start=10&end=20", "youtu.be/aBQ9m59MrWw?start=40&end=50", "youtu.be/P1HP0zaWpW4?start=150&end=160", "youtu.be/W1Wp4zzxtZc?start=10&end=20", "youtu.be/U0YJy6vQA4c?start=20&end=30", "youtu.be/orgwzt45ojE?start=30&end=40", "youtu.be/9yPUjp9LLsE?start=310&end=320", "youtu.be/hjicO_5mHF8?start=100&end=110", "youtu.be/TSbkLVHTETY?start=30&end=40"],
+    "child_ids": ["/m/020bb7", "/m/0h0rv", "/m/04s8yn", "/m/09d5_", "/m/01dwxx", "/m/05_wcq"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/020bb7",
+    "name": "Bird vocalization, bird call, bird song",
+    "description": "Bird communication calls, often considered melodious to the human ear.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bird_vocalization",
+    "positive_examples": ["youtu.be/ouPPVBBOODI?start=40&end=50", "youtu.be/s2QGitj2jUc?start=170&end=180", "youtu.be/wT52hDSLFTo?start=340&end=350", "youtu.be/492jB4DXETM?start=240&end=250", "youtu.be/uQB9xtJvgUk?start=30&end=40", "youtu.be/LCFO6o812y0?start=350&end=360", "youtu.be/OqoxikHu7eY?start=20&end=30", "youtu.be/QtZ6qZdacwc?start=70&end=80", "youtu.be/2bUbSeUd9n8?start=30&end=40"],
+    "child_ids": ["/m/07pggtn", "/m/07sx8x_"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pggtn",
+    "name": "Chirp, tweet",
+    "description": "A brief sound as made by a small bird.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=chirp",
+    "positive_examples": ["youtu.be/TSGfF4opE18?start=120&end=130", "youtu.be/DAmwRR8EWlc?start=380&end=390", "youtu.be/YWipp1KTXa8?start=480&end=490", "youtu.be/f6tGN34_izc?start=90&end=100", "youtu.be/QS8t1QDrxfo?start=130&end=140", "youtu.be/AbQBlpdjdu0?start=40&end=50", "youtu.be/sqghcdp_C8I?start=110&end=120", "youtu.be/Eh44C8ocwdM?start=550&end=560", "youtu.be/_JkYH257o2c?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07sx8x_",
+    "name": "Squawk",
+    "description": "Abrasive, unpleasant sharp sound produced by a bird.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=squawk",
+    "positive_examples": ["youtu.be/RtxzI2FngL4?start=20&end=30", "youtu.be/9EqiEH9fgwc?start=270&end=280", "youtu.be/apb5dycPX-0?start=7&end=17", "youtu.be/KaL17J_SMzo?start=400&end=410", "youtu.be/pw6ZPTpn0bE?start=580&end=590"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0h0rv",
+    "name": "Pigeon, dove",
+    "description": "Sounds associated with these species of birds having short necks and short, slender bills.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Columbidae",
+    "positive_examples": ["youtu.be/CF_cw6igH9s?start=30&end=40", "youtu.be/ngXDfqnWHEU?start=30&end=40", "youtu.be/K2xIzdu-Ga0?start=30&end=40", "youtu.be/LZEGjYrMM8o?start=30&end=40", "youtu.be/F5LddF9IU80?start=30&end=40", "youtu.be/mmPHyB4iAPA?start=280&end=290", "youtu.be/gI7kgvkz1DI?start=30&end=40", "youtu.be/jrdY2k4s37c?start=30&end=40", "youtu.be/jDY9LdYDqhI?start=270&end=280"],
+    "child_ids": ["/m/07r_25d"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r_25d",
+    "name": "Coo",
+    "description": "The sound made by a pigeon or dove.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=coo",
+    "positive_examples": ["youtu.be/AvwSHC92GlY?start=100&end=110", "youtu.be/IHAteeW3JME?start=30&end=40", "youtu.be/R5OI1ftOAPs?start=30&end=40", "youtu.be/LcaLdDWhTb4?start=30&end=40", "youtu.be/qhuSO2o3nN8?start=30&end=40", "youtu.be/qizXoi1Re6s?start=30&end=40", "youtu.be/TeLKSjNW35g?start=9&end=19"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04s8yn",
+    "name": "Crow",
+    "description": "Sounds associated with the species of medium-to-large birds, Corvus.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Corvus",
+    "positive_examples": ["youtu.be/NJgk6yyMcIY?start=490&end=500", "youtu.be/EdvEBEGRWkM?start=30&end=40", "youtu.be/EdWgYZ4ffls?start=60&end=70", "youtu.be/iDYQtYqbFMA?start=40&end=50", "youtu.be/VHQjG81NcXE?start=30&end=40", "youtu.be/g6hFofVOmVU?start=170&end=180"],
+    "child_ids": ["/m/07r5c2p"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r5c2p",
+    "name": "Caw",
+    "description": "The relatively harsh sound made by corvine birds.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=caw",
+    "positive_examples": ["youtu.be/xpWvIgTbq80?start=30&end=40", "youtu.be/VYiC9fRYZwM?start=10&end=20", "youtu.be/F7TE4bTue80?start=7&end=17", "youtu.be/gyW4t5ogLyE?start=30&end=40", "youtu.be/zQjpa4I__Ag?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/09d5_",
+    "name": "Owl",
+    "description": "Sounds associated with the mostly solitary and nocturnal carnivorous birds from the order Strigiformes.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Owl",
+    "positive_examples": ["youtu.be/PJRrqdRbh0Q?start=40&end=50", "youtu.be/LEJWmpErDRY?start=30&end=40", "youtu.be/HQuy1_EDCkA?start=30&end=40", "youtu.be/hVsaTVUOzxk?start=30&end=40", "youtu.be/ZLXmK5dVGe0?start=30&end=40", "youtu.be/yw-hqbvLLbc?start=30&end=40"],
+    "child_ids": ["/m/07r_80w"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r_80w",
+    "name": "Hoot",
+    "description": "The loud raucous cry of an owl.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=hoot",
+    "positive_examples": ["youtu.be/m_39THY6PfY?start=30&end=40", "youtu.be/Zhu5ogju62A?start=1&end=11", "youtu.be/ILv7AQF-ltI?start=30&end=40", "youtu.be/dOeLFbMH09A?start=25&end=35"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01dwxx",
+    "name": "Gull, seagull",
+    "description": "Sounds associated with the family of seabirds often encountered in coastal regions.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Owl",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05_wcq",
+    "name": "Bird flight, flapping wings",
+    "description": "Sounds caused by a bird's use of its wings to travel through the air.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bird_flight",
+    "positive_examples": ["youtu.be/BUM9FcAvxJc?start=50&end=60", "youtu.be/SwZxKE3CnEg?start=80&end=90", "youtu.be/RBs0R_be7B0?start=50&end=60", "youtu.be/v_IaZzdchY8?start=30&end=40", "youtu.be/miNSZxKnDsM?start=180&end=190"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01z5f",
+    "name": "Canidae, dogs, wolves",
+    "description": "Sounds associated with the wild relatives of domesticated dogs.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Canidae",
+    "positive_examples": ["youtu.be/OFBbWkmHWok?start=40&end=50", "youtu.be/IRcPJNZkCTc?start=40&end=50", "youtu.be/L_1BdQxn5Is?start=30&end=40", "youtu.be/0HMa_BIbTo0?start=60&end=70", "youtu.be/ExcQZFswFks?start=60&end=70", "youtu.be/HV346cLZxpA?start=30&end=40", "youtu.be/zxEWn0uqw0A?start=30&end=40", "youtu.be/CqKcyXt6laA?start=14&end=24"],
+    "child_ids": ["/m/07qf0zm", "/m/0ghcn6"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06hps",
+    "name": "Rodents, rats, mice",
+    "description": "Sounds associated with the small mammals of the order Rodentia, found in vast numbers on all continents except Antarctica.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Rodent",
+    "positive_examples": ["youtu.be/BGEMgl1xjac?start=340&end=350", "youtu.be/mrcePXm-R0Y?start=110&end=120", "youtu.be/g3ITqDViDAk?start=210&end=220", "youtu.be/U3zf6nQ6pUE?start=10&end=20", "youtu.be/xtzjBhvhBmY?start=150&end=160"],
+    "child_ids": ["/m/04rmv", "/m/02021", "/m/07r4gkf"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04rmv",
+    "name": "Mouse",
+    "description": "Sounds associated with the familiar small rodent.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Mouse",
+    "positive_examples": ["youtu.be/CtfoWY3GqM4?start=60&end=70", "youtu.be/hvBFjdYnW4U?start=30&end=40", "youtu.be/KU4WtmR753Y?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02021",
+    "name": "Chipmunk",
+    "description": "Sounds associated with the small, striped rodents of the family Sciuridae.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Chipmunk",
+    "positive_examples": ["youtu.be/36XjVkEAC_A?start=13&end=23", "youtu.be/6-X5_NZA9Pw?start=2&end=12", "youtu.be/kipCBDj28-U?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r4gkf",
+    "name": "Patter",
+    "description": "A quick succession of light rapid sounds, usually suggesting the locomotion of small animals.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=patter",
+    "positive_examples": ["youtu.be/l5CAOayPe4E?start=50&end=60", "youtu.be/2ay8uwJNX1E?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/03vt0",
+    "name": "Insect",
+    "description": "Sounds associated with invertebrates from the arthropod phylum that have a chitinous exoskeleton, a three-part body, three pairs of jointed legs, compound eyes, and one pair of antennae.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Insect",
+    "positive_examples": ["youtu.be/hIBwx8JqEJI?start=410&end=420", "youtu.be/Df8ayuKMUUs?start=50&end=60", "youtu.be/2VZeKEW4crE?start=50&end=60", "youtu.be/T455LBU8lfU?start=230&end=240", "youtu.be/CL7qusrB888?start=20&end=30", "youtu.be/WVQz8LM_SNI?start=70&end=80"],
+    "child_ids": ["/m/09xqv", "/m/09f96", "/m/0h2mp", "/m/01h3n"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/09xqv",
+    "name": "Cricket",
+    "description": "Sounds associated with these relatives of grasshoppers characterized by enlarged hind legs, providing power for jumping. Crickets are mainly nocturnal, and are best known for the loud, persistent, chirping song of males trying to attract females.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cricket_(insect)",
+    "positive_examples": ["youtu.be/B3aFxHuR7bY?start=30&end=40", "youtu.be/LxUJwOOpJws?start=110&end=120", "youtu.be/jypEvhhECH4?start=70&end=80", "youtu.be/5JTshf6gISY?start=260&end=270", "youtu.be/X0xdCeFkk08?start=450&end=460"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/09f96",
+    "name": "Mosquito",
+    "description": "Sounds associated with these small, midge-like flies whose tube-like mouth parts pierce the hosts' skin to consume blood.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Mosquito",
+    "positive_examples": ["youtu.be/OIkpYphVHVI?start=30&end=40", "youtu.be/crtrt0HbAtg?start=30&end=40", "youtu.be/hq3e3aKFMjQ?start=30&end=40", "youtu.be/ccmAp6PBdDI?start=30&end=40", "youtu.be/p41gzO8pd4k?start=21&end=31"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0h2mp",
+    "name": "Fly, housefly",
+    "description": "Sounds associated with these insects of the order Diptera, which use only a single pair of wings to fly.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Fly",
+    "positive_examples": ["youtu.be/OAuVRzogngc?start=340&end=350", "youtu.be/6UOObVAQS_M?start=30&end=40", "youtu.be/41G_oW9IQrk?start=20&end=30", "youtu.be/kiMG-hDyOPk?start=120&end=130", "youtu.be/U24BkLFGDtg?start=490&end=500"],
+    "child_ids": ["/m/07pjwq1"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pjwq1",
+    "name": "Buzz",
+    "description": "The sound of rapid vibration, commonly the wings of a flying insect.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=buzz",
+    "positive_examples": ["youtu.be/hOqnxZQerhw?start=30&end=40", "youtu.be/PEiKSjl0x0M?start=3&end=13", "youtu.be/tHk9vA5xIPU?start=30&end=40", "youtu.be/-BZuLO9Uvnw?start=30&end=40", "youtu.be/A_n04sE1oyw?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01h3n",
+    "name": "Bee, wasp, etc.",
+    "description": "Sounds associated with these closely-related species of flying insects known for pollination, honey-production, and the ability to sting humans.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bee",
+    "positive_examples": ["youtu.be/GWmgGN3qwLk?start=280&end=290", "youtu.be/rdwmkUJzLRQ?start=400&end=410", "youtu.be/CqkChVlZ0Zc?start=480&end=490", "youtu.be/uGS7O46tlSo?start=70&end=80", "youtu.be/Uax2BiqOKEg?start=130&end=140", "youtu.be/N2arYiB9j-g?start=100&end=110"],
+    "child_ids": ["/m/07pjwq1"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/09ld4",
+    "name": "Frog",
+    "description": "Sounds associated with the short-bodied, tailless amphibians composing the order Anura.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Frog",
+    "positive_examples": ["youtu.be/duywiEdH7kU?start=9&end=19", "youtu.be/-IHAaycWLLo?start=30&end=40", "youtu.be/5NPWv-2F3eM?start=30&end=40", "youtu.be/gff36H5kddQ?start=26&end=36", "youtu.be/JIVTdjGj2eM?start=30&end=40", "youtu.be/T_maPCFQreY?start=60&end=70", "youtu.be/Li8cODFJBJk?start=60&end=70"],
+    "child_ids": ["/m/07st88b"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07st88b",
+    "name": "Croak",
+    "description": "The harsh hoarse utterance of a frog.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=croak",
+    "positive_examples": ["youtu.be/_pFSFgPWnjE?start=30&end=40", "youtu.be/Lc2gZT8Tloc?start=30&end=40", "youtu.be/cX3Zrrld1Tk?start=9&end=19", "youtu.be/QfkpNf93T-Y?start=30&end=40", "youtu.be/_Av6uyAugVQ?start=30&end=40", "youtu.be/BA8YrMd7KVk?start=320&end=330", "youtu.be/_SNr4XpbqNQ?start=30&end=40", "youtu.be/WCYs6hXENGc?start=11&end=21"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/078jl",
+    "name": "Snake",
+    "description": "Sounds associated with the elongated, legless, carnivorous reptiles of the suborder Serpentes.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Snake",
+    "positive_examples": ["youtu.be/6_TjTbIt-xo?start=30&end=40", "youtu.be/rf1OS5Crog8?start=30&end=40", "youtu.be/w3Bdu-s9Tpk?start=30&end=40", "youtu.be/sn0_4kZwmCw?start=90&end=100"],
+    "child_ids": ["/m/07rjwbb", "/m/07qn4z3"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qn4z3",
+    "name": "Rattle",
+    "description": "A rapid series of short loud sounds as of small hard items loose inside a container.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=rattle",
+    "positive_examples": ["youtu.be/cmNsnLQSFjw?start=4&end=14", "youtu.be/TSrlEhhOF5U?start=20&end=30", "youtu.be/8lhdsS_xrvg?start=30&end=40", "youtu.be/f5pPVPk_MY4?start=160&end=170", "youtu.be/uCpEA5JND_c?start=80&end=90"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/032n05",
+    "name": "Whale vocalization",
+    "description": "Sounds produced by whales for different kinds of communication.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Whale_vocalization",
+    "positive_examples": ["youtu.be/SayTcZUipZI?start=250&end=260", "youtu.be/H20tJk2cu-U?start=30&end=40", "youtu.be/u4-VEvmu9kU?start=30&end=40", "youtu.be/hx-UWi3VS8o?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04rlf",
+    "name": "Music",
+    "description": "Music is an art form and cultural activity whose medium is sound and silence. The common elements of music are pitch, rhythm, dynamics, and the sonic qualities of timbre and texture.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Music",
+    "positive_examples": ["youtu.be/E83fRA1wxKU?start=420&end=430", "youtu.be/uNve6Iyh5jA?start=170&end=180", "youtu.be/xMsVXjoVvBY?start=570&end=580", "youtu.be/MM1Fi3tOaKU?start=30&end=40", "youtu.be/obPlMMjBfJo?start=30&end=40", "youtu.be/3MTKFrRID6Y?start=30&end=40", "youtu.be/jz0EDSpW79Q?start=570&end=580", "youtu.be/-UVOFRthq_c?start=30&end=40", "youtu.be/9QxbRgSE0I0?start=30&end=40", "youtu.be/8P-psJ8v8ZA?start=30&end=40"],
+    "child_ids": ["/m/04szw", "/m/0kpv1t", "/t/dd00027", "/t/dd00028", "/t/dd00030"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04szw",
+    "name": "Musical instrument",
+    "description": "Sounds specifically associated with instruments created, adapted or otherwise used to make musical sounds.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Musical_instrument",
+    "positive_examples": ["youtu.be/7umb9yJpkKU?start=70&end=80", "youtu.be/obWlyVlIbXI?start=40&end=50", "youtu.be/5UMC51-0gtY?start=130&end=140", "youtu.be/7RedoApAa5g?start=50&end=60", "youtu.be/kkEwhEEe42E?start=50&end=60", "youtu.be/2SebmDnbwu8?start=120&end=130", "youtu.be/oqToPCSVKvE?start=30&end=40", "youtu.be/74CdH7qHL9Q?start=30&end=40", "youtu.be/QGL1xK5D8Fw?start=30&end=40"],
+    "child_ids": ["/m/0fx80y", "/m/05148p4", "/m/0l14md", "/m/05pd6", "/m/01kcd", "/m/0l14_3", "/m/085jw", "/m/03m5k", "/m/0l14jd", "/m/0395lw", "/m/03qjg", "/m/0mkg", "/m/0192l", "/m/02bxd", "/m/0l14l2", "/m/07kc_", "/m/0l14t7", "/m/05229", "/m/01vj9c", "/m/01hgjl"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0fx80y",
+    "name": "Plucked string instrument",
+    "description": "Sounds of a musical instrument using tensioned strings to produce tones, where the usual mode of playing is to pull and release the strings to cause them to vibrate.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Plucked_string_instrument",
+    "positive_examples": ["youtu.be/623y1sJMR3k?start=50&end=60", "youtu.be/cW7XnBXFi6w?start=30&end=40", "youtu.be/OFWD8T1wqHo?start=80&end=90", "youtu.be/sYoJJnswtZc?start=180&end=190", "youtu.be/e6yoR0fEmR0?start=30&end=40", "youtu.be/BxOQq1ZNtCk?start=30&end=40", "youtu.be/wBK_7cToiNU?start=50&end=60", "youtu.be/h-UHIxkUhBM?start=90&end=100"],
+    "child_ids": ["/m/0342h", "/m/018j2", "/m/0jtg0", "/m/04rzd", "/m/01bns_", "/m/07xzm"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0342h",
+    "name": "Guitar",
+    "description": "Sounds of a string instrument with between 4 and 18 strings (typically 6) running over a fretboard, typically played by strumming or plucking the strings with the right hand while fretting the strings with the fingers of the left hand.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Guitar",
+    "positive_examples": ["youtu.be/4M8jrnFOsv4?start=250&end=260", "youtu.be/3a7ZQYncZzo?start=30&end=40", "youtu.be/03zEmRftWkE?start=30&end=40", "youtu.be/0EZTOSkuFy0?start=30&end=40", "youtu.be/WhcHkiTCg2Y?start=10&end=20", "youtu.be/YophyPW6R2M?start=40&end=50", "youtu.be/NtjgQir_GwM?start=390&end=400"],
+    "child_ids": ["/m/02sgy", "/m/018vs", "/m/042v_gx", "/m/06w87", "/m/01glhc", "/m/07s0s5r"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02sgy",
+    "name": "Electric guitar",
+    "description": "Sounds of a guitar that uses a pickup to convert the vibration of its strings (which are typically made of metal, and which occurs when a guitarist strums, plucks, or fingerpicks the strings) into electrical impulses, which are then amplified and converted to sound.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Electric_guitar",
+    "positive_examples": ["youtu.be/vsseT3Rm88s?start=250&end=260", "youtu.be/GCz2JE4UUxs?start=120&end=130", "youtu.be/rEpG-An1E_g?start=470&end=480", "youtu.be/qOkBZPbv85k?start=410&end=420", "youtu.be/q03HDM5GvMY?start=20&end=30", "youtu.be/17Lx5LoeI3s?start=30&end=40", "youtu.be/uUQyXlqMlVo?start=60&end=70", "youtu.be/5_yzPAQHclw?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/018vs",
+    "name": "Bass guitar",
+    "description": "Sounds of a relative of the electric guitar with a longer neck and 4 to 6 strings. The common 4-string bass is usually tuned one octave lower than the four lowest pitched strings of a guitar.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bass_guitar",
+    "positive_examples": ["youtu.be/p4Wapz6rZWc?start=120&end=130", "youtu.be/f1yunD_7XFI?start=50&end=60", "youtu.be/3YtCNw7vY3A?start=10&end=20", "youtu.be/08uDXandwEQ?start=60&end=70", "youtu.be/9bQeCu-hYfE?start=40&end=50", "youtu.be/8tV2X-AvdY8?start=50&end=60", "youtu.be/XFQzDpqzkT4?start=80&end=90"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/042v_gx",
+    "name": "Acoustic guitar",
+    "description": "Sounds of a guitar that produces sound acoustically by transmitting the vibration of the strings from its body to the air. Includes guitars with both nylon (or gut) strings, and those with steel strings.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Acoustic_guitar",
+    "positive_examples": ["youtu.be/0_MLIPfb84s?start=30&end=40", "youtu.be/-37uZp3L3vw?start=30&end=40", "youtu.be/zeAO1j2LStk?start=10&end=20", "youtu.be/-SOoc9Rr39Y?start=12&end=22", "youtu.be/-DPoX0GdToU?start=130&end=140", "youtu.be/GDfQPFcG74k?start=150&end=160", "youtu.be/4gZkMShMpmc?start=30&end=40", "youtu.be/OSSa7XnAxkk?start=460&end=470", "youtu.be/mPEQ9bBWUYE?start=210&end=220", "youtu.be/ygonIq0Qatk?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06w87",
+    "name": "Steel guitar, slide guitar",
+    "description": "Sounds of a guitar whose string length is controlled by a hard object placed on the string (the \"slide\" or \"steel\") instead of by pressing against the frets with the fingers.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Steel_guitar",
+    "positive_examples": ["youtu.be/0fcW2Nu_yk4?start=70&end=80", "youtu.be/gGEMCZmcJo0?start=130&end=140", "youtu.be/KvDjUWfxLvw?start=210&end=220", "youtu.be/JY_l4taOZG4?start=180&end=190", "youtu.be/Zne2aFaPEjE?start=180&end=190"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01glhc",
+    "name": "Tapping (guitar technique)",
+    "description": "Sounds of a guitar playing technique, where a string is fretted and set into vibration as part of a single motion of being pushed onto the fretboard, as opposed to the standard technique being fretted with one hand and picked with the other.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Tapping",
+    "positive_examples": ["youtu.be/hrOa0R7Lfvg?start=10&end=20", "youtu.be/ML3A4Z1UrG4?start=60&end=70", "youtu.be/sAD_dtC_6cM?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07s0s5r",
+    "name": "Strum",
+    "description": "The sound of playing a guitar by dragging a finger or plectrum over multiple strings near-simultaneously.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=strum",
+    "positive_examples": ["youtu.be/J8Fp-ol3oWk?start=30&end=40", "youtu.be/-_WO2kys2tU?start=30&end=40", "youtu.be/14jEF7Bhx0Q?start=30&end=40", "youtu.be/-eUHclSdrz4?start=30&end=40", "youtu.be/2a-u6r7pPgU?start=30&end=40", "youtu.be/-rDW578Jqpw?start=30&end=40", "youtu.be/yfsV_LY2rS4?start=470&end=480", "youtu.be/tj375STXuek?start=90&end=100"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/018j2",
+    "name": "Banjo",
+    "description": "Sounds of a 4-, 5-, or 6-stringed instrument with a thin membrane stretched over a frame or cavity as a resonator, called the head.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Banjo",
+    "positive_examples": ["youtu.be/l_7B1wnTNtA?start=20&end=30", "youtu.be/R-coz17NCsE?start=250&end=260", "youtu.be/miFBEtS8iaw?start=70&end=80", "youtu.be/M2w7M0xhCok?start=30&end=40", "youtu.be/zm0qNj8QaLA?start=160&end=170", "youtu.be/3kaCL9Zu7NY?start=170&end=180", "youtu.be/1COTNE5iwpw?start=70&end=80"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0jtg0",
+    "name": "Sitar",
+    "description": "Sounds of a plucked stringed instrument used mainly in Hindustani and Indian classical music, which derives its distinctive timbre and resonance from sympathetic strings, bridge design, a long hollow neck, and a gourd-shaped resonance chamber.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sitar",
+    "positive_examples": ["youtu.be/UB5Lh65DhGI?start=240&end=250", "youtu.be/NvAlKJXWuz0?start=220&end=230", "youtu.be/JLyg8PK6VzY?start=150&end=160", "youtu.be/9SvlmFWEsJE?start=530&end=540", "youtu.be/XLv-1DYujvo?start=470&end=480", "youtu.be/eVmuNiSlM08?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04rzd",
+    "name": "Mandolin",
+    "description": "Sounds of an instrument in the lute family, commonly with 4 courses of doubled metal strings, usually plucked with a plectrum or \"pick\".",
+    "citation_uri": "http://en.wikipedia.org/wiki/Mandolin",
+    "positive_examples": ["youtu.be/EiL4B7P8w5E?start=160&end=170", "youtu.be/UfCnuSlcb8c?start=230&end=240", "youtu.be/V2TOF7oO5iw?start=30&end=40", "youtu.be/6hBBOM8wkzY?start=30&end=40", "youtu.be/7vugt_BNbK0?start=230&end=240"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01bns_",
+    "name": "Zither",
+    "description": "Sounds of a class of stringed instruments consisting of many strings stretched across a thin, flat body, played by strumming or plucking.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Zither",
+    "positive_examples": ["youtu.be/dvmutEzAcjA?start=140&end=150", "youtu.be/-VtQ1KQPAzU?start=30&end=40", "youtu.be/-Mtj9kQgkk4?start=30&end=40", "youtu.be/03Am-YeLdK8?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07xzm",
+    "name": "Ukulele",
+    "description": "Sounds of a small four-stringed guitar-like instument that originated in Hawaii.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Ukulele",
+    "positive_examples": ["youtu.be/Szh-0r2nefs?start=30&end=40", "youtu.be/c6AjhdkSNWI?start=30&end=40", "youtu.be/lawaVpYj3t4?start=210&end=220", "youtu.be/UNJX3yYxJjE?start=30&end=40", "youtu.be/aVjQk_ZTOQU?start=230&end=240", "youtu.be/fxDPFgl_uhU?start=30&end=40", "youtu.be/7LhnENv-9vw?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05148p4",
+    "name": "Keyboard (musical)",
+    "description": "Sounds of a musical instrument played using a keyboard, most commonly the piano, organ, and various electronic keyboards, including synthesizers and digital pianos.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Keyboard_instrument",
+    "positive_examples": ["youtu.be/11bWvQaQhrM?start=440&end=450", "youtu.be/E7PfYoBL14c?start=80&end=90", "youtu.be/OOKSJ45MgmI?start=30&end=40", "youtu.be/8f3xNkAxq8E?start=20&end=30", "youtu.be/YfMY4JtzeEA?start=340&end=350", "youtu.be/6nTvu7T6cGk?start=30&end=40", "youtu.be/_HxoLyv0zA4?start=130&end=140", "youtu.be/1wYs3gtvFRk?start=340&end=350", "youtu.be/msC0nzoxin4?start=120&end=130"],
+    "child_ids": ["/m/05r5c", "/m/013y1f", "/m/0l14qv", "/m/03q5t"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05r5c",
+    "name": "Piano",
+    "description": "Sounds of a musical instrument played via a row of keys that the performer presses down or strikes with the fingers and thumbs of both hands, to trigger a decaying note whose loudness reflects the vigor of the press.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Piano",
+    "positive_examples": ["youtu.be/jETQAE_vBQI?start=30&end=40", "youtu.be/MvA6dSsIPdM?start=380&end=390", "youtu.be/Sq8vJKMiTbA?start=210&end=220", "youtu.be/vTCVxCW77wA?start=200&end=210", "youtu.be/5IAzn0I7IOs?start=30&end=40", "youtu.be/FR9EWioJq6s?start=590&end=600", "youtu.be/rPYyIE1lfeA?start=410&end=420"],
+    "child_ids": ["/m/01s0ps"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01s0ps",
+    "name": "Electric piano",
+    "description": "Sounds of a music instrument with a piano-style keyboard, where pressing keys causes mechanical hammers to strike metal strings, metal reeds, or wire tines, leading to vibrations which are converted into electrical signals by magnetic pickups.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Electric_piano",
+    "positive_examples": ["youtu.be/skeFawZe__U?start=30&end=40", "youtu.be/m484xjK104Y?start=20&end=30", "youtu.be/ExBXCryXOak?start=80&end=90", "youtu.be/-DDiBs4JIxc?start=140&end=150", "youtu.be/-YATTKBtmRA?start=190&end=200"],
+    "child_ids": ["/m/025cbm", "/m/0bxl5"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/025cbm",
+    "name": "Clavinet",
+    "description": "Sounds of an electrically-amplified keyboard instrument with a distinctive bright staccato sound, popular in funk, jazz-funk, rock, and soul songs.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Clavinet",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0bxl5",
+    "name": "Rhodes piano",
+    "description": "Sounds of an electric piano invented by Harold Rhodes in which the hammers strike thin metal tines, which are then amplified via an electromagnetic pickup.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Rhodes_piano",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/013y1f",
+    "name": "Organ",
+    "description": "Sounds of a keyboard instrument of one or more pipe divisions, each played with its own keyboard, played either with the hands on a keyboard or with the feet using pedals. Unlike the piano, organ notes typically sustain while the key is depressed, rather than dying away.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Organ_(music)",
+    "positive_examples": ["youtu.be/ddoz52PLnnM?start=480&end=490", "youtu.be/-JXGBn-QDFY?start=60&end=70", "youtu.be/BBfp97N31ag?start=30&end=40", "youtu.be/tkPPIT_n4NQ?start=60&end=70", "youtu.be/XW2nILE5__g?start=80&end=90", "youtu.be/Kvpav8cFKhM?start=100&end=110", "youtu.be/VGwNAk50fcQ?start=50&end=60"],
+    "child_ids": ["/m/03xq_f", "/m/03gvt"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03xq_f",
+    "name": "Electronic organ",
+    "description": "Sounds of an electronic keyboard instrument designed to imitate the sound of the pipe organ.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Electronic_organ",
+    "positive_examples": ["youtu.be/3KEPeUOABxc?start=30&end=40", "youtu.be/uE2oHfgljwE?start=230&end=240", "youtu.be/dyxYEQbWAxM?start=60&end=70", "youtu.be/sFq05nFNw4k?start=150&end=160", "youtu.be/nl0nKw-1VkU?start=30&end=40", "youtu.be/pk8CAgk7tHU?start=310&end=320", "youtu.be/zaw7smD79XA?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03gvt",
+    "name": "Hammond organ",
+    "description": "Sounds of an electric organ invented by Laurens Hammond and John M. Hanert in which sliding drawbars create a variety of sounds.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Hammond_organ",
+    "positive_examples": ["youtu.be/d9r_kYpOvW8?start=30&end=40", "youtu.be/BjPvQnVQsOw?start=20&end=30", "youtu.be/YQSYAXHgZ24?start=30&end=40", "youtu.be/UxOSSoMg7eA?start=30&end=40", "youtu.be/n6JP70Sr76k?start=10&end=20", "youtu.be/2eP3SBgYDEQ?start=30&end=40", "youtu.be/aDJDaIgme3k?start=30&end=40", "youtu.be/HH3qmmKao2E?start=100&end=110"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0l14qv",
+    "name": "Synthesizer",
+    "description": "Sounds associated with an electronic musical instrument that generates electric signals converted to sound through amplifiers and loudspeakers or headphones. Synthesizers may imitate instruments such as piano, organ, flute, or vocals; or they may generate novel electronic timbres.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Synthesizer",
+    "positive_examples": ["youtu.be/DQ5KwZ2qBMY?start=390&end=400", "youtu.be/wb6eNKCdmgc?start=290&end=300", "youtu.be/drDfZAkVi4k?start=500&end=510", "youtu.be/XBDxkLByWRQ?start=130&end=140", "youtu.be/vxJ_lQpZcRk?start=550&end=560", "youtu.be/xlEZYQOt9-Q?start=210&end=220"],
+    "child_ids": ["/m/01v1d8", "/m/0gkd1"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01v1d8",
+    "name": "Sampler",
+    "description": "Sounds suggesting the use of an electronic musical instrument that uses recordings of sounds loaded or recorded into it by the user, then played back by means of the sampler program itself, a keyboard, sequencer, or another triggering device.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sampler_(musical_instrument)",
+    "positive_examples": ["youtu.be/P_Tr82fXp54?start=30&end=40", "youtu.be/EJXeCTtWX1I?start=200&end=210", "youtu.be/RNN-S-X61qM?start=30&end=40", "youtu.be/2KkNk9Ao7G4?start=150&end=160", "youtu.be/D0ZsJnmBde0?start=30&end=40", "youtu.be/CsGMebE_xgk?start=30&end=40", "youtu.be/9RBzsjga73s?start=10&end=20", "youtu.be/OMoXXckByJI?start=50&end=60", "youtu.be/bMp1fPnQyWo?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0gkd1",
+    "name": "Mellotron",
+    "description": "Sounds of an electro-mechanical, polyphonic tape replay keyboard in which each note is produced by a separate piece of pre-recorded tape, supplied in a corresponding set to simulate a particular instrument.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Mellotron",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/03q5t",
+    "name": "Harpsichord",
+    "description": "Sounds of a keyboard-controlled instrument in which each key plucks a particular string.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Harpsichord",
+    "positive_examples": ["youtu.be/3QyBsEwyI4g?start=230&end=240", "youtu.be/kaYBmFJzseo?start=400&end=410", "youtu.be/S_zInSBhWhU?start=100&end=110"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0l14md",
+    "name": "Percussion",
+    "description": "The sound of a musical instrument that is sounded by being struck or scraped by a beater; struck, scraped or rubbed by hand; or struck against another similar instrument.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Percussion_instrument",
+    "positive_examples": ["youtu.be/cEvgKicGrNs?start=30&end=40", "youtu.be/OK5Ev_1OcbU?start=220&end=230", "youtu.be/LszgixYT18E?start=30&end=40", "youtu.be/3yMo8i-ws7o?start=30&end=40", "youtu.be/dxPcrVYlaX8?start=30&end=40", "youtu.be/HFVIKa0XcPg?start=30&end=40", "youtu.be/x22NHqwKSNE?start=90&end=100"],
+    "child_ids": ["/m/02hnl", "/m/026t6", "/m/01qbl", "/m/0239kh", "/m/01sm1g", "/m/07brj", "/m/05r5wn", "/m/0mbct", "/m/016622", "/m/0j45pbj"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02hnl",
+    "name": "Drum kit",
+    "description": "Sounds of a collection of drums and other percussion instruments, typically cymbals, which are set up on stands to be played by a single player with drumsticks held in both hands and the feet operating pedals that control the hi-hat cymbal and the beater for the bass drum.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Drum_kit",
+    "positive_examples": ["youtu.be/-VqHJfjcNl8?start=70&end=80", "youtu.be/-kgUDrfLbKw?start=10&end=20", "youtu.be/a7N-Oa4NKKI?start=30&end=40", "youtu.be/BuHnSV6592c?start=30&end=40", "youtu.be/klUmhkMVtN8?start=70&end=80", "youtu.be/hcjHzFKgXSE?start=30&end=40", "youtu.be/xaHjFAy54dU?start=40&end=50", "youtu.be/p9Rh85FgFYk?start=90&end=100", "youtu.be/lhH4TTaAQvU?start=150&end=160"],
+    "child_ids": ["/m/0cfdd"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0cfdd",
+    "name": "Drum machine",
+    "description": "Sounds of an electronic musical instrument designed to imitate the sound of drums, cymbals, other percussion instruments, and often basslines.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Drum_machine",
+    "positive_examples": ["youtu.be/OEpMpYMjO9Y?start=30&end=40", "youtu.be/UmoQDRfLpiI?start=30&end=40", "youtu.be/0ZwxHoPdHqI?start=20&end=30", "youtu.be/aONVSrSlbYM?start=70&end=80", "youtu.be/EzALQdZ5RnI?start=30&end=40", "youtu.be/_jdcbOFrg4Q?start=360&end=370", "youtu.be/sfiDHExt6rI?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/026t6",
+    "name": "Drum",
+    "description": "The sound of an instrument consisting of at least one membrane, called a drumhead or drum skin, that is stretched over a shell and struck, either directly with the player's hands, or with a drum stick, to produce sound.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Drum",
+    "positive_examples": ["youtu.be/65uPPy5e8oI?start=30&end=40", "youtu.be/GZ-jXUN0Hpg?start=70&end=80", "youtu.be/P1f09xVBNTc?start=150&end=160", "youtu.be/lYALJ6L251c?start=320&end=330", "youtu.be/EyopPrqUxcU?start=180&end=190", "youtu.be/6WdMSnWhppk?start=280&end=290", "youtu.be/2ZEkawx_eL8?start=120&end=130", "youtu.be/7E4uaC3YkHM?start=60&end=70", "youtu.be/aJpy-R7ZFb8?start=30&end=40"],
+    "child_ids": ["/m/06rvn", "/m/0bm02", "/m/011k_j", "/m/01p970"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06rvn",
+    "name": "Snare drum",
+    "description": "The sound of a drum that produces a sharp staccato sound by virtue of metal coils (the \"snare\") stretched across one of the membranes.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Snare_drum",
+    "positive_examples": ["youtu.be/1vhU7Zn-VBM?start=270&end=280", "youtu.be/_U8C951VmOc?start=30&end=40", "youtu.be/rZa2PFRUfyg?start=90&end=100", "youtu.be/UtlddariDo4?start=60&end=70", "youtu.be/3e7FToRhcTE?start=40&end=50", "youtu.be/7BEUpZOEFAQ?start=100&end=110", "youtu.be/dAAfKqP13QE?start=30&end=40", "youtu.be/B6XqwiZ_cmE?start=40&end=50", "youtu.be/kmiLtUMZPeA?start=60&end=70"],
+    "child_ids": ["/m/03t3fj", "/m/02k_mr"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03t3fj",
+    "name": "Rimshot",
+    "description": "The sound of an accented snare drum beat produced by simultaneously hitting the rim and head of a drum with a drum stick.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Rimshot",
+    "positive_examples": ["youtu.be/BZLfT6ZqGHU?start=30&end=40", "youtu.be/1dXUNNc180g?start=270&end=280", "youtu.be/BMpPQuKbJ6U?start=30&end=40", "youtu.be/6ao2_JxtXjU?start=60&end=70", "youtu.be/-cNY6fbbldY?start=30&end=40", "youtu.be/LrLz1wRVdbg?start=30&end=40", "youtu.be/1Og2YfIVZKQ?start=20&end=30", "youtu.be/B6XqwiZ_cmE?start=40&end=50", "youtu.be/1Yw69hcsaYg?start=30&end=40", "youtu.be/1hTljKxD8aY?start=320&end=330"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02k_mr",
+    "name": "Drum roll",
+    "description": "A sustained sound produced by multiple, rapid strikes between drum sticks and drum, made possible by bouncing alternating sticks off the head to produce a temporally dense sequence.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Drum_roll",
+    "positive_examples": ["youtu.be/-r-iX1t7eE8?start=420&end=430", "youtu.be/vBHIihIl_vg?start=50&end=60", "youtu.be/jBIJvd3pUYE?start=230&end=240", "youtu.be/SC8RGKfaJrQ?start=60&end=70"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0bm02",
+    "name": "Bass drum",
+    "description": "The sound of a large drum that produces a note of low definite or indefinite pitch.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bass_drum",
+    "positive_examples": ["youtu.be/umIND3KZyqs?start=70&end=80", "youtu.be/h1L06porcL0?start=220&end=230", "youtu.be/khRBhDUyLb0?start=360&end=370", "youtu.be/ts76TqD6eiQ?start=30&end=40", "youtu.be/k36gVPLVPU4?start=50&end=60", "youtu.be/vYoHjD5slzg?start=80&end=90", "youtu.be/yTgBSKCZ1ag?start=240&end=250", "youtu.be/fokECmrANcs?start=310&end=320", "youtu.be/cBJGUfPyGcw?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/011k_j",
+    "name": "Timpani",
+    "description": "The sound of an orchestral drum consisting of a skin stretched over a large bowl traditionally made of copper, where the head is tensioned to produce an identifiable pitch.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Timpani",
+    "positive_examples": ["youtu.be/oczQMKP1GlU?start=190&end=200", "youtu.be/QVouc9CpXiw?start=30&end=40", "youtu.be/aoJ9P5IatjU?start=440&end=450", "youtu.be/boCwqpKwWsY?start=110&end=120", "youtu.be/IsFkruyADHc?start=410&end=420", "youtu.be/FzcVZOICJeU?start=240&end=250"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01p970",
+    "name": "Tabla",
+    "description": "The sound of a classical Hindustani percussion instrument consisting of a pair of hand drums of contrasting sizes and timbres, producing distinct pitches when struck. The larger drum has a pitch that can be manipulated with the player's hand.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Tabla",
+    "positive_examples": ["youtu.be/WXUfeWxCKlI?start=250&end=260", "youtu.be/FwW2Rjd-Rds?start=70&end=80", "youtu.be/5FQI0Fzt57Q?start=10&end=20", "youtu.be/OVkxmOGRzEk?start=270&end=280", "youtu.be/m9qHnNaAskw?start=100&end=110", "youtu.be/8fA1_gzERUE?start=20&end=30", "youtu.be/XmIRBoXWbQ0?start=190&end=200"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01qbl",
+    "name": "Cymbal",
+    "description": "The sound of a percussion instrument consisting of thin, normally round plates of various alloys. They may be used in pairs, struck together, or as single cymbals struck with sticks.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cymbal",
+    "positive_examples": ["youtu.be/0nURxLEqvRc?start=170&end=180", "youtu.be/JnrAsNneLbo?start=110&end=120", "youtu.be/hZaqDtQprgI?start=130&end=140", "youtu.be/CBi8zo190Rc?start=70&end=80", "youtu.be/I6rouB_37sE?start=80&end=90", "youtu.be/MQ5RUPOYTRI?start=30&end=40", "youtu.be/2FViTj8j_oc?start=250&end=260", "youtu.be/AQ4y-cd5jTc?start=70&end=80"],
+    "child_ids": ["/m/03qtq", "/m/0bm0k"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03qtq",
+    "name": "Hi-hat",
+    "description": "The sound of a mating pair of small cymbals mounted atop one-another on a stand, the bottom fixed and the top activated up and down by a foot pedal. The rate of decay of the sound is changed between a shimmering and sharp effect by pressing on the pedal.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Hi-hat",
+    "positive_examples": ["youtu.be/Jo-Rlw1dl0Y?start=70&end=80", "youtu.be/jEgdYuCQPtk?start=30&end=40", "youtu.be/4LPBTlzBfgU?start=230&end=240", "youtu.be/AVwL9t-Hhlw?start=30&end=40", "youtu.be/-A743FXw0VE?start=140&end=150"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0bm0k",
+    "name": "Crash cymbal",
+    "description": "The sound of a cymbal that produces a loud, sharp \"crash\" used for occasional accents.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Crash_cymbal",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/01sm1g",
+    "name": "Wood block",
+    "description": "The sound of a small slit drum made from a single piece of wood, making a very short, clean sound.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Wood_block",
+    "positive_examples": ["youtu.be/4qxz8m23ZCk?start=3&end=13", "youtu.be/4uBq4jhmsEw?start=3&end=13", "youtu.be/nHPrHjUaPDI?start=70&end=80", "youtu.be/pKk1OLOBap4?start=220&end=230"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07brj",
+    "name": "Tambourine",
+    "description": "The sound of a musical instrument consisting of a frame with pairs of small metal jingles. There is often a drumhead stretched across the frame, and the instrument is usually played by striking the frame or head with the hand.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Tambourine",
+    "positive_examples": ["youtu.be/brAD8wCj00U?start=16&end=26", "youtu.be/sQY6hx71INQ?start=30&end=40", "youtu.be/U6aLiMIlqCc?start=250&end=260", "youtu.be/dlB9D-tD8Jg?start=13&end=23", "youtu.be/3P9Mp5FjMPo?start=120&end=130", "youtu.be/g-erbiFIy30?start=310&end=320", "youtu.be/gDnJoHpSL4M?start=40&end=50", "youtu.be/mU6cfEWw5Og?start=180&end=190", "youtu.be/U716X--8X18?start=150&end=160", "youtu.be/1ycXNv1vgFs?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05r5wn",
+    "name": "Rattle (instrument)",
+    "description": "The sound of an instrument that produces a sound when shaken, usually consisting of a closed rigid shell containing numerous small particles that strike the shell when shaken.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Rattle_(percussion_instrument)",
+    "positive_examples": ["youtu.be/ZJtY7zzYROI?start=10&end=20", "youtu.be/L7VmcEuksqs?start=120&end=130", "youtu.be/FAhfuP_xh5Y?start=450&end=460", "youtu.be/kNMqGt7SNMo?start=10&end=20", "youtu.be/Z05m7IQ3-b0?start=110&end=120"],
+    "child_ids": ["/m/0xzly"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0xzly",
+    "name": "Maraca",
+    "description": "The sound of a specific kind of rattle that appears in many genres of Caribbean and Latin music. Players hold them by their handles, usually in pairs, and shake them.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Maraca",
+    "positive_examples": ["youtu.be/tx39HB2qQfg?start=160&end=170", "youtu.be/UH--XDDtwUA?start=50&end=60", "youtu.be/BBncSiS4-jg?start=30&end=40", "youtu.be/UxKwjMKGLhQ?start=80&end=90"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0mbct",
+    "name": "Gong",
+    "description": "The sound of a musical percussion instrument consisting of a flat, circular metal disc which is hit with a mallet.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Gong",
+    "positive_examples": ["youtu.be/JUrbfbmArBQ?start=290&end=300", "youtu.be/cj3eSVIrKs8?start=50&end=60", "youtu.be/ShuwAKNiOsc?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/016622",
+    "name": "Tubular bells",
+    "description": "Sounds of tuned percussion instruments consisting of a metal tube, tuned by altering its length in the range C4-F5.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Tubular_bells",
+    "positive_examples": ["youtu.be/-bE5twf76Jw?start=30&end=40", "youtu.be/Ht3AjqvgRq0?start=20&end=30", "youtu.be/JKZ-_CVEJKY?start=210&end=220"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0j45pbj",
+    "name": "Mallet percussion",
+    "description": "Sounds of melodic percussion instruments consisting of an array of elements, one for each note, played with mallets.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Mallet_percussion",
+    "positive_examples": ["youtu.be/Xk5sz4pmOdw?start=180&end=190", "youtu.be/1WYJ1qfQghA?start=30&end=40", "youtu.be/ZTu4mSOhOrU?start=190&end=200", "youtu.be/Z7jt1J4zpys?start=80&end=90", "youtu.be/soKp5kWpZAI?start=20&end=30", "youtu.be/OIeyYgZknyM?start=80&end=90"],
+    "child_ids": ["/m/0dwsp", "/m/0dwtp", "/m/0dwt5", "/m/0l156b"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0dwsp",
+    "name": "Marimba, xylophone",
+    "description": "Sounds of a percussion instrument consisting of a set of wooden bars struck with mallets to produce musical tones. Resonators suspended underneath the bars may amplify their sound.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Marimba",
+    "positive_examples": ["youtu.be/boCwqpKwWsY?start=20&end=30", "youtu.be/Vvqf6rxvnJ8?start=40&end=50", "youtu.be/UB-F2trb4Fs?start=510&end=520", "youtu.be/ht4GN2h5bYo?start=440&end=450", "youtu.be/-iqoiKgKNYE?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0dwtp",
+    "name": "Glockenspiel",
+    "description": "Sounds of a percussion instrument composed of a set of tuned metal plates or tubes laid out like the keyboard of a piano.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Glockenspiel",
+    "positive_examples": ["youtu.be/jAuskt6flA4?start=110&end=120", "youtu.be/66B8oYpHKfc?start=20&end=30", "youtu.be/LCUwzeqbhdY?start=40&end=50", "youtu.be/gJopkFkV6ho?start=20&end=30", "youtu.be/P9_5_2tHTM8?start=170&end=180"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0dwt5",
+    "name": "Vibraphone",
+    "description": "Sounds of a tuned mallet percussion instrument similar to a xylophone or glockenspiel with the addition a motor-driven valve on each resonator that produce a tremolo or vibrato effect.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Vibraphone",
+    "positive_examples": ["youtu.be/2M-P1FB9QAk?start=10&end=20", "youtu.be/mAbApaNedVc?start=230&end=240", "youtu.be/eXTErlP38Cc?start=60&end=70", "youtu.be/7i3HNSNwz4s?start=60&end=70", "youtu.be/VeITc7tV24k?start=420&end=430", "youtu.be/XDtWBZ0EUBk?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0l156b",
+    "name": "Steelpan",
+    "description": "Sounds of a tuned percussion instrument originally constructed from steel oil drums by hammering out small patches on the head to produce separate pitches.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Steelpan",
+    "positive_examples": ["youtu.be/kMwTShj-LnY?start=90&end=100", "youtu.be/ZTfCj_u1wu0?start=80&end=90", "youtu.be/XC_k5KRn0yc?start=70&end=80", "youtu.be/qNIJV7f0CRY?start=430&end=440", "youtu.be/x56KbBd4wGU?start=40&end=50", "youtu.be/SxyxQndQL8g?start=30&end=40", "youtu.be/H_uOu7ipuYk?start=70&end=80"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05pd6",
+    "name": "Orchestra",
+    "description": "The sound of a large instrumental ensemble (a dozen or more people), often used in classical music, that contains sections of string, brass, woodwind, and percussion instruments.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Orchestra",
+    "positive_examples": ["youtu.be/AdXeApNvWEs?start=30&end=40", "youtu.be/INDEchOtcAs?start=140&end=150", "youtu.be/i1orsU9GvV4?start=210&end=220", "youtu.be/McaaPRnasK4?start=100&end=110", "youtu.be/XVocggdVOQU?start=30&end=40", "youtu.be/_LI3WVnOjPI?start=310&end=320", "youtu.be/57bXQfZlbzY?start=240&end=250"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01kcd",
+    "name": "Brass instrument",
+    "description": "The sound of a musical instrument that produces sound by vibration of air in a tubular resonator in sympathy with the vibration of the player's lips.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Brass_instrument",
+    "positive_examples": ["youtu.be/MQJSNWtvojI?start=10&end=20", "youtu.be/PaupGh4ZNpM?start=250&end=260", "youtu.be/2XAA3oS6ws4?start=170&end=180", "youtu.be/-k6TMxNASFQ?start=490&end=500", "youtu.be/uG4zreyH1Yo?start=60&end=70", "youtu.be/P3EpQMrRtpQ?start=40&end=50", "youtu.be/Di7Rs4QmYKI?start=150&end=160", "youtu.be/UB0P7ZG8DDg?start=20&end=30", "youtu.be/qhYax0Adtas?start=60&end=70"],
+    "child_ids": ["/m/0319l", "/m/07gql", "/m/07c6l", "/m/020w2", "/m/0y64j"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0319l",
+    "name": "French horn",
+    "description": "The sound of a brass instrument made of tubing wrapped into a coil with a flared bell. A modern French horn includes valves to control pitch by routing air into extra sections of tubing.",
+    "citation_uri": "http://en.wikipedia.org/wiki/French_horn",
+    "positive_examples": ["youtu.be/FfAGd9uFcuc?start=29&end=39", "youtu.be/dSAFI_547oQ?start=30&end=40", "youtu.be/wQhycJsKSPE?start=340&end=350", "youtu.be/EWnC6IbYpgs?start=440&end=450"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07gql",
+    "name": "Trumpet",
+    "description": "The sound of a high-pitched brass instruments played by blowing air through almost-closed lips, producing a \"buzzing\" sound that starts a standing wave vibration in the air column inside the instrument.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Trumpet",
+    "positive_examples": ["youtu.be/TaBJtSIFxNI?start=230&end=240", "youtu.be/2NY5vr-zuPk?start=30&end=40", "youtu.be/K6m0jA-zqkM?start=20&end=30", "youtu.be/jzlD88TWgAY?start=30&end=40", "youtu.be/eiVonYZuzUc?start=30&end=40", "youtu.be/njmeO5JDRAI?start=150&end=160"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07c6l",
+    "name": "Trombone",
+    "description": "The sound of a brass instrument that includes a telescoping slide mechanism that varies the length of the instrument to change the pitch.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Trombone",
+    "positive_examples": ["youtu.be/o6Lm-qQZM-w?start=30&end=40", "youtu.be/2DiNEVtvTlM?start=10&end=20", "youtu.be/TNG8t6gCDRI?start=440&end=450", "youtu.be/cTAZpiMmQ7E?start=40&end=50", "youtu.be/EU4RunterMg?start=110&end=120", "youtu.be/-3OxjnEhi3A?start=15&end=25"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/020w2",
+    "name": "Cornet",
+    "description": "The sound of a brass instrument distinguished from a trumpet by its conical bore, more compact shape, and mellower tone quality.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cornet",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0y64j",
+    "name": "Bugle",
+    "description": "The sound of a simple brass instrument with no valves or other pitch-altering devices. All pitch control is done by varying the player's embouchure.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bugle",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0l14_3",
+    "name": "Bowed string instrument",
+    "description": "Sounds of the subcategory of string instruments that are usually played by a bow rubbing the strings.  Examples may include other playing techniques for these instruments, such as plucking.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bowed_string_instrument",
+    "positive_examples": ["youtu.be/VicqlR2dxTQ?start=20&end=30", "youtu.be/RK7KFZ9SWOc?start=30&end=40", "youtu.be/ucZ5P4EvFe0?start=140&end=150", "youtu.be/Pk5X4JnfT8o?start=220&end=230", "youtu.be/XxhwXQcX58Y?start=60&end=70", "youtu.be/SyXlIXHKfes?start=510&end=520"],
+    "child_ids": ["/m/02qmj0d", "/m/07y_7", "/m/01xqw", "/m/02fsn"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02qmj0d",
+    "name": "String section",
+    "description": "The sound of a group of string instruments typically present in a standard classical orchestra.",
+    "citation_uri": "http://en.wikipedia.org/wiki/String_section",
+    "positive_examples": ["youtu.be/59bu7JPOqR8?start=80&end=90", "youtu.be/rBOkr_DAlK4?start=500&end=510", "youtu.be/xKmDVsO2uSw?start=10&end=20", "youtu.be/ich_-wya6Cs?start=60&end=70", "youtu.be/SrQRhZVLFI0?start=530&end=540"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07y_7",
+    "name": "Violin, fiddle",
+    "description": "The sound of a wooden string instrument, typically with four strings tuned in perfect fifths, that is most commonly played by drawing a bow across its strings, though it can also be played by plucking the strings.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Violin",
+    "positive_examples": ["youtu.be/5HLDUExzhYU?start=30&end=40", "youtu.be/DY9Xm0boaeA?start=30&end=40", "youtu.be/qTeVf7bOztU?start=30&end=40", "youtu.be/lzp88JPSpJE?start=130&end=140", "youtu.be/-fFHHJmhnuM?start=10&end=20", "youtu.be/QJPNBp9eI5M?start=80&end=90", "youtu.be/9a572z81TIw?start=30&end=40", "youtu.be/OiEPSWBQMl0?start=30&end=40", "youtu.be/JyiVnMB8Z1A?start=30&end=40", "youtu.be/2KffWn62wZ4?start=6&end=16"],
+    "child_ids": ["/m/0d8_n"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0d8_n",
+    "name": "Pizzicato",
+    "description": "The sound of playing a stringed instrument that is usually bowed (such as a violin) by plucking the strings with the fingers.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Pizzicato",
+    "positive_examples": ["youtu.be/6DMtphlHzTM?start=30&end=40", "youtu.be/6cVpV4lX3wE?start=30&end=40", "youtu.be/8Wsmo4nUcUE?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01xqw",
+    "name": "Cello",
+    "description": "The sound of a larger, lower-pitched bowed string instrument with four strings tuned in perfect fifths, usually C2, G2, D3, and A3.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cello",
+    "positive_examples": ["youtu.be/4Atbvyzcyms?start=30&end=40", "youtu.be/ekDtSo-QQmo?start=60&end=70", "youtu.be/iu6qTrNQaro?start=240&end=250", "youtu.be/jIPgZAc_GZQ?start=30&end=40", "youtu.be/EayN_Jj0740?start=40&end=50", "youtu.be/CEeX04qZg4Q?start=120&end=130", "youtu.be/u-qDCzZk6a8?start=60&end=70", "youtu.be/5e7zBZTv6Bo?start=540&end=550"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02fsn",
+    "name": "Double bass",
+    "description": "The sound of a large, bowed string instrument, the lowest-pitched in a standard symphony orchestra, with strings usually tuned to E1, A1, D2, and G2.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Double_bass",
+    "positive_examples": ["youtu.be/0MzKqnXHNW8?start=220&end=230", "youtu.be/X7u0UeMNg5c?start=20&end=30", "youtu.be/QvRueweYq6w?start=150&end=160", "youtu.be/Hg2v0Wb8WV4?start=60&end=70", "youtu.be/1xrK5P_fSBA?start=40&end=50", "youtu.be/6yZ67KvDFX8?start=30&end=40", "youtu.be/nhp2HwPoZRw?start=550&end=560"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/085jw",
+    "name": "Wind instrument, woodwind instrument",
+    "description": "Sounds of a family of musical instruments in which a column of air within a resonator is set into vibration by the player blowing into a mouthpiece set at the end of the resonator.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Wind_instrument",
+    "positive_examples": ["youtu.be/P8Ep-MUeZpE?start=30&end=40", "youtu.be/4vKah6NGacI?start=40&end=50", "youtu.be/xEJKVm-XlTI?start=140&end=150", "youtu.be/ko0_jYVXOjw?start=10&end=20", "youtu.be/Mjf34K-cGf0?start=50&end=60", "youtu.be/DVWoxLvpHH4?start=190&end=200", "youtu.be/dfUZdxXl_kU?start=570&end=580"],
+    "child_ids": ["/m/0l14j_", "/m/06ncr", "/m/01wy6", "/m/05kms", "/m/01c3q"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0l14j_",
+    "name": "Flute",
+    "description": "The sound of an aerophone or reedless wind instrument that produces its sound from the flow of air across an opening.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Flute",
+    "positive_examples": ["youtu.be/tF0u90ESFIs?start=30&end=40", "youtu.be/-oOzwEopvdY?start=80&end=90", "youtu.be/oXK4afYJ-ko?start=30&end=40", "youtu.be/xuEwpyrAE40?start=170&end=180", "youtu.be/14Ki89E_S_8?start=120&end=130", "youtu.be/-8ozvTgx--E?start=30&end=40", "youtu.be/sapHfiXGCfY?start=110&end=120"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06ncr",
+    "name": "Saxophone",
+    "description": "The sound of a woodwind instrument made of brass and played with a single-reed mouthpiece similar to that of the clarinet.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Saxophone",
+    "positive_examples": ["youtu.be/wq5wg0L-KF4?start=50&end=60", "youtu.be/jZ-guxYSD2E?start=320&end=330", "youtu.be/5h40xBO4cSM?start=45&end=55", "youtu.be/VBLMzXqcjeA?start=160&end=170", "youtu.be/VDUb4wHGDBE?start=40&end=50", "youtu.be/EtQeywjkRqI?start=60&end=70"],
+    "child_ids": ["/m/02pprs", "/m/03t22m"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02pprs",
+    "name": "Alto saxophone",
+    "description": "The sound of the most common member of the saxophone family covering a mid-range of pitches.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Alto_saxophone",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/03t22m",
+    "name": "Soprano saxophone",
+    "description": "The sound of a higher-register variety of the saxophone, popular as a lead instrument in jazz.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Soprano_saxophone",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/01wy6",
+    "name": "Clarinet",
+    "description": "The sound of a woodwind instrument consisting of a single-reed mouthpiece, a straight cylindrical tube with an almost cylindrical bore, and a flared bell.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Clarinet",
+    "positive_examples": ["youtu.be/fL1dLazpseU?start=10&end=20", "youtu.be/1qdxACwrgl0?start=150&end=160", "youtu.be/2dUAk6Ml4O0?start=40&end=50", "youtu.be/AHlMvXkziEY?start=30&end=40", "youtu.be/KTePg_avLAE?start=480&end=490", "youtu.be/Q4KNKaFsyCs?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05kms",
+    "name": "Oboe",
+    "description": "The sounds of straight-bored double-reed woodwind instruments.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Oboe",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01c3q",
+    "name": "Bassoon",
+    "description": "The sound of the low-pitched double-reed woodwind instrument with a folded bore.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Oboe",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03m5k",
+    "name": "Harp",
+    "description": "The sound of a stringed musical instrument with a number of individual strings, plucked with the fingers, running at an angle to its soundboard.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Harp",
+    "positive_examples": ["youtu.be/KVveqUp3QJk?start=190&end=200", "youtu.be/2htboubCq14?start=50&end=60", "youtu.be/GU8khdLxccg?start=30&end=40", "youtu.be/RhdGQ6vyLBg?start=80&end=90", "youtu.be/op8pav9qypA?start=70&end=80", "youtu.be/M88ZrlaX0Xs?start=320&end=330", "youtu.be/JCGhzN11lAw?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0395lw",
+    "name": "Bell",
+    "description": "The sound of a simple instrument usually consisting of metal cast in the shape of a hollow cup, whose sides form a resonator which vibrates in a single tone upon being struck by a \"clapper\" suspended within, or by a separate mallet or hammer.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bell",
+    "positive_examples": ["youtu.be/e-MkVbRmlIo?start=80&end=90", "youtu.be/hTb_hLSPH3w?start=200&end=210", "youtu.be/7WoxYO6rWLo?start=430&end=440", "youtu.be/btFRBcWGlbU?start=550&end=560", "youtu.be/tYZLPFuzNIs?start=20&end=30", "youtu.be/Qklbd5OLmac?start=60&end=70", "youtu.be/8Jp638z8SEs?start=30&end=40", "youtu.be/u3doJa_O5p8?start=30&end=40", "youtu.be/AlSWSI50R7U?start=60&end=70"],
+    "child_ids": ["/m/03w41f", "/m/0239kh", "/m/027m70_", "/m/0gy1t2s", "/m/07n_g", "/m/0f8s22", "/m/0150b9"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03w41f",
+    "name": "Church bell",
+    "description": "The sound of a large bell usually encountered in churches where it used either to signify the hour or the time for worshippers to go to church.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Church_bell",
+    "positive_examples": ["youtu.be/CwhbaRYl3kQ?start=180&end=190", "youtu.be/8c_pb6dimmU?start=180&end=190", "youtu.be/hTb_hLSPH3w?start=200&end=210", "youtu.be/ySKvlZdECBI?start=30&end=40", "youtu.be/xDFzNhcSDCU?start=30&end=40", "youtu.be/whFx67_zhFw?start=100&end=110", "youtu.be/YL_yzbTuiic?start=10&end=20", "youtu.be/qMZ1nj4fDas?start=290&end=300", "youtu.be/ITFzMwD9Q64?start=150&end=160"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/027m70_",
+    "name": "Jingle bell",
+    "description": "The sound of a type of bell which produces a distinctive 'jingle' sound, especially in large numbers. They are commonly produced from a single piece of sheet metal bent into a roughly spherical shape containing a small ball bearing.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Jingle_bell",
+    "positive_examples": ["youtu.be/m4ysMjnrTnQ?start=10&end=20", "youtu.be/TWQXP_v8opY?start=260&end=270", "youtu.be/VY9hzBD-Sh4?start=100&end=110", "youtu.be/dl793c9RCJY?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0gy1t2s",
+    "name": "Bicycle bell",
+    "description": "The sound of a percussive signaling instrument mounted on a bicycle for warning pedestrians and other cyclists.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bicycle_bell",
+    "positive_examples": ["youtu.be/LK8j0Q4UU4g?start=10&end=20", "youtu.be/s0F2kzW8quU?start=160&end=170", "youtu.be/k7oGk-ozhKI?start=30&end=40", "youtu.be/kTkG_z_GWFs?start=18&end=28", "youtu.be/OY-jfOrL-_A?start=20&end=30", "youtu.be/vSPaTX3nq5A?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07n_g",
+    "name": "Tuning fork",
+    "description": "The sound of an acoustic resonator in the form of a two-pronged fork with the prongs formed from a U-shaped bar of elastic metal. It emits a pure musical tone and is frequently used as a standard of pitch to tune musical instruments.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Tuning_fork",
+    "positive_examples": ["youtu.be/A96UdAiDxfI?start=30&end=40", "youtu.be/NxPqGv1MYh4?start=180&end=190", "youtu.be/s7sRKH_EdAY?start=60&end=70", "youtu.be/rlSvS7InhjE?start=30&end=40", "youtu.be/X1iK3Un7bbI?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0f8s22",
+    "name": "Chime",
+    "description": "The sound of a musical instrument consisting of multiple tuned bells, usually rung by an automated mechanism to produce a short, characteristic tone or melody.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Chime_(bell_instrument)",
+    "positive_examples": ["youtu.be/2cJw4p0NzL8?start=30&end=40", "youtu.be/-OIgmZ_M7Co?start=60&end=70", "youtu.be/JO3yqua94PM?start=17&end=27", "youtu.be/B4WnT62BRog?start=500&end=510", "youtu.be/wiYHKu0-9XM?start=170&end=180", "youtu.be/ofNRyTtPZ8I?start=10&end=20", "youtu.be/So5SUEh2bZc?start=100&end=110", "youtu.be/m9qHnNaAskw?start=20&end=30", "youtu.be/_RbYie-Fxo4?start=60&end=70", "youtu.be/caVRLI71CAA?start=25&end=35", "youtu.be/ZpZsTWwUCSY?start=3&end=13"],
+    "child_ids": ["/m/026fgl"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/026fgl",
+    "name": "Wind chime",
+    "description": "The sound of an instrument constructed from suspended tubes, rods, bells, or other objects that are often made of metal or wood along with some type of weight the tubes or rods can strike when they or another wind-catching surface are blown by the natural movement of air outside.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Wind_chime",
+    "positive_examples": ["youtu.be/1zmAwtZgohE?start=170&end=180", "youtu.be/3aR0vdDSuAA?start=0&end=10", "youtu.be/2xzSvnP5LHU?start=10&end=20", "youtu.be/LhXxwS30-es?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0150b9",
+    "name": "Change ringing (campanology)",
+    "description": "Sounds of the art of ringing a set of (typically large) tuned bells in a controlled manner to produce variations in their sounding order.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Change_ringing",
+    "positive_examples": ["youtu.be/OP1OQKL0LJc?start=280&end=290", "youtu.be/NmKVkgXB64g?start=280&end=290", "youtu.be/2_Ea3T14HNA?start=130&end=140", "youtu.be/vaMn20oJ4Bc?start=10&end=20", "youtu.be/MJI_9fDsX3I?start=40&end=50", "youtu.be/OMMjjf5O1gY?start=240&end=250", "youtu.be/KHapBfftSoE?start=70&end=80", "youtu.be/gKEIFL2uFgU?start=30&end=40", "youtu.be/DhEiv81k5BI?start=180&end=190"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03qjg",
+    "name": "Harmonica",
+    "description": "The sound of a wind instrument played by using the mouth to direct air into or out of one or more holes along a mouthpiece. Behind each hole is a chamber containing at least one reed, producing a specific note or notes.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Harmonica",
+    "positive_examples": ["youtu.be/079QG8nZA7k?start=110&end=120", "youtu.be/yDAkWVjjJFo?start=200&end=210", "youtu.be/gM0V0aomTyA?start=20&end=30", "youtu.be/pbGa3ut9s24?start=60&end=70", "youtu.be/IRCpKYdBrwo?start=120&end=130", "youtu.be/ybpj_cvRPII?start=30&end=40", "youtu.be/edPpQ4A1TY4?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0mkg",
+    "name": "Accordion",
+    "description": "The sound of a family of box-shaped bellows-driven musical instruments played by pressing buttons or keys which allow air to flow across strips of brass or steel, called reeds, that vibrate to produce sound inside the body.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Accordion",
+    "positive_examples": ["youtu.be/WXCy_B98FoI?start=210&end=220", "youtu.be/_NUdDndH7kw?start=140&end=150", "youtu.be/MNAPqNAJLRk?start=30&end=40", "youtu.be/1UmPZEeakuQ?start=110&end=120", "youtu.be/JzgMUjrm4HQ?start=100&end=110", "youtu.be/i5LHakiuDAM?start=131&end=141", "youtu.be/KNJCUmcwLYY?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0192l",
+    "name": "Bagpipes",
+    "description": "The sound of a wind instrument using enclosed reeds fed from a constant reservoir of air in the form of a bag.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bagpipes",
+    "positive_examples": ["youtu.be/vFpiDoOZc8Y?start=30&end=40", "youtu.be/GKbldfNmkZ8?start=120&end=130", "youtu.be/s6K8qalzgI8?start=30&end=40", "youtu.be/uUoEB3DBSjo?start=30&end=40", "youtu.be/eFzPYy6IWq4?start=100&end=110", "youtu.be/xyvS_KsEJC0?start=60&end=70", "youtu.be/oGeklgrvf2g?start=180&end=190"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02bxd",
+    "name": "Didgeridoo",
+    "description": "The sound of an Indigenous Australian wind instrument, usually cylindrical or conical, measuring anywhere from 1 to 3 m long.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Didgeridoo",
+    "positive_examples": ["youtu.be/xqdv0dHk8sM?start=50&end=60", "youtu.be/d2jVpLHIDYA?start=400&end=410", "youtu.be/dimAXdB5M4A?start=30&end=40", "youtu.be/_LbQtA860Ys?start=30&end=40", "youtu.be/ZYcHl5hSG0c?start=80&end=90", "youtu.be/ELLJd_c3cG8?start=100&end=110", "youtu.be/GD89xqFvx9I?start=30&end=40", "youtu.be/6AnnPCJJ8dM?start=80&end=90", "youtu.be/NHz8UGzTMAY?start=120&end=130"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0l14l2",
+    "name": "Shofar",
+    "description": "The sound of an ancient musical horn made of ram's horn, used for Jewish religious purposes.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Shofar",
+    "positive_examples": ["youtu.be/PmiLDro91gk?start=570&end=580", "youtu.be/ZzB115GeM6M?start=70&end=80", "youtu.be/x6f0yu_JzsE?start=40&end=50", "youtu.be/pq9irpvQhMk?start=4&end=14"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07kc_",
+    "name": "Theremin",
+    "description": "The sound of an early electronic musical instrument controlled without physical contact via two metal antennas that sense the relative position of the player's hands and control oscillators for frequency with one hand, and amplitude with the other.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Theremin",
+    "positive_examples": ["youtu.be/W8iIOvGNNcE?start=100&end=110", "youtu.be/y_MbC4fVy2g?start=80&end=90", "youtu.be/8bakI0ITCqQ?start=580&end=590", "youtu.be/5DUdq5JPUsQ?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0l14t7",
+    "name": "Singing bowl",
+    "description": "The sound of a type of bell that sits with the bottom surface resting, allowing the rim to vibrate to produce sound.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Singing_bowl",
+    "positive_examples": ["youtu.be/Y2MwHholr3c?start=340&end=350", "youtu.be/Q3FWUtPD08o?start=240&end=250", "youtu.be/jGIWR_k1Yt4?start=400&end=410", "youtu.be/ToQqkcyH21U?start=30&end=40", "youtu.be/t3Ufg50eARI?start=290&end=300"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05229",
+    "name": "Musical ensemble",
+    "description": "The sound of a group of people who perform instrumental and/or vocal music.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Musical_ensemble",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/01vj9c",
+    "name": "Bass (instrument role)",
+    "description": "Sounds of musical instruments that produce tones in the low-pitched range, typically providing a tonic root in a musical ensemble.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bass_(instrument)",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/01hgjl",
+    "name": "Scratching (performance technique)",
+    "description": "The sound of a technique of moving a vinyl record back and forth on a turntable while optionally manipulating the crossfader on a DJ mixer.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Scratching",
+    "positive_examples": ["youtu.be/Gt1DQkzcDCk?start=90&end=100", "youtu.be/Iue-KvTNGRY?start=30&end=40", "youtu.be/inTLqCdltCc?start=60&end=70", "youtu.be/8zf62sLj0IM?start=140&end=150", "youtu.be/ZkVC4Iw3YDE?start=590&end=600", "youtu.be/crgM97w4fM4?start=490&end=500", "youtu.be/SI7uLBg7HIk?start=230&end=240", "youtu.be/xU1dkNbkRkU?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0kpv1t",
+    "name": "Music genre",
+    "description": "Portmanteau class holding categories that represent styles or classifications of music, useful in identifying and organizing similar musical artists or recordings.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/064t9", "/m/0glt670", "/m/06by7", "/m/06j6l", "/m/0gywn", "/m/06cqb", "/m/01lyv", "/m/02x8m", "/m/02w4v", "/m/06j64v", "/m/03_d0", "/m/026z9", "/m/0ggq0m", "/m/02lkt", "/m/0g293", "/m/0155w", "/m/05fw6t", "/m/02v2lh", "/m/0y4f8", "/m/0164x2", "/m/02mscn", "/m/028sqc", "/m/06rqw", "/m/02p0sh1", "/m/05rwpb"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/064t9",
+    "name": "Pop music",
+    "description": "A genre of popular music that originated in the West during the 1950s and 1960s. Pop music is eclectic, often borrowing elements from urban, dance, rock, Latin, country, and other styles. Songs are typically short to medium-length with repeated choruses, melodic tunes, and hooks.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Pop_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0glt670",
+    "name": "Hip hop music",
+    "description": "Hip hop or rap music formed in the United States in the 1970s and consists of stylized rhythmic music that commonly accompanies rhythmic and rhyming speech (\"rapping\").",
+    "citation_uri": "http://en.wikipedia.org/wiki/Hip_hop_music",
+    "positive_examples": [],
+    "child_ids": ["/m/04j_h4", "/m/0n8zsc8", "/m/02cz_7"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04j_h4",
+    "name": "Grime music",
+    "description": "A genre of music that emerged in East London in the early 2000s as a development of UK garage and jungle.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Grime_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0n8zsc8",
+    "name": "Trap music",
+    "description": "A music genre that originated from hip hop in the early 1990s in the Southern United States, typified by its aggressive lyrical content and sound.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Trap_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/02cz_7",
+    "name": "Beatboxing",
+    "description": "A form of vocal percussion primarily involving the art of mimicking drum machines using one's mouth, lips, tongue, and voice.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Beatboxing",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06by7",
+    "name": "Rock music",
+    "description": "A genre of popular music that originated as \"rock and roll\" in the United States in the 1950s, and developed into a range of different styles in the 1960s and later. Compared to pop music, rock places a higher degree of emphasis on musicianship, live performance, and an ideology of authenticity.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Rock_music",
+    "positive_examples": [],
+    "child_ids": ["/m/03lty", "/m/05r6t", "/m/0dls3", "/m/0dl5d", "/m/07sbbz2", "/m/05w3f"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03lty",
+    "name": "Heavy metal",
+    "description": "A genre of rock music that developed in the late 1960s and early 1970s, consisting of a thick, massive sound, characterized by highly amplified distortion, extended guitar solos, emphatic beats, and overall loudness.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Heavy_metal_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05r6t",
+    "name": "Punk rock",
+    "description": "A rock music genre that developed between 1974 and 1976 typically composed of short or fast-paced songs, with hard-edged melodies and singing styles, stripped-down instrumentation, and often political, anti-establishment lyrics.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Punk_rock",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0dls3",
+    "name": "Grunge",
+    "description": "A subgenre of alternative rock that emerged during the mid-1980s fusing elements of punk rock and heavy metal, such as distorted electric guitars. Lyrics are typically angst-filled, addressing themes such as social alienation, apathy, confinement, and a desire for freedom.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Grunge",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0dl5d",
+    "name": "Progressive rock",
+    "description": "A rock music subgenre that developed in the late 1960s as an attempt to give greater artistic credibility to rock music. Songs were replaced by musical suites that often stretched to 20 or 40 minutes in length and contained symphonic influences, extended musical themes, fantasy-like ambience and lyrics, and complex orchestrations.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Progressive_rock",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07sbbz2",
+    "name": "Rock and roll",
+    "description": "A genre of popular music that originated and evolved in the United States during the late 1940s and early 1950s, from a combination of African-American genres such as blues, boogie-woogie, jump blues, jazz, and gospel music, together with Western swing and country music.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Rock_and_roll",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05w3f",
+    "name": "Psychedelic rock",
+    "description": "A style of rock music influenced by psychedelic culture and attempts to replicate and enhance the mind-altering experiences of psychedelic drugs, most notably LSD. It often uses new recording techniques and effects and sometimes draws on sources such as the ragas and drones of Indian music.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Psychedelic_rock",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06j6l",
+    "name": "Rhythm and blues",
+    "description": "A genre of popular African-American music that originated in the 1940s as urbane, rocking, jazz based music with a heavy, insistent beat. Lyrics focus heavily on the themes of triumphs and failures in terms of relationships, freedom, economics, aspirations, and sex.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Rhythm_and_blues",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0gywn",
+    "name": "Soul music",
+    "description": "A popular music genre that combines elements of African-American gospel music, rhythm and blues and jazz.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Soul_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06cqb",
+    "name": "Reggae",
+    "description": "A music genre that originated in Jamaica in the late 1960s, strongly influenced by traditional mento as well as American jazz and rhythm and blues, instantly recognizable from the counterpoint between the bass and drum downbeat, and the offbeat rhythm section.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Reggae",
+    "positive_examples": [],
+    "child_ids": ["/m/0190y4"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0190y4",
+    "name": "Dub",
+    "description": "A genre of music that grew out of reggae, consisting predominantly of instrumental remixes of existing recordings achieved by significantly manipulating and reshaping the recordings, usually by removing the vocals from an existing music piece, and emphasizing the drum and bass parts.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Dub_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/01lyv",
+    "name": "Country",
+    "description": "A genre of United States popular music with origins in folk, Blues and Western music, often consisting of ballads and dance tunes with generally simple forms and harmonies accompanied by mostly string instruments such as banjos, electric and acoustic guitars, dobros, and fiddles as well as harmonicas.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Country_music",
+    "positive_examples": [],
+    "child_ids": ["/m/015y_n", "/m/0gg8l"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/015y_n",
+    "name": "Swing music",
+    "description": "A form of American music that dominated in the 1930s and 1940s, using a strong rhythm section of double bass and drums as the anchor, a lead section of brass, woodwind, and sometimes stringed instruments, medium to fast tempos, and a \"lilting\" swing time rhythm.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Swing_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0gg8l",
+    "name": "Bluegrass",
+    "description": "A form of American roots music from the Appalachias with mixed roots in Irish, Scottish, Welsh, and English traditional music, later influenced by the music of African-Americans through incorporation of jazz elements.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bluegrass_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02x8m",
+    "name": "Funk",
+    "description": "A music genre that originated in the 1960s when African American musicians created a rhythmic, danceable new form of music that de-emphasized melody and chord progressions to bring a strong rhythmic groove of a bass line and drum part to the foreground.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Funk",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02w4v",
+    "name": "Folk music",
+    "description": "A genre that evolved from traditional music during the 20th century folk revival. One meaning often given is that of old songs with no known composers; another is music that has been transmitted and evolved by a process of oral transmission or performed by custom over a long period of time.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Folk_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06j64v",
+    "name": "Middle Eastern music",
+    "description": "Music originating from the vast region from Morocco to Iran, including the Arabic countries of the Middle East and North Africa, the Iraqi traditions of Mesopotamia, Iranian traditions of Persia, the Hebrew music of Israel, Armenian music, the varied traditions of Cypriot music, the music of Turkey, traditional Assyrian music, Berbers of North Africa, and Coptic Christians in Egypt.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Middle_Eastern_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03_d0",
+    "name": "Jazz",
+    "description": "A music genre that originated from African American communities of New Orleans during the late 19th and early 20th centuries in the form of independent traditional and popular musical styles, all linked by the common bonds of African American and European American musical parentage with a performance orientation.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Jazz",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/026z9",
+    "name": "Disco",
+    "description": "A genre of dance music containing elements of funk, soul, pop, and salsa that achieved popularity during the mid-1970s to the early 1980s.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Disco",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0ggq0m",
+    "name": "Classical music",
+    "description": "Art music produced or rooted in the traditions of Western music, including both liturgical and secular music, over the broad span of time from roughly the 11th century to the present day.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Classical_music",
+    "positive_examples": [],
+    "child_ids": ["/m/05lls"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05lls",
+    "name": "Opera",
+    "description": "An art form in which singers and musicians perform a dramatic work combining text and musical score, usually in a theatrical setting.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Opera",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02lkt",
+    "name": "Electronic music",
+    "description": "A large set of predominantly popular and dance genres in which synthesizers and other electronic instruments are the primary sources of sound.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/03mb9", "/m/07gxw", "/m/07s72n", "/m/029h7y", "/m/0283d", "/m/0m0jc", "/m/08cyft", "/m/0fd3y", "/m/07lnk", "/m/0m0fw", "/m/0bmfpc"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03mb9",
+    "name": "House music",
+    "description": "A genre of electronic dance music originating in Chicago in the early 1980s which is generally dance-based music characterized by repetitive 4/4 beats, rhythms mainly provided by drum machines, off-beat hi-hat cymbals, and synthesized basslines.",
+    "citation_uri": "http://en.wikipedia.org/wiki/House_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07gxw",
+    "name": "Techno",
+    "description": "A form of electronic dance music that emerged in Detroit during the mid-to-late 1980s, resulting from the melding of African American music including with electronic music by artists such as Kraftwerk, Giorgio Moroder, and Yellow Magic Orchestra.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Techno",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07s72n",
+    "name": "Dubstep",
+    "description": "A genre of electronic dance music that originated in South London in the late 1990s which generally features sparse, syncopated drum and percussion patterns with bass lines that contain prominent sub bass frequencies.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Dubstep",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/029h7y",
+    "name": "Electro",
+    "description": "A genre of electronic music and early hip hop influenced by funk and German and Japanese electropop which typically features drum machines and heavy electronic sounds, usually without vocals. If vocals are present they are delivered in a deadpan manner, often through electronic distortion such as vocoding and talkboxing.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Electro_(music)",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0283d",
+    "name": "Drum and bass",
+    "description": "A genre of electronic music that emerged from rave and oldschool jungle scenes in England during the early 1990s characterized by fast, syncopated breakbeats with heavy bass and sub-bass lines, sampled sources, and synthesizers.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Drum_and_bass",
+    "positive_examples": [],
+    "child_ids": ["/m/01f9gb"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01f9gb",
+    "name": "Oldschool jungle",
+    "description": "A genre of electronic music that developed in England in the early 1990s characterized by fast tempos, relatively slow and lyrical reggae-derived basslines, breakbeats, and heavily syncopated percussive loops, samples, and synthesized effects.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Oldschool_jungle",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0m0jc",
+    "name": "Electronica",
+    "description": "An umbrella term that encompasses a broad group of electronic-based styles such as techno, house, ambient, drum and bass, jungle, and industrial dance, among others.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Electronica",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/08cyft",
+    "name": "Electronic dance music",
+    "description": "A broad range of percussive electronic music genres including techno, house, trance, drum and bass, dubstep, and Jersey club produced largely for nightclubs, raves, and festivals, or by disc jockeys in the context of a live mix.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Electronic_dance_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0fd3y",
+    "name": "Ambient music",
+    "description": "A genre of music that developed in England in the 1970s from experimental and synthesizer-oriented styles which puts an emphasis on tone and atmosphere over traditional musical structure or rhythm.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Ambient_music",
+    "positive_examples": [],
+    "child_ids": ["/m/052smk"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/052smk",
+    "name": "Drone music",
+    "description": "A minimalist genre of music that emphasizes the use of sustained or repeated sounds, notes, or tone-clusters with relatively slight harmonic variations.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Drone_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/07lnk",
+    "name": "Trance music",
+    "description": "A genre of electronic dance music that developed in Germany during the 1990s characterized by a tempo between 125 and 150 beats per minute, repeating melodic phrases, and a musical form that distinctly builds tension throughout a track by mixing layers with distinctly foreshadowed build-up and release.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Trance_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0m0fw",
+    "name": "Noise music",
+    "description": "A genre of music that challenges the distinction between musical and non-musical sound with the expressive use of acoustically or electronically generated noise.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Noise_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0bmfpc",
+    "name": "UK garage",
+    "description": "A genre of electronic music from England in the early 1990s that featuress a tempo around 130 beats per minute with a distinctive 4/4 percussive rhythm, syncopated hi-hats, cymbals, and snares, and occasionally beat-skipping kick drums and altered vocal samples.",
+    "citation_uri": "http://en.wikipedia.org/wiki/UK_garage",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0g293",
+    "name": "Music of Latin America",
+    "description": "Music originating from Latin America which encompasses a wide variety of styles, including son, rumba, salsa, merengue, tango, samba, and bossa nova.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Music_of_Latin_America",
+    "positive_examples": [],
+    "child_ids": ["/m/02ccj9", "/m/0ln16", "/m/0kpck", "/m/080nby", "/m/05q7ms", "/m/0326g"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02ccj9",
+    "name": "Cumbia",
+    "description": "A dance-oriented music genre popular throughout Latin America which began as a courtship dance practiced among the African population on the Caribbean coasts of Colombia and Panama but later mixed with Amerindian and European instruments, steps, and musical characteristics.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cumbia",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0ln16",
+    "name": "Salsa music",
+    "description": "A genre of music that is based largely on Cuban, Puerto Rican, and Dominican popular dance music, occasionally incorporating elements of rock, R&B, and funk.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Salsa_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0kpck",
+    "name": "Soca music",
+    "description": "A genre of Caribbean music that originated in Trinidad and Tobago in the late 1970s as an offshoot of kaiso and calypso, with influences from cadence, funk, and soul.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Soca_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/080nby",
+    "name": "Kuduro",
+    "description": "A type of music and dance developed in Angola in the 1980s sampled from traditional Caribbean carnival music and Angolan semba around a fast, energetic 4/4 beat.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Kuduro",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/05q7ms",
+    "name": "Funk carioca",
+    "description": "A type of dance music originally from Rio de Janeiro derived from Miami bass and African style music, also known as favela funk and baile funk.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Funk_carioca",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0326g",
+    "name": "Flamenco",
+    "description": "A genre originating in Andalusian music and dance styles which includes cante, toque, baile, jaleo, palmas, and pitos.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Flamenco",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0155w",
+    "name": "Blues",
+    "description": "A genre and musical form developed by African Americans in the United States around the end of the 19th century from African-American work songs and European-American folk music. The blues form, ubiquitous in jazz and rock and roll, is characterized by the call-and-response pattern, the blues scale and specific chord progressions, of which the twelve-bar blues is the most common. Blues shuffles or walking bass reinforce the trance-like rhythm and form a repetitive groove effect.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Blues",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05fw6t",
+    "name": "Music for children",
+    "description": "Music performed for children, often designed to provide an entertaining means of teaching about cultures, good behavior, facts, and skills.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Children's_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02v2lh",
+    "name": "New-age music",
+    "description": "A genre of music intended to create artistic inspiration, relaxation, and optimism used by listeners for yoga, massage, meditation, and reading as a method of stress management or to create a peaceful atmosphere. Includes both electronic and acoustic forms.",
+    "citation_uri": "http://en.wikipedia.org/wiki/New-age_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0y4f8",
+    "name": "Vocal music",
+    "description": "Music performed by one or more singers, with or without instrumental accompaniment, in which singing provides the main focus of the piece.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Vocal_music",
+    "positive_examples": [],
+    "child_ids": ["/m/0z9c", "/m/02bk07", "/m/02cz_7"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0z9c",
+    "name": "A capella",
+    "description": "Group or solo singing without instrumental accompaniment.",
+    "citation_uri": "http://en.wikipedia.org/wiki/A_cappella",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0164x2",
+    "name": "Music of Africa",
+    "description": "Music whose style or form clearly indicates African origin or primarily African influence. Given the vastness of the continent, this covers many distinct musical traditions. Sub-Saharan African music frequently relies on percussion instruments including xylophones, drums, and tone-producing instruments such as the mbira or \"thumb piano.\"",
+    "citation_uri": "http://en.wikipedia.org/wiki/Music_of_Africa",
+    "positive_examples": [],
+    "child_ids": ["/m/0145m", "/m/022dgg"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0145m",
+    "name": "Afrobeat",
+    "description": "A combination of traditional Nigerian music, Ghanaian music, jazz, highlife, funk, and chanted vocals, fused with percussion and vocal styles, popularised in Africa in the 1970s.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Afrobeat",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/022dgg",
+    "name": "Kwaito",
+    "description": "A music genre that emerged in South Africa, during the 1990s. It is a variant of house music featuring the use of African sounds and samples.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Kwaito",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/02mscn",
+    "name": "Christian music",
+    "description": "Music that has been written to express either personal or a communal belief regarding Christian life and faith. Its forms vary widely across the world, according to culture and social context.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Christian_music",
+    "positive_examples": [],
+    "child_ids": ["/m/016cjb"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/016cjb",
+    "name": "Gospel music",
+    "description": "A genre of Christian music usually featuring dominant vocals with Christian lyrics. Gospel music is rooted in the black oral tradition, in which hymns and sacred songs were repeated in call and response fashion, with hand clapping and foot stomping as rhythmic accompaniment.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Gospel_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/028sqc",
+    "name": "Music of Asia",
+    "description": "Musical styles originating from a large number of Asian countries located in Central, Southern, and East Asia.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Music_of_Asia",
+    "positive_examples": [],
+    "child_ids": ["/m/015vgc", "/m/0dq0md"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/015vgc",
+    "name": "Carnatic music",
+    "description": "A system of music commonly associated with the southern India, whose main emphasis is on vocal music. Although improvisation plays an important role, Carnatic music is mainly sung through compositions.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Carnatic_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0dq0md",
+    "name": "Music of Bollywood",
+    "description": "Hindi film songs featured in Bollywood films. Bollywood songs, along with dance, are a characteristic motif of Hindi cinema which gives it enduring popular appeal, cultural value, and context.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Music_of_Bollywood",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06rqw",
+    "name": "Ska",
+    "description": "A music genre that originated in Jamaica in the late 1950s, combining elements of Caribbean mento and calypso with American jazz and rhythm and blues. It is characterized by a walking bass line accented with rhythms on the off-beat.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Ska",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02p0sh1",
+    "name": "Traditional music",
+    "description": "Musical forms that have origins many generations into the past, commonly without formal notation or description, commonly familiar to people in a given culture.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05rwpb",
+    "name": "Independent music",
+    "description": "Music produced independent of major commercial record labels, possibly including a do-it-yourself approach to recording and publishing. The term indie is also used to describe music of this style regardless of actual production channel.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Independent_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00027",
+    "name": "Musical concepts",
+    "description": "Portmanteau class for descriptions of music sounds that reflect their abstract music-theoretical properties rather than their physical realizations.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/074ft", "/m/09dsr", "/m/05jcn", "/m/022c7z", "/m/01gp74", "/m/0b128", "/m/021wwz", "/m/0kc2j", "/m/03w6d1"],
+    "restrictions": ["abstract", "blacklist"]
+  },
+  {
+    "id": "/m/074ft",
+    "name": "Song",
+    "description": "A musical work intended to be sung by the human voice with distinct and fixed pitches and patterns using sound and silence and a variety of forms that often include the repetition of sections.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Song",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/09dsr",
+    "name": "Melody",
+    "description": "A linear succession of musical tones that the listener perceives as a single entity; a combination of pitch and rhythm, also known as a tune, voice, or line.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Melody",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/05jcn",
+    "name": "Musical note",
+    "description": "A pitched sound forming the \"atom\" of much written music.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Musical_note",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/022c7z",
+    "name": "Beat",
+    "description": "The basic unit of musical time -- the pulse -- of the mensural level. The beat is often defined as the rhythm listeners would tap their toes to when listening to a piece of music.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Beat_(music)",
+    "positive_examples": [],
+    "child_ids": ["/m/05xp3j"],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/05xp3j",
+    "name": "Drum beat",
+    "description": "A rhythmic pattern establishing the meter and groove through the pulse and subdivision, played on drum kits and other percussion instruments.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Drum_beat",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/01gp74",
+    "name": "Chord",
+    "description": "Any musical set of usually three or more notes that is heard as if sounding simultaneously.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Chord_(music)",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0b128",
+    "name": "Harmony",
+    "description": "The use of simultaneous pitches or chords. Harmony is often said to refer to the \"vertical\" aspect of music, as distinguished from melodic line, or the \"horizontal\" aspect.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Harmony",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/021wwz",
+    "name": "Bassline",
+    "description": "The low-pitched instrumental part or line played by a rhythm section instrument such as the electric bass, double bass, cello, tuba, or keyboard in many forms of popular and other music.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bassline",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0kc2j",
+    "name": "Loop",
+    "description": "A repeating section of sound material, usually in electroacoustical music.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Loop_(music)",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/03w6d1",
+    "name": "Drone",
+    "description": "A harmonic or monophonic effect or accompaniment where a note or chord is continuously sounded throughout most or all of a musical piece.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Drone_(music)",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/t/dd00028",
+    "name": "Music role",
+    "description": "Portmanteau class for categories that describe music according to its functional role. Although the genre and instrumentation of examples of each of these classes may vary widely, a listener will be able to recognize that the music is being used for a common specific purpose as stated in each class definition.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/025td0t", "/m/02cjck", "/m/03r5q_", "/m/0l14gg", "/m/07pkxdp", "/m/01z7dr", "/m/0140xf", "/m/0ggx5q", "/m/04wptg", "/t/dd00029"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/025td0t",
+    "name": "Background music",
+    "description": "Styles of music or soundscapes primarily intended to be listened to passively and not meant to be the main focus of an audience.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Background_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02cjck",
+    "name": "Theme music",
+    "description": "Music often written specifically for a radio program, television program, video game, or movie, and usually played during the intro, opening credits, and/or ending credits.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Theme_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03r5q_",
+    "name": "Jingle (music)",
+    "description": "A short song or tune used in advertising and for other commercial uses. The jingle contains one or more hooks that explicitly promote the product or service being advertised.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Jingle",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0l14gg",
+    "name": "Soundtrack music",
+    "description": "Recorded music accompanying a movie, video, TV show, video game, or the like. Although any music can be used in a soundtrack, this specifically refers to music that suggests its use to accompany images, rather than something that happens to have been used that way.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Soundtrack",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pkxdp",
+    "name": "Lullaby",
+    "description": "The act of singing a quiet song to lull a child to sleep.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=lullaby",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01z7dr",
+    "name": "Video game music",
+    "description": "The soundtrack that accompanies video games. Early video game music was once limited to simple melodies of early sound synthesizer technology; with advances in technology, video game music has now grown to include the same breadth and complexity associated with television and movie soundtracks.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Video_game_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0140xf",
+    "name": "Christmas music",
+    "description": "A variety of genres of music normally performed or heard around the Christmas season.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Christmas_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0ggx5q",
+    "name": "Dance music",
+    "description": "Music composed specifically to facilitate or accompany dancing. It can be either a whole musical piece or part of a larger musical arrangement.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Dance_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04wptg",
+    "name": "Wedding music",
+    "description": "Music played at wedding celebrations, including the ceremony and any festivities before or after the event.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Wedding_music",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00029",
+    "name": "Birthday music",
+    "description": "Music specifically used or performed at birthday celebrations.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00030",
+    "name": "Music mood",
+    "description": "Portmanteau class for music categories that indicate the over emotional affect of music, regardless of genre or instrumentation. These judgments are intrinsically subjective and likely to vary substantially between different musical cultures.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/t/dd00031", "/t/dd00032", "/t/dd00033", "/t/dd00034", "/t/dd00035", "/t/dd00036", "/t/dd00037"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/t/dd00031",
+    "name": "Happy music",
+    "description": "Music that evokes or conveys feelings of happiness.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00032",
+    "name": "Funny music",
+    "description": "Music that evokes or conveys amusement.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00033",
+    "name": "Sad music",
+    "description": "Music that evokes or conveys feelings of sadness.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00034",
+    "name": "Tender music",
+    "description": "Music that evokes or conveys feelings of tenderness.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00035",
+    "name": "Exciting music",
+    "description": "Music that evokes or conveys feelings of excitement.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00036",
+    "name": "Angry music",
+    "description": "Music that evokes or conveys feelings of anger.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00037",
+    "name": "Scary music",
+    "description": "Music that evokes or conveys feelings of fear.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/059j3w",
+    "name": "Natural sounds",
+    "description": "Sounds produced by natural sources in their normal soundscape, excluding animal and human sounds.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Natural_sounds",
+    "positive_examples": [],
+    "child_ids": ["/m/03m9d0z", "/m/0jb2l", "/m/0838f", "/m/02_41"],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/03m9d0z",
+    "name": "Wind",
+    "description": "Sounds caused by the large-scale flow of gases, especially the air flowing over the surface of the Earth. Long-duration winds have various names associated with their average strength, such as breeze, gale, storm, and hurricane.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Wind",
+    "positive_examples": ["youtu.be/JRyhdsQwFXM?start=110&end=120", "youtu.be/-PJrbyYLtS4?start=330&end=340", "youtu.be/dOU3KOnQM2Q?start=200&end=210", "youtu.be/48HQ_eeoygY?start=10&end=20", "youtu.be/HfaFm2c4a78?start=40&end=50", "youtu.be/aqAvJgN6GOE?start=220&end=230", "youtu.be/aN-oXqXdsVM?start=100&end=110", "youtu.be/cpFdPrI-8EQ?start=120&end=130", "youtu.be/U-WqWv0pXwI?start=20&end=30", "youtu.be/urfP_4xhJCE?start=90&end=100"],
+    "child_ids": ["/m/07q8f3b", "/m/09t49", "/t/dd00092"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07q8f3b",
+    "name": "Howl (wind)",
+    "description": "A loud sustained noise caused by wind, resembling the cry of a hound.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=howl",
+    "positive_examples": ["youtu.be/FhEJYUlNEqM?start=260&end=270", "youtu.be/JfzqqDmIwhY?start=30&end=40", "youtu.be/MRnpKEhDQNE?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/09t49",
+    "name": "Rustling leaves",
+    "description": "The sound of dried leaves rubbing against one another in respondse to being moved by the wind or another cause.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Leaf",
+    "positive_examples": ["youtu.be/18aaA2efGng?start=370&end=380", "youtu.be/0Hxth3DK480?start=140&end=150"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00092",
+    "name": "Wind noise (microphone)",
+    "description": "The noise produced when a strong air current passes over a microphone, causing large amplitude local turbulence, normally recorded as mechanical clipping as the microphone element exceeds its limits of linearity.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/LvfGG-k7ZO8?start=250&end=260", "youtu.be/IfvejNeLtno?start=30&end=40", "youtu.be/CTmRRq187y4?start=30&end=40", "youtu.be/GGQDjbHCq-E?start=260&end=270", "youtu.be/VtdAZlFNuTw?start=150&end=160", "youtu.be/10JMr_3UN0g?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0jb2l",
+    "name": "Thunderstorm",
+    "description": "The sound of a storm characterized by the presence of lightning and its acoustic effect on the Earth's atmosphere, known as thunder.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Thunderstorm",
+    "positive_examples": ["youtu.be/9gpdoYeFjoU?start=110&end=120", "youtu.be/zQptvcZ6Q64?start=30&end=40", "youtu.be/IADbYuioZ9s?start=190&end=200", "youtu.be/RllsaWFnyz0?start=10&end=20", "youtu.be/iqy2_Ofk2TQ?start=100&end=110", "youtu.be/AI1OweEW8C0?start=50&end=60", "youtu.be/9TKSDR1HANg?start=280&end=290", "youtu.be/ThUAAmLjUKM?start=20&end=30"],
+    "child_ids": ["/m/0ngt1"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0ngt1",
+    "name": "Thunder",
+    "description": "The sound caused by lightning. Depending on the distance and nature of the lightning, thunder can range from a sharp, loud crack to a long, low rumble.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Thunder",
+    "positive_examples": ["youtu.be/3y2aZEs1F5s?start=80&end=90", "youtu.be/S38pF1kVLYI?start=310&end=320", "youtu.be/cg1A8R7B7B8?start=30&end=40", "youtu.be/k4ggjvnuzbI?start=150&end=160", "youtu.be/Mmml5YKQYIY?start=400&end=410", "youtu.be/NN6kHRAbGeA?start=390&end=400", "youtu.be/JY9VX8KnreU?start=110&end=120", "youtu.be/1lMN9N4DBOc?start=200&end=210", "youtu.be/Jh-upSoOqTc?start=70&end=80"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0838f",
+    "name": "Water",
+    "description": "Sounds caused by motion of liquid water.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Properties_of_water",
+    "positive_examples": ["youtu.be/UDEyewB7-Hg?start=60&end=70", "youtu.be/GOJiiisgi-Q?start=30&end=40", "youtu.be/s0O-mPb6yHE?start=30&end=40", "youtu.be/IZe1BGDPzA8?start=30&end=40", "youtu.be/jy6ZJRjl1No?start=70&end=80", "youtu.be/F0gZgJRxJhA?start=100&end=110", "youtu.be/btD25mb9BRE?start=50&end=60", "youtu.be/U2-7bxSMCzA?start=30&end=40", "youtu.be/Gw0gwDD8cts?start=20&end=30"],
+    "child_ids": ["/m/06mb1", "/m/0j6m2", "/m/0j2kx", "/m/05kq4", "/m/06wzb", "/m/07swgks"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06mb1",
+    "name": "Rain",
+    "description": "The sound of droplets of liquid water that have condensed from atmospheric water vapor and then fallen under gravity.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Rain",
+    "positive_examples": ["youtu.be/5Ehgo2dKD3c?start=260&end=270", "youtu.be/aDViuftS7Wk?start=210&end=220", "youtu.be/nULDV0qOSDw?start=30&end=40", "youtu.be/wyXpYD4E-Lo?start=50&end=60", "youtu.be/QL-GkJ0BP0w?start=90&end=100", "youtu.be/uH3j2cZCzvk?start=80&end=90", "youtu.be/ZriuDmppWfw?start=140&end=150"],
+    "child_ids": ["/m/07r10fb", "/t/dd00038"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r10fb",
+    "name": "Raindrop",
+    "description": "A sound clearly attributable to a single drop of rain.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=raindrop",
+    "positive_examples": ["youtu.be/AOYnd6OzO2U?start=30&end=40", "youtu.be/V_J1Zx1PbFU?start=30&end=40", "youtu.be/doi3DiqyMl0?start=6&end=16", "youtu.be/JFWiNHljGFI?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00038",
+    "name": "Rain on surface",
+    "description": "Steady sound of many rain drops striking a surface such as a roof or window.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/1r0Y4VFXrmE?start=30&end=40", "youtu.be/1C7lFCTvd6U?start=30&end=40", "youtu.be/0j9XJr31TA4?start=24&end=34"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0j6m2",
+    "name": "Stream",
+    "description": "Sounds of a body of water with a current, confined within a bed and banks.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Stream",
+    "positive_examples": ["youtu.be/5Hh3nZGtzaI?start=30&end=40", "youtu.be/r_qcJwjFuM4?start=100&end=110", "youtu.be/rUr2EL0sp7s?start=20&end=30", "youtu.be/12PDR1SiMoY?start=30&end=40", "youtu.be/P2kW_zbZEyc?start=210&end=220", "youtu.be/2YjgcnIKUmc?start=70&end=80"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0j2kx",
+    "name": "Waterfall",
+    "description": "The sound of water flowing over a vertical drop or a series of drops in the course of a stream or river.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Waterfall",
+    "positive_examples": ["youtu.be/P2kW_zbZEyc?start=210&end=220", "youtu.be/0WQ5Xejk0cs?start=30&end=40", "youtu.be/FrHCQ5x2pNQ?start=20&end=30", "youtu.be/D-oU-1zhS-U?start=30&end=40", "youtu.be/E4duB2A-ces?start=50&end=60", "youtu.be/XbigWWtnGL4?start=70&end=80"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05kq4",
+    "name": "Ocean",
+    "description": "Sounds of the body of saline water that composes much of Earth's surface.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Ocean",
+    "positive_examples": ["youtu.be/b1iahVw7phI?start=240&end=250", "youtu.be/bspTVc-6whI?start=70&end=80", "youtu.be/DVqUkCoFwgk?start=530&end=540", "youtu.be/Hi1HVjOqJa8?start=120&end=130", "youtu.be/Y6ft09j8rwI?start=370&end=380", "youtu.be/lQBqdnyzFH8?start=10&end=20", "youtu.be/2lEGN0fx9t4?start=10&end=20"],
+    "child_ids": ["/m/034srq"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/034srq",
+    "name": "Waves, surf",
+    "description": "Sounds caused by the surface waves that occur on the free surface of oceans, seas, lakes, rivers, etc., resulting from the wind blowing over the surface.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Wind_wave",
+    "positive_examples": ["youtu.be/F1acJgs48ug?start=420&end=430", "youtu.be/ciShfkeGGPs?start=140&end=150", "youtu.be/ZVveYlQuMAw?start=30&end=40", "youtu.be/3DhQmxwJ5f0?start=530&end=540", "youtu.be/acCLHAVHOO4?start=80&end=90"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06wzb",
+    "name": "Steam",
+    "description": "Sounds caused by  water in the gas phase, which is formed when water boils.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Steam",
+    "positive_examples": ["youtu.be/AoQcAv9swE4?start=220&end=230", "youtu.be/q73cABJraqg?start=60&end=70", "youtu.be/qgASsbk7Jo0?start=50&end=60", "youtu.be/AEGHk8z6Sbc?start=40&end=50", "youtu.be/UyC5UsOHaN8?start=270&end=280", "youtu.be/QKkSUUsM7kw?start=90&end=100"],
+    "child_ids": ["/m/07rjwbb"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07swgks",
+    "name": "Gurgling",
+    "description": "The bubbling sound of water flowing through a narrow constriction, such as from a bottle with a narrow neck.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=gurgling",
+    "positive_examples": ["youtu.be/ueGrX54zEs4?start=30&end=40", "youtu.be/PlPg7pFN-c0?start=30&end=40", "youtu.be/bN-pEae5Ojk?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02_41",
+    "name": "Fire",
+    "description": "Sounds resulting from  the rapid oxidation of a material in the exothermic chemical process of combustion, releasing heat, light, and various reaction products.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Fire",
+    "positive_examples": ["youtu.be/rRA29fWQ-yo?start=40&end=50", "youtu.be/ncTBfKkL98M?start=10&end=20", "youtu.be/xGzpK8xOJj8?start=220&end=230", "youtu.be/FkW00xIxnMM?start=160&end=170", "youtu.be/JocAxXHMaVw?start=40&end=50"],
+    "child_ids": ["/m/07pzfmf", "/m/0fjy1"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pzfmf",
+    "name": "Crackle",
+    "description": "An irregular sequence of sharp sounds, as from sudden vaporization of liquids trapped in a burning solid, or from a collection of snapping noises.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=crackle",
+    "positive_examples": ["youtu.be/yD8-rFGIX1Y?start=80&end=90", "youtu.be/bbQgr9juJHU?start=200&end=210", "youtu.be/MNQlSUhlaoU?start=130&end=140", "youtu.be/o2ll07zNfvo?start=20&end=30", "youtu.be/eDRs0CPfUT8?start=350&end=360", "youtu.be/J1gpa4iJ-ds?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0fjy1",
+    "name": "Wildfire",
+    "description": "Sounds of an uncontrolled fire in an area of combustible vegetation that occurs in the countryside.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Wildfire",
+    "positive_examples": ["youtu.be/7N-rIXXcb-Q?start=170&end=180", "youtu.be/gM1DIbory6A?start=70&end=80"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00041",
+    "name": "Sounds of things",
+    "description": "Set of sound classes referring to sounds that are immediately understood by listeners as arising from specific objects (rather than being heard more literally as \"sounds\").",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/07yv9", "/m/02mk9", "/t/dd00071", "/m/0395lw", "/m/07pp_mv", "/t/dd00077", "/m/07k1x", "/m/014zdl", "/m/083vt", "/m/039jq", "/m/04k94", "/t/dd00089", "/t/dd00133"],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/07yv9",
+    "name": "Vehicle",
+    "description": "Sounds of mobile machines that transport people or cargo.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Vehicle",
+    "positive_examples": ["youtu.be/Pp-F-z-_yfk?start=160&end=170", "youtu.be/551dHGGa05I?start=10&end=20", "youtu.be/H4993LXvCZ0?start=110&end=120", "youtu.be/e_1B185lSIo?start=40&end=50", "youtu.be/bS647KEfsH4?start=30&end=40", "youtu.be/DvdscEsZh6A?start=70&end=80", "youtu.be/8ycflE3dIHw?start=20&end=30", "youtu.be/BjXjO7fsBT4?start=270&end=280", "youtu.be/f8vk98Ul2yQ?start=180&end=190", "youtu.be/xquV-Ui8cMc?start=260&end=270"],
+    "child_ids": ["/m/019jd", "/m/012f08", "/m/06d_3", "/m/0k5j", "/t/dd00061"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/019jd",
+    "name": "Boat, Water vehicle",
+    "description": "Sounds of watercraft designed to float, plane, work, or travel on water.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Boat",
+    "positive_examples": ["youtu.be/6j1Rp2fqNxI?start=540&end=550", "youtu.be/m55Fx5rDh8g?start=50&end=60", "youtu.be/xISRpYtGzaw?start=260&end=270", "youtu.be/vihk0nkq5Bg?start=80&end=90", "youtu.be/vGPlsl1S4mM?start=260&end=270", "youtu.be/2Uir5X9ZgyM?start=30&end=40", "youtu.be/adjWwiHzQAg?start=430&end=440"],
+    "child_ids": ["/m/0hsrw", "/m/056ks2", "/m/02rlv9", "/m/06q74"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0hsrw",
+    "name": "Sailboat, sailing ship",
+    "description": "Sounds of a boat (large or small) propelled partly or entirely by sails.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sailboat",
+    "positive_examples": ["youtu.be/bhs6VmkT8KI?start=340&end=350", "youtu.be/YcuMAHW6qBQ?start=130&end=140", "youtu.be/CyljecUybZw?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/056ks2",
+    "name": "Rowboat, canoe, kayak",
+    "description": "Sounds of a boat propelled using the motion of oars in the water.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Rowing",
+    "positive_examples": ["youtu.be/hoGzOkPLH1U?start=10&end=20", "youtu.be/hseqZnjc_t0?start=30&end=40", "youtu.be/EAt6jhYn8Nc?start=26&end=36", "youtu.be/nNbI-kSSeTg?start=30&end=40", "youtu.be/Rpo1MaZsBmA?start=170&end=180", "youtu.be/TMHeXKbz8vA?start=30&end=40", "youtu.be/CIN14f0ybzQ?start=360&end=370"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02rlv9",
+    "name": "Motorboat, speedboat",
+    "description": "Sounds of a boat which is powered by an inboard or outboard engine.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Motorboat",
+    "positive_examples": ["youtu.be/PpWc5v7JxoE?start=30&end=40", "youtu.be/3xnZraMY7ug?start=30&end=40", "youtu.be/MdptfcMqSNU?start=110&end=120", "youtu.be/22MGaPGKU58?start=30&end=40", "youtu.be/ljWbztbJyGI?start=30&end=40", "youtu.be/KVCEkvej6jA?start=26&end=36", "youtu.be/6T2wUBeDDl0?start=10&end=20", "youtu.be/A0sa5M5sJjM?start=30&end=40", "youtu.be/1-H5_TcnWNY?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06q74",
+    "name": "Ship",
+    "description": "The sound of a large buoyant watercraft, distinguished from boats based on size, shape, and cargo or passenger capacity.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Ship",
+    "positive_examples": ["youtu.be/q4w9sFyLvps?start=350&end=360", "youtu.be/BW4QjhWFfE0?start=70&end=80", "youtu.be/0xWD_SlWXBM?start=80&end=90", "youtu.be/ILAtgaMVy60?start=30&end=40", "youtu.be/er8zQZ4d0Ew?start=250&end=260"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/012f08",
+    "name": "Motor vehicle (road)",
+    "description": "Sounds of self-propelled land vehicles, usually wheeled, that do not operate on rails. Includes \"off-road\" vehicles designed for unmade roads.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Motor_vehicle",
+    "positive_examples": ["youtu.be/tMPg88c5ciQ?start=160&end=170", "youtu.be/-znLAiE_r_w?start=30&end=40", "youtu.be/2R2qwpgb0Dw?start=30&end=40", "youtu.be/ko91_sThwdo?start=290&end=300", "youtu.be/u8rFWqmbx18?start=240&end=250", "youtu.be/g6o47ksKlpQ?start=70&end=80", "youtu.be/gKKzQNZiymI?start=130&end=140", "youtu.be/f1yc8bkg0sc?start=10&end=20", "youtu.be/B1vvkDwpgLQ?start=30&end=40"],
+    "child_ids": ["/m/0k4j", "/m/07r04", "/m/01bjv", "/m/03j1ly", "/m/04_sv", "/m/0btp2"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0k4j",
+    "name": "Car",
+    "description": "Sounds of a self-powered motor vehicle with usually four wheels used for transportation of one to eight people, designed to run primarily on roads.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Car",
+    "positive_examples": ["youtu.be/EiyEPSJY_cM?start=20&end=30", "youtu.be/dThSTe35jb0?start=250&end=260", "youtu.be/a_35ez_FOY4?start=40&end=50", "youtu.be/S-VtBVNXxHw?start=30&end=40", "youtu.be/qKUVlPkkWNc?start=30&end=40", "youtu.be/TrczACxTtrg?start=270&end=280", "youtu.be/1dOV9NEPc60?start=8&end=18", "youtu.be/717m6D03130?start=100&end=110", "youtu.be/5xOlEfsD0_8?start=14&end=24"],
+    "child_ids": ["/m/0912c9", "/m/02mfyn", "/m/04gxbd", "/m/07rknqz", "/m/0h9mv", "/t/dd00134", "/m/0ltv"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0912c9",
+    "name": "Vehicle horn, car horn, honking",
+    "description": "The sound of a motor vehicle accessory whose purpose is to provide an audible alert of the vehicle's presence.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Vehicle_horn",
+    "positive_examples": ["youtu.be/tlyFVJ7P-po?start=23&end=33", "youtu.be/_waM2-2QnK8?start=30&end=40", "youtu.be/-aYumc8KoXg?start=60&end=70"],
+    "child_ids": ["/m/07qv_d5"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qv_d5",
+    "name": "Toot",
+    "description": "A blast of a horn.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=toot",
+    "positive_examples": ["youtu.be/PrNMIEfwmm4?start=240&end=250", "youtu.be/ikJlmuxCMgo?start=50&end=60", "youtu.be/0SoVB6iEHTU?start=100&end=110", "youtu.be/wN0i4-VxOgc?start=120&end=130", "youtu.be/Mcuclfu6kcg?start=100&end=110", "youtu.be/EYsAX8CaJ-4?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02mfyn",
+    "name": "Car alarm",
+    "description": "The loud sound of an electronic device installed in a vehicle in an attempt to discourage theft of the vehicle or its contents.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Car_alarm",
+    "positive_examples": ["youtu.be/17VuPl9Wxvs?start=20&end=30", "youtu.be/o799nvBLsaQ?start=50&end=60", "youtu.be/VC9nqtFULW4?start=280&end=290", "youtu.be/n8gnTTCrC98?start=40&end=50", "youtu.be/4A1Ar1TIXIY?start=30&end=40", "youtu.be/0ct9AETvIdE?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04gxbd",
+    "name": "Power windows, electric windows",
+    "description": "The sound of automobile windows being raised and lowered by a built-in electric motor, controlled by a button or switch.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Power_window",
+    "positive_examples": ["youtu.be/z-wdnR3D8y4?start=8&end=18", "youtu.be/PKDeI8PzYxk?start=30&end=40", "youtu.be/ta2vGgYNBgg?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rknqz",
+    "name": "Skidding",
+    "description": "The sound of a vehicle sliding on a road surface as a consequence of its wheels losing sufficient frictional contact.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=skidding",
+    "positive_examples": ["youtu.be/q9CaARH_mgI?start=40&end=50", "youtu.be/UtLGcgDmYhI?start=210&end=220", "youtu.be/TWcbU5_9jao?start=150&end=160", "youtu.be/0IUR0a8uR5c?start=30&end=40", "youtu.be/V3CQ5EUog80?start=180&end=190", "youtu.be/22olCB3wQaA?start=40&end=50", "youtu.be/3GHVkqqQZ_k?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0h9mv",
+    "name": "Tire squeal",
+    "description": "The high-pitched sound of a rubber vehicle tire sliding over a road surface when the torque applied to the wheel (to either accelerate or decelerate) exceeds the maximum frictional force that can be supported.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Tire",
+    "positive_examples": ["youtu.be/ZLvD9fHgaUQ?start=20&end=30", "youtu.be/TCudWnNMr0s?start=10&end=20", "youtu.be/UNjIcZaQ9YM?start=400&end=410", "youtu.be/OoJJu9TzPXo?start=150&end=160", "youtu.be/_Jr8Wehn1uo?start=400&end=410", "youtu.be/YOuBSVA8m2k?start=180&end=190"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00134",
+    "name": "Car passing by",
+    "description": "The sound of a motorized vehicle as it passes by a listener close to the vehicle's path. The sound may include engine and tire noise and will typically involve a clear build-up and/or decay of intensity as the vehicle approaches and retreats, as well as possible Doppler shift.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/-5-jLuQ6U_E?start=19&end=29", "youtu.be/NvReVInFNxk?start=30&end=40", "youtu.be/2FyalYzSF6g?start=17&end=27", "youtu.be/31iv4K9G_4E?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0ltv",
+    "name": "Race car, auto racing",
+    "description": "The sound of one or more motor vehicles engaged in a competition to complete a course as quickly as possible. Specialized race cars include many modifications, often making them much louder than common street vehicles.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Auto_racing",
+    "positive_examples": ["youtu.be/VWkQ9L1Uc5M?start=270&end=280", "youtu.be/5BthTpmqpqY?start=580&end=590", "youtu.be/_dQop-gc2hA?start=50&end=60", "youtu.be/MlHCVDr_tAU?start=20&end=30", "youtu.be/bq9EO2TQx8w?start=20&end=30", "youtu.be/H6HLCq8o3KE?start=230&end=240"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r04",
+    "name": "Truck",
+    "description": "Sounds of large motor vehicles designed to transport cargo on roads.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Truck",
+    "positive_examples": ["youtu.be/3k7zGsqUsbY?start=30&end=40", "youtu.be/fbNmnmuCha8?start=170&end=180", "youtu.be/j7muFWO1vN4?start=30&end=40", "youtu.be/d6dTtZwpSN8?start=150&end=160", "youtu.be/GVrspqytLM0?start=80&end=90", "youtu.be/Iu5uS7s-7ic?start=240&end=250", "youtu.be/fyYoxBvG29A?start=210&end=220"],
+    "child_ids": ["/m/0gvgw0", "/m/05x_td", "/m/02rhddq", "/m/03cl9h"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0gvgw0",
+    "name": "Air brake",
+    "description": "Sounds of a vehicle braking system in which compressed air is used to transmit force to the brake pads on the wheels. The pneumatic system makes an abrupt hissing sound when the pressure is released by venting the air.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Air_brake_(road_vehicle)",
+    "positive_examples": ["youtu.be/8Wk-ZmlsUqY?start=28&end=38", "youtu.be/6OOX9BS-ydU?start=30&end=40", "youtu.be/PJULCvSqmPw?start=30&end=40", "youtu.be/oancmFO62ns?start=21&end=31", "youtu.be/9keCNLhx4a0?start=30&end=40", "youtu.be/NecAPvps9io?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05x_td",
+    "name": "Air horn, truck horn",
+    "description": "The sound of a pneumatic device mounted on large vehicles designed to create an extremely loud noise for signalling purposes.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Air_horn",
+    "positive_examples": ["youtu.be/EF7i4DHBcnE?start=22&end=32", "youtu.be/AVC9tvCnKYE?start=30&end=40", "youtu.be/kcFS8Ugs3PU?start=30&end=40", "youtu.be/4nomoKwSVys?start=30&end=40", "youtu.be/fBMj2amDb7c?start=3&end=13", "youtu.be/ZIMZy7mOX7Y?start=30&end=40", "youtu.be/4iPQgalitDs?start=250&end=260", "youtu.be/58zUgdsdM0w?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02rhddq",
+    "name": "Reversing beeps",
+    "description": "The sound of an electronic warning device fitted to many commercial vehicles to alert pedestrians when the reverse gear is engaged, signaling that the vehicle is likely to move backwards.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Reversing_(vehicle_maneuver)",
+    "positive_examples": ["youtu.be/9OfYjXOhqmk?start=17&end=27", "youtu.be/DlKTxOx07jA?start=60&end=70", "youtu.be/7bBUxUpozzQ?start=40&end=50", "youtu.be/gQ1KUsQayuY?start=190&end=200", "youtu.be/38F6eeIR-s0?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03cl9h",
+    "name": "Ice cream truck, ice cream van",
+    "description": "Sounds of a commercial vehicle that serves as a mobile retail outlet for ice cream, usually during the summer. Ice cream vans often play a repeating nursery-rhyme-style melody from speakers mounted on the vehicle's exterior to attract customers.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Ice_cream_van",
+    "positive_examples": ["youtu.be/JXbMV5CqLkc?start=20&end=30", "youtu.be/6de_mfVMVik?start=40&end=50", "youtu.be/DRnIWAFMJOI?start=7&end=17", "youtu.be/fJpbrsTaWa4?start=19&end=29", "youtu.be/s1apsX51xBA?start=150&end=160", "youtu.be/kPIGN1jZdpk?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01bjv",
+    "name": "Bus",
+    "description": "Interior and exterior sounds of a road vehicle designed to carry many passengers.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bus",
+    "positive_examples": ["youtu.be/FLcqHUR58AU?start=60&end=70", "youtu.be/k0aJQaWGSYE?start=80&end=90", "youtu.be/h4hquL9bIEw?start=110&end=120", "youtu.be/YxvDDpmv-s4?start=30&end=40", "youtu.be/D3iiZju71yw?start=10&end=20", "youtu.be/NG3AQzmVgnE?start=14&end=24", "youtu.be/Tcdrj-kHoUc?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03j1ly",
+    "name": "Emergency vehicle",
+    "description": "The sound of any vehicle that is designated and authorized to respond to an emergency. Since emergency vehicles often need to travel at high speeds, they are frequently fitted with audible sirens to warn other motorists to give way.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Emergency_vehicle",
+    "positive_examples": ["youtu.be/xV0eTva6SKQ?start=24&end=34", "youtu.be/E6sS2d-NeTE?start=20&end=30", "youtu.be/JWd6vF4yfG8?start=100&end=110", "youtu.be/VqczA8N9pqM?start=19&end=29", "youtu.be/5gyVNyAY6Ns?start=30&end=40", "youtu.be/WPASuIJUWns?start=180&end=190", "youtu.be/mohBlDuZyYw?start=410&end=420", "youtu.be/XDJ9sFKqTV8?start=90&end=100", "youtu.be/ywRo3KB5AuM?start=10&end=20", "youtu.be/jg9TpmmZ5Ws?start=18&end=28"],
+    "child_ids": ["/m/04qvtq", "/m/012n7d", "/m/012ndj"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04qvtq",
+    "name": "Police car (siren)",
+    "description": "The sound of a siren fitted to a ground vehicle used by police when responding to incidents.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Police_car",
+    "positive_examples": ["youtu.be/C8Ne4NNA_CA?start=10&end=20", "youtu.be/lWDYbFDhV8k?start=40&end=50", "youtu.be/QRBD2TjXpcc?start=250&end=260", "youtu.be/ieDcpj6T7XI?start=30&end=40", "youtu.be/TBhbEn20dLs?start=120&end=130", "youtu.be/k9u987RcH64?start=2&end=12"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/012n7d",
+    "name": "Ambulance (siren)",
+    "description": "The sound of a siren fitted to a vehicle used to transport sick or injured people to a hospital or other medical facility.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Ambulance",
+    "positive_examples": ["youtu.be/0UX7Cl2iJJs?start=110&end=120", "youtu.be/VDom_PHnwZA?start=40&end=50", "youtu.be/u0VWWoFT0mA?start=30&end=40", "youtu.be/ZGkgx5m0Jt4?start=100&end=110", "youtu.be/RcLlkeN5TRc?start=270&end=280", "youtu.be/PTOF-fb9S5k?start=10&end=20", "youtu.be/3M3FsgEyWW8?start=290&end=300"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/012ndj",
+    "name": "Fire engine, fire truck (siren)",
+    "description": "The sound of a siren fitted to a vehicle used to transport firefighters and their equipment to an emergency situation.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Fire_engine",
+    "positive_examples": ["youtu.be/8Mnb35qaNBg?start=30&end=40", "youtu.be/AXzS-mChOB4?start=30&end=40", "youtu.be/0JPT13OUVV8?start=60&end=70", "youtu.be/iKHqGVW-Zu8?start=60&end=70", "youtu.be/7hPshpbbMBg?start=60&end=70", "youtu.be/orPJwjAeZHA?start=190&end=200", "youtu.be/qXAxJ0liwAE?start=70&end=80", "youtu.be/OP4mg83ynII?start=320&end=330"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04_sv",
+    "name": "Motorcycle",
+    "description": "Sounds of a small motor vehicle, usually with only two wheels. Motorcycles typically lack an external shell and seat riders astride the engine.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Motorcycle",
+    "positive_examples": ["youtu.be/BPXptOeqaqQ?start=80&end=90", "youtu.be/IhesEJJid7g?start=110&end=120", "youtu.be/J_EJg7FeJVQ?start=140&end=150", "youtu.be/4_qnGJihHvM?start=320&end=330", "youtu.be/PtLaYbr0ezA?start=90&end=100", "youtu.be/T7t7eymKq8I?start=360&end=370", "youtu.be/dd8ExHtH4qM?start=390&end=400", "youtu.be/FtHpeHIK3s0?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0btp2",
+    "name": "Traffic noise, roadway noise",
+    "description": "The combined sounds of many motor vehicles traveling on roads.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Traffic",
+    "positive_examples": ["youtu.be/LZ1bM5g_E0w?start=270&end=280", "youtu.be/7AN6Sfm3cFc?start=160&end=170", "youtu.be/yLW0Jd0_OAs?start=100&end=110", "youtu.be/FN1rC23Rrlg?start=170&end=180", "youtu.be/w5GiL7HGYj8?start=30&end=40", "youtu.be/K1k4sCWJS_g?start=30&end=40", "youtu.be/PIsYNyv77F4?start=570&end=580", "youtu.be/5ptjqWWz8W0?start=160&end=170"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06d_3",
+    "name": "Rail transport",
+    "description": "Sounds associated with wheeled vehicles running on rails (tracks).",
+    "citation_uri": "http://en.wikipedia.org/wiki/Rail_transport",
+    "positive_examples": ["youtu.be/nLvQz5b_520?start=140&end=150", "youtu.be/FD1ZidaXVv0?start=80&end=90", "youtu.be/mqbx_JLqq7c?start=40&end=50", "youtu.be/EL0ztYzolF0?start=410&end=420", "youtu.be/OGSX8NTNowE?start=70&end=80", "youtu.be/5jn-KJICC9g?start=110&end=120", "youtu.be/hQIu0GkaFZM?start=330&end=340", "youtu.be/x8r1bqLPm88?start=270&end=280"],
+    "child_ids": ["/m/07jdr", "/m/01g50p", "/t/dd00048", "/m/0195fx"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07jdr",
+    "name": "Train",
+    "description": "The sound of one or more coupled vehicles running on a rail track to transport cargo or passengers, propelled by a separate locomotive or individual motors in each railroad car.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Train",
+    "positive_examples": ["youtu.be/NTcgZ8rSpNI?start=20&end=30", "youtu.be/ulhaRVr-cVc?start=120&end=130", "youtu.be/-TIHs3wuY9E?start=160&end=170", "youtu.be/q1na9CH3Ufw?start=320&end=330"],
+    "child_ids": ["/m/04zmvq", "/m/0284vy3"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04zmvq",
+    "name": "Train whistle",
+    "description": "The sound of an audible signaling device on a steam locomotive used to warn that the train is approaching, and to communicate with rail workers.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Train_whistle",
+    "positive_examples": ["youtu.be/5rrwSsOeFso?start=20&end=30", "youtu.be/sCrfI81URlw?start=20&end=30", "youtu.be/30n4GYsBucU?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0284vy3",
+    "name": "Train horn",
+    "description": "The sound of an air horn which serves as an audible warning device on diesel and electric locomotives.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Train_horn",
+    "positive_examples": ["youtu.be/9kKfuvM4b64?start=110&end=120", "youtu.be/DxOJ47vC7lk?start=280&end=290", "youtu.be/JHhEjsAkZoc?start=320&end=330", "youtu.be/SimGJNnJvjA?start=30&end=40", "youtu.be/pNnwMXKDsH8?start=110&end=120", "youtu.be/KeoJ5d2CwAM?start=10&end=20", "youtu.be/gTFCK9TuLOQ?start=30&end=40", "youtu.be/_O5NaJziPSo?start=490&end=500", "youtu.be/_flJpCGAs5Y?start=220&end=230"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01g50p",
+    "name": "Railroad car, train wagon",
+    "description": "The sound of a vehicle used for carrying cargo or passengers on a rail transport system.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Railroad_car",
+    "positive_examples": ["youtu.be/6-RxMAsi5Lg?start=240&end=250", "youtu.be/AEA8ZJTyanM?start=280&end=290", "youtu.be/3ijC110Y964?start=40&end=50", "youtu.be/WWvv8lYU_Cc?start=30&end=40", "youtu.be/TA3E0Sk4Rno?start=410&end=420", "youtu.be/pYcn70JiIic?start=23&end=33", "youtu.be/Tk2dDhXIR1Y?start=120&end=130", "youtu.be/02w3vd_GgF0?start=20&end=30", "youtu.be/bYdlZOsrf60?start=450&end=460", "youtu.be/eONg_DTdnYQ?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00048",
+    "name": "Train wheels squealing",
+    "description": "The high-pitched tones caused by steel train wheels rubbing against rails, for instance when traversing a tight bend or when braking.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/3aRfForfdwQ?start=130&end=140", "youtu.be/gMWHNN1ff3E?start=380&end=390", "youtu.be/ASkhovrsIPA?start=310&end=320"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0195fx",
+    "name": "Subway, metro, underground",
+    "description": "Sounds of high-capacity electric railways that serve as public transport, generally in urban areas.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Rapid_transit",
+    "positive_examples": ["youtu.be/d1P3n4tQuqw?start=290&end=300", "youtu.be/i50lpZQbRm4?start=200&end=210", "youtu.be/-FBT_lY07L0?start=160&end=170", "youtu.be/UX6N6HRIS4w?start=10&end=20", "youtu.be/39TSxaQNm3E?start=50&end=60", "youtu.be/DB-nDjDvnfI?start=60&end=70", "youtu.be/U6QktI8TvUs?start=160&end=170", "youtu.be/XzfyPcaAEcE?start=420&end=430", "youtu.be/FF-FeQjcHo8?start=100&end=110"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0k5j",
+    "name": "Aircraft",
+    "description": "Sound of vehicles that fly by gaining support from the air.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Aircraft",
+    "positive_examples": ["youtu.be/CwiCsQ1uuwE?start=40&end=50", "youtu.be/lAeup78oZR4?start=10&end=20", "youtu.be/7lQGTHLXdhM?start=390&end=400", "youtu.be/z794C41L1pI?start=60&end=70", "youtu.be/oFECKaZ_3oE?start=80&end=90", "youtu.be/zj2R0XoFr5k?start=70&end=80", "youtu.be/T0jJZL3GKT0?start=40&end=50", "youtu.be/Fgp8ljPZNd8?start=70&end=80"],
+    "child_ids": ["/m/014yck", "/m/09ct_", "/m/0cmf2"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/014yck",
+    "name": "Aircraft engine",
+    "description": "The sound of the part of an aircraft that generates mechanical power. Aircraft engines are almost always lightweight piston engines, gas turbines, or, in small multicopter UAVs, electric motors.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Aircraft_engine",
+    "positive_examples": ["youtu.be/fn3iwcnOPrg?start=90&end=100", "youtu.be/2coSAx95GQU?start=50&end=60", "youtu.be/RKpQP1AAtBk?start=260&end=270", "youtu.be/xx17bh-qHyY?start=60&end=70", "youtu.be/4IsppmrZ5o0?start=20&end=30", "youtu.be/RqcINAxN51c?start=390&end=400", "youtu.be/Dia6QIxORbM?start=140&end=150", "youtu.be/ZGs7MopJt6o?start=10&end=20", "youtu.be/TaJHKexu3sk?start=10&end=20", "youtu.be/FsmBCrwWsJk?start=30&end=40"],
+    "child_ids": ["/m/04229", "/m/02l6bg"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04229",
+    "name": "Jet engine",
+    "description": "The sound of an internal combustion airbreathing engine that generates thrust by discharging a fast-moving jet of gas. Jet aircraft use such engines for long-distance travel.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Jet_engine",
+    "positive_examples": ["youtu.be/8IgKdVZ363c?start=30&end=40", "youtu.be/cPCbqyGC0-w?start=330&end=340", "youtu.be/ObFke2ZOH2g?start=130&end=140", "youtu.be/dENOlUJG-xI?start=160&end=170", "youtu.be/QXZBL0TQAdI?start=30&end=40", "youtu.be/pXDNMv9t990?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02l6bg",
+    "name": "Propeller, airscrew",
+    "description": "The sound of an aircraft propulsion system that converts rotary motion from an engine via a rotating set of blades into forward thrust through the air.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Propeller_(aeronautics)",
+    "positive_examples": ["youtu.be/1ag_IA2r_Ig?start=10&end=20", "youtu.be/sJwx1lnXXts?start=120&end=130", "youtu.be/n7FIIQPIbPg?start=310&end=320", "youtu.be/CuF4tcbKVpM?start=120&end=130", "youtu.be/rXNzfRo9BXU?start=140&end=150"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/09ct_",
+    "name": "Helicopter",
+    "description": "Sounds of a type of rotorcraft in which lift and thrust are supplied by rotors. This allows the helicopter to take off and land vertically, to hover, and to fly forward, backward, and laterally.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Helicopter",
+    "positive_examples": ["youtu.be/xpZpYRkr43g?start=110&end=120", "youtu.be/W1713WwiTSA?start=10&end=20", "youtu.be/ALdPf99u3s4?start=390&end=400", "youtu.be/2F9iORblSyw?start=150&end=160", "youtu.be/vuucKdxP4Ko?start=20&end=30", "youtu.be/yQwe8tQ9nNY?start=100&end=110", "youtu.be/6pzE3TgR2u8?start=20&end=30", "youtu.be/EoPk7WTZ_GY?start=470&end=480", "youtu.be/ZLJMgS5ysaQ?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0cmf2",
+    "name": "Fixed-wing aircraft, airplane",
+    "description": "Sounds of an aircraft capable of flight using wings that generate lift caused by the vehicle's forward airspeed and the shape of the wings.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Fixed-wing_aircraft",
+    "positive_examples": ["youtu.be/Gv7ZFYKFmqg?start=130&end=140", "youtu.be/8voZhq4ZUdw?start=60&end=70", "youtu.be/Ie2KkAvU1zU?start=130&end=140", "youtu.be/8vIButnIMp4?start=30&end=40", "youtu.be/ghcZErZzTPI?start=10&end=20", "youtu.be/t6-3INu2258?start=90&end=100", "youtu.be/j9N_Q9EXFP0?start=23&end=33", "youtu.be/XGammZXc2Eo?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00061",
+    "name": "Non-motorized land vehicle",
+    "description": "Sounds of human-powered vehicles used on roads or elsewhere on land.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/Dv-Ey9Na0C8?start=4&end=14"],
+    "child_ids": ["/m/0199g", "/m/06_fw"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0199g",
+    "name": "Bicycle",
+    "description": "Sounds of a human-powered, pedal-driven vehicle, having two wheels attached to a frame, one behind the other.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bicycle",
+    "positive_examples": ["youtu.be/Cg5sZo1W_EI?start=190&end=200", "youtu.be/FPi-h5oLFbw?start=410&end=420", "youtu.be/m3SxgaD4vGw?start=30&end=40", "youtu.be/DkjX3KtPHCk?start=60&end=70", "youtu.be/JqrYxQ6_eak?start=480&end=490", "youtu.be/8nfOPcwObls?start=70&end=80", "youtu.be/6SFinhyJaCs?start=30&end=40"],
+    "child_ids": ["/m/0gy1t2s"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06_fw",
+    "name": "Skateboard",
+    "description": "Sounds of a type of sports equipment consisting of a board mounted on two pairs of wheels. A skateboard is typically propelled by pushing with one foot while the other remains on the board, or by simply standing on the deck while on a downward slope and allowing gravity to propel the board and rider.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Skateboard",
+    "positive_examples": ["youtu.be/ja4EA1MiDs8?start=130&end=140", "youtu.be/4mLv61JADOQ?start=40&end=50", "youtu.be/kwQQSiYG1lk?start=70&end=80", "youtu.be/eKFbKpSfddE?start=25&end=35", "youtu.be/7awbfTNKjWc?start=30&end=40", "youtu.be/IGBRNQ9-9r0?start=250&end=260", "youtu.be/APYR7TeoGCQ?start=30&end=40", "youtu.be/yRzTXFjC-Hw?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02mk9",
+    "name": "Engine",
+    "description": "The sound of a machine designed to produce mechanical energy. Combustion engines burn a fuel to create heat, which then creates a force. Electric motors convert electrical energy into mechanical motion. Other classes of engines include pneumatic motors and clockwork motors.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Engine",
+    "positive_examples": ["youtu.be/rD1XBW018e4?start=120&end=130", "youtu.be/21Hv4dPd-5c?start=21&end=31", "youtu.be/1OulOUPg7-8?start=3&end=13", "youtu.be/DgyFll5DJeQ?start=30&end=40", "youtu.be/ETVA-wrKgtA?start=120&end=130", "youtu.be/33eq2a2BeZI?start=30&end=40", "youtu.be/V0CRYp34c2k?start=30&end=40", "youtu.be/fO250kjXV7U?start=20&end=30"],
+    "child_ids": ["/t/dd00065", "/t/dd00066", "/t/dd00067", "/m/04229", "/m/01h82_", "/t/dd00130", "/m/07pb8fc", "/m/07q2z82"],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00065",
+    "name": "Light engine (high frequency)",
+    "description": "The sound of a small engine such as a toy car, sewing machine, or moped.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/i69icWu7vgM?start=120&end=130", "youtu.be/_yFwVTg-V-M?start=10&end=20", "youtu.be/Bt-h7IczpuM?start=40&end=50", "youtu.be/5xiXwDn7eJ8?start=80&end=90", "youtu.be/HI7BKGzGerc?start=190&end=200", "youtu.be/SaUTCeOPdUQ?start=50&end=60", "youtu.be/Lzec-fG2xwI?start=520&end=530", "youtu.be/ki9Mnrelw5s?start=360&end=370"],
+    "child_ids": ["/m/08j51y", "/m/01yg9g", "/m/01j4z9"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/08j51y",
+    "name": "Dental drill, dentist's drill",
+    "description": "The sound of a small, high-speed drill used during dental procedures, usually to remove decay and shape tooth structure prior to the insertion of a filling or crown.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Dental_drill",
+    "positive_examples": ["youtu.be/Z5I3qUNg8Xg?start=280&end=290", "youtu.be/52sTvbwi7Mg?start=130&end=140"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01yg9g",
+    "name": "Lawn mower",
+    "description": "The sound of a machine utilizing one or more revolving blades to cut grass, powered by an electric motor, a small internal combustion engine, or by a human pushing the machine.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Lawn_mower",
+    "positive_examples": ["youtu.be/095CdSbYrFc?start=30&end=40", "youtu.be/CPjttawNaII?start=50&end=60", "youtu.be/zj_gAYMxfQ8?start=20&end=30", "youtu.be/LB4w_fc8F-A?start=60&end=70", "youtu.be/16d3D1AWFu8?start=20&end=30", "youtu.be/UM5xPbgiDbs?start=60&end=70"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01j4z9",
+    "name": "Chainsaw",
+    "description": "The sound of a portable mechanical saw which cuts with a set of teeth attached to a rotating chain. Chainsaws are commonly powered by a small two-stroke internal combustion engine.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Chainsaw",
+    "positive_examples": ["youtu.be/uFenFl01Eu8?start=360&end=370", "youtu.be/8yBGrAo62iQ?start=70&end=80", "youtu.be/-RNbb1ZTu8Y?start=30&end=40", "youtu.be/HZ69dl6yTYM?start=90&end=100", "youtu.be/Ae6pZjdGfRY?start=30&end=40", "youtu.be/vRa8ncJ-Zrw?start=230&end=240", "youtu.be/iWOlAJb2ogg?start=30&end=40", "youtu.be/CDm5VBH6nL4?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00066",
+    "name": "Medium engine (mid frequency)",
+    "description": "The sound of a moderately-sized engine such as that which powers a motorcycle, sedan, or small truck.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/1uTnWkTP9a0?start=24&end=34", "youtu.be/2zsjLiSNK0Q?start=30&end=40", "youtu.be/s0irKAYCfOE?start=30&end=40", "youtu.be/6Pv8cptxmaI?start=17&end=27", "youtu.be/2aQWtSZafxA?start=30&end=40", "youtu.be/0Xny2kBTr1U?start=340&end=350", "youtu.be/BrGwC9j8gZg?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00067",
+    "name": "Heavy engine (low frequency)",
+    "description": "The sound of a large, heavy-duty internal combustion engine, such as that which powers a large truck, locomotive, or ship.  Jet engines, steam engines, rocket engines etc. are excluded.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/-TBHymyAbCs?start=30&end=40", "youtu.be/-TFvKCs-Nlc?start=30&end=40", "youtu.be/QkBBROJPasI?start=30&end=40", "youtu.be/-kXfIGe5I8Y?start=28&end=38", "youtu.be/-olpPhZLSWI?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01h82_",
+    "name": "Engine knocking",
+    "description": "A metallic \"pinging\" sound caused by a malfunctioning spark-ignited internal combustion engine. Engine knocking indicates that the combustion of the air/fuel mixture in the cylinder is occurring at the wrong point in the piston's stroke.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Engine_knocking",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/t/dd00130",
+    "name": "Engine starting",
+    "description": "The sound of an engine starting from rest, which may involve a specific starter mechanism (as in a standard car).",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/6O2fJUnSxnE?start=30&end=40", "youtu.be/4fl09vJXgH4?start=30&end=40", "youtu.be/tRl0-Q0ZJZI?start=18&end=28", "youtu.be/AnpUWRakgmE?start=150&end=160", "youtu.be/BEKB0WKczpg?start=15&end=25"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pb8fc",
+    "name": "Idling",
+    "description": "The sound of an engine (typically in an automobile) running without any load and at minimal RPM.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=idling",
+    "positive_examples": ["youtu.be/-QN2auumfOI?start=30&end=40", "youtu.be/BJb9Idgq_xo?start=30&end=40", "youtu.be/1E8u66vm870?start=20&end=30", "youtu.be/9H_aqeYUlak?start=17&end=27", "youtu.be/--lKwp2nVm0?start=30&end=40", "youtu.be/90oHXiTbKGU?start=30&end=40", "youtu.be/7t2M6fwsvzs?start=510&end=520", "youtu.be/73Vz2uj8iKY?start=300&end=310"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07q2z82",
+    "name": "Accelerating, revving, vroom",
+    "description": "The sound made by the engine of a vehicle undergoing acceleration, usually involving an increase in loudness and a rising pitch.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=accelerating",
+    "positive_examples": ["youtu.be/FkyO6R1Frgw?start=30&end=40", "youtu.be/bU-KxtzE1CA?start=30&end=40", "youtu.be/gif5KpUlVT0?start=90&end=100", "youtu.be/HxiEFMumhHY?start=28&end=38", "youtu.be/M4f5MMdu4mY?start=30&end=40", "youtu.be/1NGdiCVV7iM?start=30&end=40", "youtu.be/Y7nMy5Ei_2A?start=10&end=20", "youtu.be/x2mQVZ3NpG0?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00071",
+    "name": "Domestic sounds, home sounds",
+    "description": "Sounds that suggest they have been recorded in the home.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/02dgv", "/m/0642b4", "/m/0fqfqc", "/m/04brg2", "/m/023pjk", "/m/07pn_8q", "/m/0dxrf", "/m/0fx9l", "/m/02pjr4", "/g/11b630rrvh", "/m/02jz0l", "/m/0130jx", "/m/03dnzn", "/m/03wvsk", "/m/01jt3m", "/m/012xff", "/m/0d31p", "/m/01s0vc", "/m/0zmy2j9", "/m/03v3yw", "/m/0242l", "/m/05mxj0q", "/m/01lsmm", "/m/02g901", "/m/05rj2", "/m/0316dw", "/m/081rb"],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/02dgv",
+    "name": "Door",
+    "description": "Sounds of a moving structure used to open or close an entrance to an enclosed space such as a building or vehicle.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Door",
+    "positive_examples": ["youtu.be/yM25TgQQ6Ug?start=30&end=40", "youtu.be/XPZnacpWtGI?start=100&end=110", "youtu.be/OcDE75D-O9k?start=230&end=240", "youtu.be/HMp3VHakVKw?start=30&end=40", "youtu.be/kKhnHNY2eqs?start=18&end=28", "youtu.be/8nPjSFqIIoo?start=200&end=210", "youtu.be/nzPQjQppcjc?start=30&end=40"],
+    "child_ids": ["/m/03wwcy", "/m/02y_763", "/m/07rjzl8", "/m/07r4wb8", "/m/07qcpgn", "/m/07q6cd_"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03wwcy",
+    "name": "Doorbell",
+    "description": "The sound of a signaling device typically placed near a building's entrance with which a visitor can announce their presence to occupants.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Doorbell",
+    "positive_examples": ["youtu.be/_oiZ9F6EVtw?start=130&end=140", "youtu.be/2NV5jIsXl0g?start=2&end=12", "youtu.be/-DoFDKsAOo4?start=30&end=40", "youtu.be/JvgYGGBGZpM?start=30&end=40", "youtu.be/hqCL8MieXp8?start=20&end=30"],
+    "child_ids": ["/m/07r67yg"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r67yg",
+    "name": "Ding-dong",
+    "description": "A multi-tone chime made by a doorbell.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=ding-dong",
+    "positive_examples": ["youtu.be/bVvJzXMLaS8?start=20&end=30", "youtu.be/mP0zSmVOMNE?start=1&end=11", "youtu.be/pNoFoH57fOg?start=210&end=220"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02y_763",
+    "name": "Sliding door",
+    "description": "The sound of a type of door which opens horizontally by sliding, usually parallel to a wall.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sliding_door",
+    "positive_examples": ["youtu.be/Fs462T7ODUQ?start=30&end=40", "youtu.be/49thYHlXkSA?start=21&end=31", "youtu.be/bH_4hTLhZi4?start=30&end=40", "youtu.be/HeUnxmbKYqc?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rjzl8",
+    "name": "Slam",
+    "description": "The sound of a door or other hinged cover being closed violently.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=slam",
+    "positive_examples": ["youtu.be/0W4KKR9sUIo?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r4wb8",
+    "name": "Knock",
+    "description": "A sharp noise of a rigid surface being struck, usually without damage and deliberately, most often with the knuckles of the hand.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=knock",
+    "positive_examples": ["youtu.be/bWppskIvs40?start=30&end=40", "youtu.be/qhR8NGj4QJU?start=10&end=20", "youtu.be/Lc17Q6sGH48?start=120&end=130", "youtu.be/-OsX9u6oJw8?start=40&end=50", "youtu.be/ZQ0OfMZRPGM?start=10&end=20", "youtu.be/TIjqdHhg6n0?start=220&end=230"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qcpgn",
+    "name": "Tap",
+    "description": "The sound of a light collision between a rigid object and a rigid surface, for instance to deliberately attract attention.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=tap",
+    "positive_examples": ["youtu.be/DOG1JX-hIC8?start=30&end=40", "youtu.be/EcMb6OIRnWQ?start=30&end=40", "youtu.be/-WwGFIPH6us?start=30&end=40", "youtu.be/lII65O5C_H0?start=400&end=410", "youtu.be/ch4_bbDOKMc?start=30&end=40", "youtu.be/CbeZxCPsS2w?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07q6cd_",
+    "name": "Squeak",
+    "description": "A short, high-pitched noise without a sharp attack.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=squeak",
+    "positive_examples": ["youtu.be/sS9j4nxxw4c?start=30&end=40", "youtu.be/4YPpyKEKZzc?start=350&end=360", "youtu.be/z_iUAQCVLwo?start=130&end=140", "youtu.be/l9kNnBvzQyE?start=170&end=180", "youtu.be/7v51jrS0aWw?start=80&end=90", "youtu.be/VKhsmuzuwSA?start=460&end=470", "youtu.be/-2XJTklj-Y0?start=30&end=40", "youtu.be/0K8CacUc7bc?start=260&end=270", "youtu.be/UD0pisqyLKA?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0642b4",
+    "name": "Cupboard open or close",
+    "description": "The sound of the door to a storage cabinet being opened or closed.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cupboard",
+    "positive_examples": ["youtu.be/zdA3_n7rbVA?start=350&end=360", "youtu.be/f-4xmt1Ny_A?start=20&end=30", "youtu.be/VY4Z_VyHQx8?start=440&end=450"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0fqfqc",
+    "name": "Drawer open or close",
+    "description": "The sound of the opening or closing of a box-shaped container that fits into a piece of furniture in such a way that it can be drawn out horizontally to reach its contents.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Drawer_(furniture)",
+    "positive_examples": ["youtu.be/CR3HqozYwos?start=130&end=140", "youtu.be/w3vWTE4U-C0?start=280&end=290", "youtu.be/RYyqlQusoWk?start=30&end=40", "youtu.be/u__XGncVbM4?start=190&end=200", "youtu.be/zNG3JJY1Gq0?start=430&end=440"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04brg2",
+    "name": "Dishes, pots, and pans",
+    "description": "The sound of non-destructive collisions between plates, dishes, glassware, cooking vessels, and kitchen and eating utensils.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Tableware",
+    "positive_examples": ["youtu.be/5ohCslwvxdw?start=40&end=50", "youtu.be/il4kvln-pMk?start=160&end=170", "youtu.be/T4EAWRT6XoE?start=110&end=120", "youtu.be/T9z7Ju7S7rs?start=70&end=80", "youtu.be/i34M-tBZLtA?start=480&end=490", "youtu.be/It7mU9zMI4w?start=80&end=90", "youtu.be/1X3ab9ycVL0?start=180&end=190", "youtu.be/uA_0qDi-_a0?start=350&end=360"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/023pjk",
+    "name": "Cutlery, silverware",
+    "description": "The sounds of hand implements such as knife, fork, and spoon, that are typically made of steel and are used in preparing, serving, and eating food in the Western world.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cutlery",
+    "positive_examples": ["youtu.be/-MhcTz7hPIE?start=210&end=220", "youtu.be/2osey_ew_Kw?start=80&end=90", "youtu.be/3jSNHT62tAc?start=2&end=12", "youtu.be/4dG_VyOjAqc?start=200&end=210"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pn_8q",
+    "name": "Chopping (food)",
+    "description": "The sound of cutting ingredients into pieces with a knife or similar blade tool.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=chop",
+    "positive_examples": ["youtu.be/_BETXRVC4bs?start=30&end=40", "youtu.be/AGjDiJ4mfYY?start=25&end=35", "youtu.be/EtvVawYx2pc?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0dxrf",
+    "name": "Frying (food)",
+    "description": "The sound of cooking food in oil or another fat.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Frying",
+    "positive_examples": ["youtu.be/KP-sFwyyi2k?start=160&end=170", "youtu.be/N_0XMZaUHtE?start=510&end=520", "youtu.be/OQYqCbdDWFc?start=50&end=60", "youtu.be/HJRCxcMFOMk?start=290&end=300", "youtu.be/zCghjBsfJEc?start=30&end=40", "youtu.be/yGx08kFWCSE?start=100&end=110", "youtu.be/g765TOvaIcY?start=140&end=150", "youtu.be/CrIC2a3X1Y0?start=100&end=110"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0fx9l",
+    "name": "Microwave oven",
+    "description": "Sounds made by a kitchen appliance that heats food by exposing it to microwave radiation, including the noise of the fan, rotation mechanism, and microwave source, as well as the alert sound used to indicate that cooking is complete.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Microwave_oven",
+    "positive_examples": ["youtu.be/bvMxz7Rmvus?start=110&end=120", "youtu.be/gxPVEluTzWg?start=130&end=140", "youtu.be/l0AcPKfa5hY?start=19&end=29", "youtu.be/ZusvtL69US0?start=60&end=70", "youtu.be/vHuPSThm1Hs?start=50&end=60", "youtu.be/JQsWiBWEQlc?start=470&end=480", "youtu.be/jPlFLbfXfWc?start=140&end=150", "youtu.be/OGRxucs06r8?start=280&end=290"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02pjr4",
+    "name": "Blender",
+    "description": "The sound of a kitchen and laboratory appliance used to mix, purée, or emulsify food and other substances, usually by means of metal blades at the base of a container spun rapidly by an electric motor.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Blender",
+    "positive_examples": ["youtu.be/VGgQ2zyaClY?start=30&end=40", "youtu.be/DptBcsuywGc?start=90&end=100", "youtu.be/Uqj2GGPVo2E?start=420&end=430", "youtu.be/-ghB9TOCBR8?start=50&end=60", "youtu.be/FOUjOK2AZ30?start=550&end=560", "youtu.be/CcUoNeNvHOc?start=260&end=270", "youtu.be/pSyQDrAA9sg?start=140&end=150", "youtu.be/ATI2Fz0g4yk?start=3&end=13", "youtu.be/JZq60-sNsEY?start=290&end=300"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/g/11b630rrvh",
+    "name": "Kettle whistle",
+    "description": "The high-pitched sound of a whistle attached to the spout of an appliance for boiling water.  When the water boils, steam is forced through the whistle, alerting users that boiling is complete.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/5n1i0WeteUk?start=80&end=90", "youtu.be/Zo5WbFdzMKY?start=220&end=230"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02jz0l",
+    "name": "Water tap, faucet",
+    "description": "The sound of a hand-operated valve controlling the release of water, for instance as fitted to a sink or bath, and the resulting water flow.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Tap_(valve)",
+    "positive_examples": ["youtu.be/-VvftMHnhLA?start=30&end=40", "youtu.be/iED4FnsSrt4?start=40&end=50", "youtu.be/ApyWX6Zstno?start=30&end=40", "youtu.be/5Ms9SsvnVIQ?start=80&end=90", "youtu.be/K23jUY6DnrE?start=390&end=400", "youtu.be/ixFsIj_CcN4?start=330&end=340", "youtu.be/Uu7u_EcCIXg?start=400&end=410"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0130jx",
+    "name": "Sink (filling or washing)",
+    "description": "Sounds originating from a bowl-shaped plumbing fixture that stores and drains water and that is used for washing hands, dishwashing, and other purposes.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sink",
+    "positive_examples": ["youtu.be/p4HKDsrHt80?start=310&end=320", "youtu.be/O4_OKqnPKU8?start=1&end=11", "youtu.be/IZpgE9_0SKw?start=70&end=80", "youtu.be/8kffb_v6MG0?start=90&end=100", "youtu.be/csNTcYADSIQ?start=90&end=100", "youtu.be/27NlyHgiaPw?start=120&end=130"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03dnzn",
+    "name": "Bathtub (filling or washing)",
+    "description": "Sounds originating from a large container for holding water in which a person may bathe.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bathtub",
+    "positive_examples": ["youtu.be/J3YxLTjCXt8?start=60&end=70", "youtu.be/9uSqapjvYrg?start=420&end=430", "youtu.be/NrqUBYJB1_w?start=100&end=110", "youtu.be/i8TgI5kv5AE?start=240&end=250"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03wvsk",
+    "name": "Hair dryer",
+    "description": "The sound of an electromechanical device designed to blow normal or hot air over damp hair, in order to dry the hair.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Hair_dryer",
+    "positive_examples": ["youtu.be/ezfz-icEVek?start=520&end=530", "youtu.be/HbKbkTkvOL0?start=180&end=190", "youtu.be/jwGfwbsF4c4?start=30&end=40", "youtu.be/IsGRLS6yPuE?start=500&end=510"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01jt3m",
+    "name": "Toilet flush",
+    "description": "The sound of a toilet flushing water along with any waste through a drainpipe.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Flush_toilet",
+    "positive_examples": ["youtu.be/DZa-AIhRZDM?start=40&end=50", "youtu.be/wmkFfxfOHLA?start=120&end=130", "youtu.be/P3VT_FsOCW8?start=270&end=280", "youtu.be/sQEk9hRHvqQ?start=30&end=40", "youtu.be/kWpxOCSDKsw?start=10&end=20", "youtu.be/rw7A8gr2nms?start=30&end=40", "youtu.be/7UynE2aCvIQ?start=20&end=30", "youtu.be/uGfdRA5derI?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/012xff",
+    "name": "Toothbrush",
+    "description": "Sounds of an instrument used to clean the teeth and gums consisting of a head of tightly clustered bristles mounted on a handle.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Toothbrush",
+    "positive_examples": ["youtu.be/JKX35FOb76Q?start=220&end=230", "youtu.be/WQBVIFHMJ40?start=50&end=60", "youtu.be/BpDu70Sa6qo?start=50&end=60", "youtu.be/bnjY4k3Pk5Y?start=20&end=30", "youtu.be/1BXaCy0ox3c?start=280&end=290", "youtu.be/AyA6zrWfkYY?start=310&end=320", "youtu.be/Gt50mgYkDH0?start=100&end=110"],
+    "child_ids": ["/m/04fgwm"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04fgwm",
+    "name": "Electric toothbrush",
+    "description": "The sound of a toothbrush that makes rapid, automatic bristle motions driven by an electric motor in order to clean teeth.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Electric_toothbrush",
+    "positive_examples": ["youtu.be/dm0tSDrMGUA?start=360&end=370", "youtu.be/WG08A74Cnf4?start=70&end=80", "youtu.be/mV8WUIvEKk0?start=16&end=26"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0d31p",
+    "name": "Vacuum cleaner",
+    "description": "The sound of a device that uses an air pump to create a partial vacuum to suck up dust and dirt, usually from floors and other surfaces such as upholstery and draperies.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Vacuum_cleaner",
+    "positive_examples": ["youtu.be/zPyYpAWVarc?start=150&end=160", "youtu.be/zmIwBvOXJXQ?start=130&end=140", "youtu.be/CgtYVinJPa8?start=290&end=300", "youtu.be/Qyolp0Qf9Nc?start=140&end=150", "youtu.be/cP-OvBQ5RmA?start=30&end=40", "youtu.be/QVZKgL4EORQ?start=220&end=230", "youtu.be/7HXiTVCIiQM?start=180&end=190"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01s0vc",
+    "name": "Zipper (clothing)",
+    "description": "The sound of a device consisting of two rows of small interlocking teeth for binding the edges of an opening of fabric or other flexible material, like on a garment or a bag.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Zipper",
+    "positive_examples": ["youtu.be/0XX0K_HNflo?start=30&end=40", "youtu.be/39sSIF_5oiA?start=30&end=40", "youtu.be/zjeigOmIz7U?start=30&end=40", "youtu.be/mpJolOCZ-_E?start=30&end=40", "youtu.be/t1APkUsoNhg?start=18&end=28", "youtu.be/kckdevn05rM?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0zmy2j9",
+    "name": "Velcro, hook and loop fastener",
+    "description": "Sounds of fasteners typically consisting of two lineal fabric strips, one featuring tiny hooks, the second consisting of even smaller and \"hairier\" loops.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Hook_and_loop_fastener",
+    "positive_examples": ["youtu.be/i6_BUnSbcmg?start=380&end=390", "youtu.be/nawwAJZQfzU?start=21&end=31", "youtu.be/BqtXSwmi4o0?start=170&end=180", "youtu.be/Sc-fSFNSfkg?start=30&end=40", "youtu.be/Qe6J61XXTZw?start=30&end=40", "youtu.be/3ej1cmiQYGM?start=24&end=34"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03v3yw",
+    "name": "Keys jangling",
+    "description": "Sounds made by the mutual collision of small pieces of metal, which are often linked on a ring, used to operate locks.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Key_(lock)",
+    "positive_examples": ["youtu.be/eHHBXazWbpc?start=180&end=190", "youtu.be/EMtKMP3HVs0?start=280&end=290", "youtu.be/4zEv7RY2kTg?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0242l",
+    "name": "Coin (dropping)",
+    "description": "The sound of a small, flat, round piece of hard material such as metal or plastic colliding with or bouncing on a hard surface.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Coin",
+    "positive_examples": ["youtu.be/LT0udusisI4?start=570&end=580", "youtu.be/_-u7RBpA2_Y?start=40&end=50", "youtu.be/yZDtVd414io?start=20&end=30", "youtu.be/beZ5vqRqO5U?start=220&end=230", "youtu.be/D6_LkeTx4uE?start=350&end=360", "youtu.be/KRfb-rFWqZk?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05mxj0q",
+    "name": "Packing tape, duct tape",
+    "description": "Sounds associated with self-adhesive tape from wide rolls used to seal cardboard boxes and other temporary attachments. Specifically includes the distinctive noise of the tape being dispensed from a roll.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Box-sealing_tape",
+    "positive_examples": ["youtu.be/30gm0gZpYrw?start=90&end=100"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01lsmm",
+    "name": "Scissors",
+    "description": "The sound of hand-operated shearing tools consisting of a pair of metal blades pivoted so that the sharpened edges slide against each other when the handles opposite to the pivot are closed.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Scissors",
+    "positive_examples": ["youtu.be/HDZ2_fLVZm0?start=30&end=40", "youtu.be/orxEbCkwH9M?start=320&end=330", "youtu.be/pbwT9PIfJcU?start=300&end=310", "youtu.be/1hba9jmspEQ?start=30&end=40", "youtu.be/l2LSwFtqGKk?start=470&end=480", "youtu.be/3hBvEDX7Q8k?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02g901",
+    "name": "Electric shaver, electric razor",
+    "description": "The sound of a bladed tool primarily used in the removal of unwanted body hair where the blades are continually moved by an electric motor.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Razor",
+    "positive_examples": ["youtu.be/raXE9JRtcHQ?start=40&end=50", "youtu.be/De4WXe0RE7A?start=300&end=310", "youtu.be/JODPEwUPyUE?start=40&end=50", "youtu.be/OS-kL4p0XpI?start=80&end=90", "youtu.be/EtM-2FtKBf0?start=30&end=40", "youtu.be/wHoSjefsmsE?start=420&end=430", "youtu.be/IEC8cLcZ6IE?start=170&end=180"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05rj2",
+    "name": "Shuffling cards",
+    "description": "The sound of playing cards being manually rearranged into a random order.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Shuffling",
+    "positive_examples": ["youtu.be/83W_DUSS830?start=410&end=420", "youtu.be/nn9iLR99iAM?start=30&end=40", "youtu.be/4KMp9SlzNjk?start=380&end=390", "youtu.be/dI95aySekBI?start=50&end=60", "youtu.be/QfF8hRWie4c?start=30&end=40", "youtu.be/9ju96NjwhVY?start=260&end=270", "youtu.be/fu--BTYNcKw?start=230&end=240"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0316dw",
+    "name": "Typing",
+    "description": "The sound of writing or inputting text by pressing keys on a typewriter, computer keyboard, cell phone, or calculator.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Typing",
+    "positive_examples": ["youtu.be/pfZpFTHWpEI?start=160&end=170", "youtu.be/_iOR9VnJ_iQ?start=30&end=40", "youtu.be/0_yN1k-S99I?start=30&end=40", "youtu.be/fuGiiIhekW8?start=390&end=400", "youtu.be/Rpx9ROxCJ04?start=190&end=200", "youtu.be/StRjbDLa23U?start=20&end=30", "youtu.be/-b1bMK154QU?start=280&end=290", "youtu.be/O9tM5h9beDM?start=30&end=40"],
+    "child_ids": ["/m/0c2wf", "/m/01m2v"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0c2wf",
+    "name": "Typewriter",
+    "description": "Sounds of a mechanical or electromechanical machine for printing characters by means of keyboard-operated types striking a ribbon to transfer ink or carbon impressions onto paper.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Typewriter",
+    "positive_examples": ["youtu.be/I82-B02oOBg?start=380&end=390", "youtu.be/UJ9xKsKaKAA?start=30&end=40", "youtu.be/c40hgtfiYm0?start=30&end=40", "youtu.be/yoiR7G1Y85Y?start=30&end=40", "youtu.be/9H7ugTcVbXQ?start=10&end=20", "youtu.be/L4uwP5teSwM?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01m2v",
+    "name": "Computer keyboard",
+    "description": "Sounds created by a typewriter-style device which uses an arrangement of buttons or keys controlling switches to enter text or other information into a computer or other electronic device.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Computer_keyboard",
+    "positive_examples": ["youtu.be/MK-hwHhgDLY?start=450&end=460", "youtu.be/7rGGBa_lZ54?start=260&end=270", "youtu.be/xMTVzNoGOxA?start=50&end=60", "youtu.be/jHtAPbCj0U4?start=410&end=420", "youtu.be/oBEvBG2D8AE?start=190&end=200", "youtu.be/9NcxNH75ByE?start=30&end=40", "youtu.be/eW83JnAnMww?start=260&end=270", "youtu.be/AL-dutJvx0s?start=30&end=40", "youtu.be/8GHLfJ6y6zA?start=570&end=580"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/081rb",
+    "name": "Writing",
+    "description": "The sound of inscribing signs and symbols, most often by using a purpose-made hand-held device, such as a pen or pencil, directly upon paper or similar media.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Writing",
+    "positive_examples": ["youtu.be/JO3nmsEXrro?start=340&end=350", "youtu.be/Y8uYhcPssuE?start=80&end=90", "youtu.be/74Vqth_HvqU?start=130&end=140", "youtu.be/HIfhUyU9W20?start=80&end=90", "youtu.be/drtbr0LpLDI?start=22&end=32", "youtu.be/-YKVzemh9RQ?start=30&end=40", "youtu.be/eD-ANIqSWzU?start=90&end=100"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pp_mv",
+    "name": "Alarm",
+    "description": "The sound of an automatic signal warning of danger.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=alarm",
+    "positive_examples": ["youtu.be/uZDkS4PQPhg?start=30&end=40", "youtu.be/1Hf_1QejY4I?start=20&end=30", "youtu.be/a3jZ7QBDhgc?start=30&end=40", "youtu.be/v2Mmlp3YPPM?start=150&end=160", "youtu.be/M82tO6erP8Y?start=160&end=170", "youtu.be/ygXK90AVXFY?start=50&end=60"],
+    "child_ids": ["/m/07cx4", "/m/046dlr", "/m/03kmc9", "/m/03wwcy", "/m/030rvx", "/m/01y3hg", "/m/0c3f7m", "/m/02mfyn", "/m/0912c9", "/m/0gy1t2s", "/m/05x_td", "/m/04fq5q", "/m/0l156k"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07cx4",
+    "name": "Telephone",
+    "description": "The sound of a telecommunications device that permits two or more users to conduct a conversation when they are too far apart to be heard directly.  This class covers sounds associated with the device itself, not voice that has been carried via the telephone network.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Telephone",
+    "positive_examples": ["youtu.be/0uETEh6kc0o?start=30&end=40", "youtu.be/Y12efRHPBok?start=130&end=140", "youtu.be/jDsfFsfox9o?start=20&end=30", "youtu.be/S_ZdkIw32hY?start=30&end=40", "youtu.be/ackdwXSwINs?start=30&end=40", "youtu.be/5K7mSWlamvI?start=10&end=20", "youtu.be/CaARlo0W-WI?start=5&end=15", "youtu.be/sWxcqTcEWPo?start=330&end=340"],
+    "child_ids": ["/m/07pp8cl", "/m/01hnzm", "/m/01sb50", "/m/02c8p", "/m/015jpf", "/m/01z47d"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pp8cl",
+    "name": "Telephone bell ringing",
+    "description": "The sound of a physical or synthesized electric bell ringing to signal an incoming telephone call.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=telephone%20bell",
+    "positive_examples": ["youtu.be/0RItg3CCgAc?start=280&end=290", "youtu.be/xIztYnMIWUA?start=30&end=40", "youtu.be/koZiVapPW4Q?start=220&end=230", "youtu.be/y8Kp8RmvKFw?start=30&end=40", "youtu.be/j9NQitaeuGg?start=30&end=40", "youtu.be/UJ8vpkVsY34?start=30&end=40", "youtu.be/v-C5UHWHDw4?start=11&end=21"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01hnzm",
+    "name": "Ringtone",
+    "description": "The synthesized or pre-recorded sounds made by contemporary electronic telephones to indicate an incoming call or text message.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Ringtone",
+    "positive_examples": ["youtu.be/F91ueYOdGfI?start=400&end=410", "youtu.be/NUe_yfLTqc8?start=30&end=40", "youtu.be/LhqpEHInT_w?start=380&end=390", "youtu.be/8o7yBPCaYyM?start=380&end=390", "youtu.be/NXPSFXXzzkg?start=230&end=240", "youtu.be/JC70GNb_dmo?start=180&end=190", "youtu.be/sFok1rcnU6U?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01sb50",
+    "name": "Cellphone buzz, vibrating alert",
+    "description": "The low buzz emitted by the vibrotactile actuator used to provide \"silent alarms\" on mobile phones and other devices.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Vibrating_alert",
+    "positive_examples": ["youtu.be/bipdap5oNJY?start=270&end=280"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02c8p",
+    "name": "Telephone dialing, DTMF",
+    "description": "The sound of a telephony signaling system where short combinations of tones within the frequency range of human speech are used to transmit individual digits.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Dual-tone_multi-frequency_signaling",
+    "positive_examples": ["youtu.be/4eLBAlJq1cg?start=20&end=30", "youtu.be/mxxvJtatNx8?start=30&end=40", "youtu.be/WqP9GopZdAk?start=460&end=470", "youtu.be/soJspyOEeXw?start=410&end=420", "youtu.be/xHYs_58hXfg?start=60&end=70", "youtu.be/HherPtX1e5c?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/015jpf",
+    "name": "Dial tone",
+    "description": "The sound of a signal that a telephone exchange or other switching equipment sends to a telephone to confirm that it is ready to initiate a connection.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Dial_tone",
+    "positive_examples": ["youtu.be/0Wfdq_3F9VA?start=3&end=13", "youtu.be/BcAuCN7qQzI?start=40&end=50", "youtu.be/j7whx_ntCog?start=180&end=190", "youtu.be/YTBCmc70I20?start=270&end=280"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01z47d",
+    "name": "Busy signal",
+    "description": "A sound (usually a simple repeating tone) played over a telephone line to indicate that the requested connection could not be completed, for instance because the remote party is already engaged in a different call.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Busy_signal",
+    "positive_examples": ["youtu.be/CtweZ8ULo78?start=30&end=40", "youtu.be/NiHk39QzgVc?start=90&end=100", "youtu.be/iT9zHI02zDo?start=160&end=170"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/046dlr",
+    "name": "Alarm clock",
+    "description": "Sounds made by a clock that is designed to make an audible signal at a specific time. The primary use of alarm clocks is to awaken people from their night's sleep.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Alarm_clock",
+    "positive_examples": ["youtu.be/q8i4B6lSshE?start=30&end=40", "youtu.be/fqQHxi-CBwY?start=20&end=30", "youtu.be/WSNtES6nmRI?start=50&end=60", "youtu.be/61X1X_LmORw?start=90&end=100", "youtu.be/stiK2hvKAeA?start=24&end=34"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03kmc9",
+    "name": "Siren",
+    "description": "The sound of a loud noise-making device used to provide warnings to people nearby. A siren typically consists of a single pitch that changes either smoothly or abruptly on timescales around one second.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Siren_(alarm)",
+    "positive_examples": ["youtu.be/ZHnpad4e8rI?start=16&end=26", "youtu.be/bUmokBhoTlw?start=29&end=39", "youtu.be/kn09Reh4DZc?start=30&end=40", "youtu.be/BaZiXQC0aAw?start=30&end=40", "youtu.be/BxXcX0kuZTI?start=4&end=14", "youtu.be/b1dvYzcVcKA?start=30&end=40", "youtu.be/6g-ttVYeOX4?start=180&end=190", "youtu.be/o3nq59MHsTU?start=30&end=40", "youtu.be/Cldv-kSc7kU?start=30&end=40", "youtu.be/KjO-sgL8_10?start=60&end=70"],
+    "child_ids": ["/m/04qvtq", "/m/012n7d", "/m/012ndj", "/m/0dgbq"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0dgbq",
+    "name": "Civil defense siren",
+    "description": "The sound of a siren used to provide emergency population warning of approaching danger such as hurricanes, earthquakes, or military attacks.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Civil_defense_siren",
+    "positive_examples": ["youtu.be/ExSi3SDF45o?start=30&end=40", "youtu.be/wVbDqtAXCug?start=30&end=40", "youtu.be/AY7UQYV1GpM?start=30&end=40", "youtu.be/fsaCfxi_VAs?start=30&end=40", "youtu.be/Xy4aPDjvXkQ?start=400&end=410", "youtu.be/rM4XSEZw-ug?start=30&end=40", "youtu.be/Q3ckbWJ9aI4?start=260&end=270", "youtu.be/Kc2-IHeqq0o?start=30&end=40", "youtu.be/8A30tAwXdzM?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/030rvx",
+    "name": "Buzzer",
+    "description": "Sounds of a mechanical, electromechanical, or piezoelectric signaling device that emits a steady, highly-audible tone with a spectrum extending to high frequencies.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Buzzer",
+    "positive_examples": ["youtu.be/-uuG4ZCJmyU?start=30&end=40", "youtu.be/3Ab0sgelCEw?start=30&end=40", "youtu.be/eJM8xH6ny28?start=30&end=40", "youtu.be/OtaGvBD1oEc?start=30&end=40", "youtu.be/Nbmc0U5HPl0?start=270&end=280", "youtu.be/xqOErPbPZFQ?start=70&end=80", "youtu.be/L3vuNVEuZeQ?start=20&end=30", "youtu.be/vaz3zMS8Cus?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01y3hg",
+    "name": "Smoke detector, smoke alarm",
+    "description": "Sounds emitted by a device that senses smoke, typically to warn of a fire.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Smoke_detector",
+    "positive_examples": ["youtu.be/6CzgrjobyzQ?start=30&end=40", "youtu.be/BRnPYH9WHSM?start=30&end=40", "youtu.be/YmsNoKDfWUE?start=120&end=130", "youtu.be/acoqKEVczug?start=19&end=29"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0c3f7m",
+    "name": "Fire alarm",
+    "description": "Sounds of a system designed to warn people when smoke, fire, carbon monoxide or other emergencies are present. Alarms can be either motorized bells or wall-mountable sounders or horns.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Fire_alarm_system",
+    "positive_examples": ["youtu.be/NyT8rRl6nd8?start=8&end=18", "youtu.be/oy-ZMaQbe9c?start=210&end=220", "youtu.be/Q9qGvtK8bBs?start=10&end=20", "youtu.be/e0cGR8OojpQ?start=50&end=60", "youtu.be/ZDxoinMcZj0?start=30&end=40", "youtu.be/AdW3WsQy7QY?start=170&end=180", "youtu.be/4xcSq8UjPCI?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04fq5q",
+    "name": "Foghorn",
+    "description": "A signaling sound used primarily in foggy conditions to warn watercraft of the presence of nearby vessels or other navigational hazards.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Foghorn",
+    "positive_examples": ["youtu.be/0kgiYfKS_qE?start=30&end=40", "youtu.be/siWV-9iulHI?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0l156k",
+    "name": "Whistle",
+    "description": "The sound of an instrument that produces sound from a stream of forced air.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Whistle",
+    "positive_examples": ["youtu.be/zUbqCMZvqP4?start=330&end=340", "youtu.be/mVpQrw3yWuc?start=20&end=30", "youtu.be/wMor1YCRU4E?start=270&end=280"],
+    "child_ids": ["/g/11b630rrvh", "/m/06hck5"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06hck5",
+    "name": "Steam whistle",
+    "description": "The sound of a device used to produce sound with the aid of live steam, which acts as a vibrating system.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Steam_whistle",
+    "positive_examples": ["youtu.be/4t7Mi3pnSA4?start=100&end=110", "youtu.be/00iiNF4tn4o?start=20&end=30", "youtu.be/E5DNG4kVPeg?start=20&end=30", "youtu.be/7kSxwHZYrL4?start=400&end=410", "youtu.be/VSVhZ2aDjro?start=30&end=40", "youtu.be/2FkfQgDiW_o?start=369&end=379"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00077",
+    "name": "Mechanisms",
+    "description": "Sounds that originate from human-created machinery and devices.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/5K6zvn-Zdw0?start=1&end=11", "youtu.be/EFB1v8UGXZk?start=590&end=600", "youtu.be/wY3hhIqVvjo?start=60&end=70", "youtu.be/kcqmwG_rHFA?start=80&end=90"],
+    "child_ids": ["/m/02bm9n", "/m/01x3z", "/m/0l7xg", "/m/05zc1", "/m/0llzx", "/m/02x984l", "/m/025wky1", "/m/024dl", "/m/01m4t", "/m/0dv5r"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02bm9n",
+    "name": "Ratchet, pawl",
+    "description": "The sound of a mechanical device that allows continuous linear or rotary motion in only one direction while preventing motion in the opposite direction.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Ratchet_(device)",
+    "positive_examples": ["youtu.be/CGk8RdSyKVs?start=30&end=40", "youtu.be/6Ks0uENycv4?start=1&end=11", "youtu.be/7S55nEHxIHE?start=30&end=40", "youtu.be/V2M4UI7O0Jo?start=0&end=6", "youtu.be/I3z4A5M-XEQ?start=4&end=14"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01x3z",
+    "name": "Clock",
+    "description": "Sounds made by an instrument designed to keep and indicate time.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Clock",
+    "positive_examples": ["youtu.be/iq62ay8Lv4o?start=450&end=460", "youtu.be/FuWDfaQjbvs?start=150&end=160", "youtu.be/CJCwr2gl2CM?start=120&end=130", "youtu.be/G40Kohywqh4?start=20&end=30", "youtu.be/CuOWQr1a5-c?start=120&end=130", "youtu.be/G23Me3A60b8?start=20&end=30", "youtu.be/Qda2h9SXacs?start=20&end=30", "youtu.be/OL63NVm1v7A?start=20&end=30"],
+    "child_ids": ["/m/07qjznt", "/m/07qjznl"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qjznt",
+    "name": "Tick",
+    "description": "A metallic tapping sound.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=tick",
+    "positive_examples": ["youtu.be/aTcKrIlKI9o?start=30&end=40", "youtu.be/y-hd-Ol4ES4?start=30&end=40", "youtu.be/GgpH6htMmQQ?start=30&end=40", "youtu.be/xNZ0aU2X5uQ?start=30&end=40", "youtu.be/R6VUgJzDwBQ?start=30&end=40", "youtu.be/WupBieE-8Us?start=30&end=40", "youtu.be/YKtbQkTmvnY?start=30&end=40", "youtu.be/t6Hlse8lKmg?start=20&end=30", "youtu.be/8nS-KGITte8?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qjznl",
+    "name": "Tick-tock",
+    "description": "A steady recurrent ticking sound as made by a clock.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=ticktock",
+    "positive_examples": ["youtu.be/gD5Pft3FKdU?start=8&end=18", "youtu.be/wRnYhBhofVY?start=30&end=40", "youtu.be/pDjj6MiFNuc?start=30&end=40", "youtu.be/4ftDFi4684Y?start=30&end=40", "youtu.be/y5cRJZB83ZA?start=4&end=14"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0l7xg",
+    "name": "Gears",
+    "description": "Sounds of rotating machine parts having cut teeth, or cogs, which mesh with other toothed parts to transmit torque.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Gear",
+    "positive_examples": ["youtu.be/0HGFcukxF9Q?start=30&end=40", "youtu.be/0xyapQxC7yM?start=30&end=40", "youtu.be/3EnkJZx4b94?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05zc1",
+    "name": "Pulleys",
+    "description": "Sounds of a wheel on an axle or shaft that is designed to support movement and change of direction of a taut cable or belt along its circumference.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Pulley",
+    "positive_examples": ["youtu.be/LYbzpPSQLbI?start=30&end=40", "youtu.be/j7KrjKwz1VY?start=30&end=40", "youtu.be/OuKRNNbgsGc?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0llzx",
+    "name": "Sewing machine",
+    "description": "Sounds of a machine used to stitch fabric and other materials together with thread.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sewing_machine",
+    "positive_examples": ["youtu.be/3ejlQ7u5kkU?start=220&end=230", "youtu.be/x7ROZ8Lps2k?start=130&end=140", "youtu.be/DMbLpqQlYjc?start=30&end=40", "youtu.be/r9MHNEIYNBY?start=80&end=90", "youtu.be/9ZjoQLYo03Y?start=130&end=140", "youtu.be/qZMkCBSNzLo?start=450&end=460", "youtu.be/AfZTLVMTAD4?start=30&end=40", "youtu.be/4GYEVk6ngdk?start=40&end=50", "youtu.be/4zEP9py4ZO0?start=310&end=320"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02x984l",
+    "name": "Mechanical fan",
+    "description": "Sounds of a machine used to create air flow via the motion of a rotating arrangement of vanes or blades.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Mechanical_fan",
+    "positive_examples": ["youtu.be/DwTfsGSG3y8?start=30&end=40", "youtu.be/3qeBcAw5T8U?start=240&end=250", "youtu.be/ESeWXm2Obnc?start=60&end=70", "youtu.be/S5KErFSn92w?start=210&end=220", "youtu.be/rJZo6erXckU?start=180&end=190", "youtu.be/ZVtm-Pw6gJU?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/025wky1",
+    "name": "Air conditioning",
+    "description": "The sound of a device that removes heat from the air inside a building or vehicle, thus lowering the air temperature.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Air_conditioning",
+    "positive_examples": ["youtu.be/wRBGmik5Dz0?start=160&end=170", "youtu.be/xBxsVs1BQh0?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/024dl",
+    "name": "Cash register",
+    "description": "Sounds of a mechanical or electronic device for registering and calculating transactions, usually attached to a drawer for storing cash.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cash_register",
+    "positive_examples": ["youtu.be/OY5485e1_yM?start=30&end=40", "youtu.be/mJiXm0TbS1w?start=460&end=470", "youtu.be/w3wyawCHZOM?start=110&end=120", "youtu.be/nvY30V3-kD8?start=250&end=260", "youtu.be/Wb3ZTFSc7bc?start=120&end=130", "youtu.be/GuFTgsvMAUc?start=23&end=33", "youtu.be/twQ9-kxoJ70?start=10&end=20", "youtu.be/dXKql7mi4rU?start=60&end=70"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01m4t",
+    "name": "Printer",
+    "description": "Sounds of a computer peripheral which makes a persistent human readable representation of graphics or text on paper or similar physical media.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Printer_(computing)",
+    "positive_examples": ["youtu.be/NjDe3O45xjI?start=470&end=480", "youtu.be/xCK4-CaqGBw?start=40&end=50", "youtu.be/4uSbpeUmxAk?start=30&end=40", "youtu.be/mRtqC_FswFc?start=30&end=40", "youtu.be/7BzyG8MV_zs?start=30&end=40", "youtu.be/MFFrOFlAXQ8?start=30&end=40", "youtu.be/1qkdvq7Qlsc?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0dv5r",
+    "name": "Camera",
+    "description": "Sounds of mechanical or electronic instruments that employ optics to record or capture images.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Camera",
+    "positive_examples": ["youtu.be/sH33P94VpZQ?start=50&end=60", "youtu.be/QdGg7SIlTj8?start=350&end=360", "youtu.be/eF7BVZza7qg?start=390&end=400", "youtu.be/bq8-CK-dXfY?start=40&end=50", "youtu.be/djy4CXMXZls?start=310&end=320", "youtu.be/mYmn4kAwLG8?start=300&end=310", "youtu.be/a4eISIE97EU?start=260&end=270", "youtu.be/APJEtvVrv1Q?start=30&end=40", "youtu.be/vQwg9vG_7E0?start=40&end=50"],
+    "child_ids": ["/m/07bjf"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07bjf",
+    "name": "Single-lens reflex camera",
+    "description": "Sounds of camera that uses a mirror and prism system to permit the photographer to view through the lens and see exactly what will be captured.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Single-lens_reflex_camera",
+    "positive_examples": ["youtu.be/7o2YlSlfLp8?start=30&end=40", "youtu.be/9hzWgd8CNoI?start=30&end=40", "youtu.be/4bibld_jSR0?start=30&end=40", "youtu.be/51pSJYU7wdU?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07k1x",
+    "name": "Tools",
+    "description": "Sounds associated with any physical item that can be used to achieve a goal, especially if the item is not consumed in the process.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Tool",
+    "positive_examples": ["youtu.be/6EvqESUDuh4?start=150&end=160", "youtu.be/--hYWyUh_BY?start=30&end=40", "youtu.be/GJhuBSoQeRg?start=170&end=180", "youtu.be/gnytgNTz4Tw?start=460&end=470", "youtu.be/YpjgUzOBWSM?start=420&end=430", "youtu.be/WpeT6stfbac?start=40&end=50", "youtu.be/itFDsYrpdQ4?start=80&end=90", "youtu.be/5I8lmN8rwDM?start=540&end=550", "youtu.be/bE2hGIuk3nE?start=20&end=30"],
+    "child_ids": ["/m/03l9g", "/m/03p19w", "/m/01b82r", "/m/02p01q", "/m/023vsd", "/m/0_ksk"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03l9g",
+    "name": "Hammer",
+    "description": "Sounds made by a tool or device that delivers a blow to an object. Most hammers are hand tools used to drive nails, fit parts, forge metal, and break apart objects.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Hammer",
+    "positive_examples": ["youtu.be/DPWTr_fAamU?start=50&end=60", "youtu.be/gwz2RRFSp_I?start=70&end=80", "youtu.be/UJubaPeUu58?start=100&end=110", "youtu.be/rUyjioYts8k?start=220&end=230", "youtu.be/hqeM4MaM8AY?start=270&end=280", "youtu.be/QnKuwMUYhIo?start=120&end=130", "youtu.be/oy_ZYPJ_i4U?start=130&end=140"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/03p19w",
+    "name": "Jackhammer",
+    "description": "The sound of a pneumatic or electro-mechanical tool that combines a hammer directly with a chisel, usually used to break up rock, pavement, and concrete.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Jackhammer",
+    "positive_examples": ["youtu.be/D8ZGG2r9rw4?start=70&end=80", "youtu.be/9PXlmLwYdSU?start=30&end=40", "youtu.be/2OVIxKp0tDY?start=30&end=40", "youtu.be/4qWfY_x6hpA?start=20&end=30", "youtu.be/2_MZIyjeHkg?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01b82r",
+    "name": "Sawing",
+    "description": "Sounds of a tool consisting of a tough blade, wire, or chain with a hard toothed edge, used to cut through material, most often wood.  Includes both manual and motorized saws.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Saw",
+    "positive_examples": ["youtu.be/2cA6U33DhmU?start=21&end=31", "youtu.be/IIrxuKxXgbI?start=50&end=60", "youtu.be/4UhoP_5tq-8?start=40&end=50", "youtu.be/CZbwyN1DAUU?start=30&end=40", "youtu.be/dSdfeqU-CHE?start=390&end=400", "youtu.be/tHaynxVvo0k?start=30&end=40", "youtu.be/KkO1_TZkPmA?start=70&end=80"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02p01q",
+    "name": "Filing (rasp)",
+    "description": "Sounds of a common wood- and metal-working tool used to remove fine amounts of material from a workpiece.",
+    "citation_uri": "http://en.wikipedia.org/wiki/File_(tool)",
+    "positive_examples": ["youtu.be/WvLRozv0VO8?start=480&end=490", "youtu.be/xobSVmWsS3M?start=230&end=240", "youtu.be/bmlAZ217IeQ?start=390&end=400", "youtu.be/QsuVk4wgxVA?start=210&end=220", "youtu.be/1lkHxuNt0ys?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/023vsd",
+    "name": "Sanding",
+    "description": "The sounds of a surface being scraped by an abrasive material affixed to sheets of paper or cloth, either to make the surface smoother, remove a layer of material, or sometimes to make the surface rougher.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sandpaper",
+    "positive_examples": ["youtu.be/5f2ygkdBhXQ?start=180&end=190", "youtu.be/gq3mrdhrUco?start=370&end=380", "youtu.be/6KPXNKlaAo8?start=60&end=70", "youtu.be/6SjftAv04VM?start=440&end=450", "youtu.be/l4raHxFuVIU?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0_ksk",
+    "name": "Power tool",
+    "description": "Sounds of tools that employ a power source other than the manual labor used with hand tools. The most common types of power tools use electric motors.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Power_tool",
+    "positive_examples": ["youtu.be/xcqLleK10js?start=50&end=60", "youtu.be/awcVolHHBHA?start=100&end=110", "youtu.be/AVst_gI8r0Y?start=130&end=140", "youtu.be/c7WBUf2Rslg?start=300&end=310", "youtu.be/iXJ6cCkogvA?start=130&end=140", "youtu.be/w7Ar6TrvBiE?start=460&end=470", "youtu.be/ggP0GzUehZ8?start=100&end=110", "youtu.be/pPbaKEYpP-4?start=60&end=70", "youtu.be/oQA78VCxa2U?start=60&end=70"],
+    "child_ids": ["/m/01d380"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01d380",
+    "name": "Drill",
+    "description": "Sounds of a tool used for making holes in various materials via a rotating drill bit.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Drill",
+    "positive_examples": ["youtu.be/2hYNQDynVrY?start=20&end=30", "youtu.be/g2Q3U2nID1o?start=50&end=60", "youtu.be/0zfWGqDMT04?start=60&end=70", "youtu.be/g_tNcWk39d8?start=20&end=30", "youtu.be/MDWok2Z9eK8?start=100&end=110", "youtu.be/-XoJN3kzimY?start=90&end=100"],
+    "child_ids": ["/m/08j51y"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/014zdl",
+    "name": "Explosion",
+    "description": "The sound of a rapid increase in volume and release of energy in an extreme manner, usually with the generation of high temperatures and the release of gases.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Explosion",
+    "positive_examples": ["youtu.be/PrLxgTuUFMM?start=30&end=40", "youtu.be/kQpyLZEenDs?start=280&end=290", "youtu.be/ir1XTdyt4IY?start=18&end=28", "youtu.be/T_ZCW1gW9MY?start=21&end=31", "youtu.be/V6oQYxXbUGs?start=30&end=40", "youtu.be/52P29_VwBT0?start=30&end=40", "youtu.be/1LYnGafjSfs?start=30&end=40", "youtu.be/BG7QfANwqsw?start=170&end=180"],
+    "child_ids": ["/m/032s66", "/m/0g6b5", "/m/07qsvvw", "/m/07pxg6y", "/m/07qqyl4"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/032s66",
+    "name": "Gunshot, gunfire",
+    "description": "The sound of the discharge of a firearm, or multiple such discharges.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Gunshot",
+    "positive_examples": ["youtu.be/--PG66A3lo4?start=80&end=90", "youtu.be/PKEhOxE-Ovs?start=130&end=140", "youtu.be/c9030y4sJo0?start=140&end=150", "youtu.be/6slrju_ar9U?start=290&end=300", "youtu.be/K1cnDXbkPu0?start=170&end=180", "youtu.be/AjIQf3HK_Vc?start=130&end=140", "youtu.be/klCJfirqUF8?start=30&end=40", "youtu.be/Ma65O2T_hN0?start=10&end=20", "youtu.be/-Ho5tDtuah0?start=50&end=60"],
+    "child_ids": ["/m/04zjc", "/m/02z32qm", "/m/0_1c", "/m/073cg4"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04zjc",
+    "name": "Machine gun",
+    "description": "Sounds of a fully automatic mounted or portable firearm, designed to fire bullets in quick succession from an ammunition belt or magazine, typically at a rate of 300 to 1800 rounds per minute.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Machine_gun",
+    "positive_examples": ["youtu.be/CMsuBmtxj1c?start=50&end=60", "youtu.be/DFVVjacIPJc?start=40&end=50", "youtu.be/HrQ_2pDcXgk?start=200&end=210", "youtu.be/YGzn9Xn-hxU?start=540&end=550"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/02z32qm",
+    "name": "Fusillade",
+    "description": "The sound of the simultaneous and continuous firing of a group of firearms on command.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Fusillade",
+    "positive_examples": ["youtu.be/7ZrDUuR6jhQ?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0_1c",
+    "name": "Artillery fire",
+    "description": "The sound of large military weapons built to fire munitions far beyond the range and power of infantry's small arms.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Artillery",
+    "positive_examples": ["youtu.be/PqXCkCGMd_Y?start=30&end=40", "youtu.be/pEDafzZbNwE?start=30&end=40", "youtu.be/RaSAyTj1oQ8?start=22&end=32", "youtu.be/SoDJkvxOYKA?start=30&end=40", "youtu.be/ZtK9HZGMyDo?start=30&end=40", "youtu.be/7G0L7iR1J30?start=30&end=40", "youtu.be/v6BTFTJnkN8?start=30&end=40", "youtu.be/DmfwH6q4nSA?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/073cg4",
+    "name": "Cap gun",
+    "description": "The sound of a toy gun that creates a loud sound simulating a gunshot and a puff of smoke when a small percussion cap is exploded.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Cap_gun",
+    "positive_examples": ["youtu.be/0Hnrufry54I?start=11&end=21", "youtu.be/a4nkA0NL4Hw?start=0&end=9", "youtu.be/s14pZzKGsdE?start=30&end=40", "youtu.be/FTPLIbmvoSs?start=140&end=150"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0g6b5",
+    "name": "Fireworks",
+    "description": "Sounds of a class of low explosive pyrotechnic devices used for aesthetic and entertainment purposes.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Fireworks",
+    "positive_examples": ["youtu.be/cWgHxozrrVg?start=30&end=40", "youtu.be/PtNDWxRjBwU?start=90&end=100", "youtu.be/e6GFJxUv6WQ?start=450&end=460", "youtu.be/3Eexn6Q-S0g?start=4&end=14", "youtu.be/Y0P1S-mEMR4?start=180&end=190", "youtu.be/AW8HjiOEwjk?start=20&end=30", "youtu.be/SFdFVOilebk?start=10&end=20", "youtu.be/JUBUL74vtjs?start=270&end=280", "youtu.be/H8K9xauYZSM?start=340&end=350"],
+    "child_ids": ["/g/122z_qxw"],
+    "restrictions": []
+  },
+  {
+    "id": "/g/122z_qxw",
+    "name": "Firecracker",
+    "description": "The sound of a small explosive device primarily designed to produce a large amount of noise, especially in the form of a loud bang.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Firecracker",
+    "positive_examples": ["youtu.be/HA1QdosEauQ?start=230&end=240", "youtu.be/H6xfwBVAk8k?start=10&end=20", "youtu.be/2He2w7av5Zc?start=50&end=60", "youtu.be/eUIUHMSS870?start=20&end=30", "youtu.be/AfSs1ULO6so?start=40&end=50", "youtu.be/7_GIrU0H3FA?start=290&end=300"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qsvvw",
+    "name": "Burst, pop",
+    "description": "The sound of an enclosure holding gas or liquid coming open suddenly and violently.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=burst",
+    "positive_examples": ["youtu.be/RpFDag_WTi4?start=30&end=40", "youtu.be/s-tz_tCHzWo?start=10&end=20", "youtu.be/Ozzhq8roq54?start=15&end=25", "youtu.be/MXOe4NZQCvg?start=8&end=18"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pxg6y",
+    "name": "Eruption",
+    "description": "The sound of a volcano violently ejecting ash and lava, or a similar event in which large volumes of material are explosively released.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=eruption",
+    "positive_examples": ["youtu.be/2b4c8PGpqhI?start=30&end=40", "youtu.be/0bD6alaQ8p4?start=540&end=550"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qqyl4",
+    "name": "Boom",
+    "description": "A deep prolonged loud noise.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=boom",
+    "positive_examples": ["youtu.be/txZ0Ka2JQxo?start=60&end=70", "youtu.be/j2iXdCbRD1w?start=110&end=120", "youtu.be/CrurGAJGFEo?start=570&end=580", "youtu.be/mPA-o61cmsU?start=530&end=540", "youtu.be/bdLPcIBg1jQ?start=70&end=80", "youtu.be/HJrMrPOFwMw?start=270&end=280", "youtu.be/rRft1-LuYFE?start=370&end=380", "youtu.be/EUk1c1LphAU?start=130&end=140"],
+    "child_ids": ["/m/0193bn"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0193bn",
+    "name": "Sonic boom",
+    "description": "The sound associated with the shock waves created by an object traveling through the air faster than the speed of sound.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sonic_boom",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/083vt",
+    "name": "Wood",
+    "description": "Sounds associated with the porous and fibrous structural tissue found in the stems and roots of trees, and other woody plants.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Wood",
+    "positive_examples": ["youtu.be/6uw4VuJaiyU?start=200&end=210", "youtu.be/0xiCiydk7Z8?start=50&end=60", "youtu.be/ZiWvhIbB7JU?start=110&end=120", "youtu.be/Hy2zg9K4iWw?start=230&end=240", "youtu.be/Dc7Uago6dTo?start=120&end=130", "youtu.be/DPpeWsDmMqM?start=430&end=440"],
+    "child_ids": ["/m/07pczhz", "/m/07pl1bw", "/m/07qs1cx", "/m/07pc8l3"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pczhz",
+    "name": "Chop",
+    "description": "The sound of cutting a solid material such as wood into smaller pieces by using an ax or other hacking tool.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=chop",
+    "positive_examples": ["youtu.be/TgnBMRMoqiU?start=30&end=40", "youtu.be/GSNkf-1GPSQ?start=30&end=40", "youtu.be/RswPwZBfRi4?start=80&end=90"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pl1bw",
+    "name": "Splinter",
+    "description": "The sound of a rigid fibrous material, typically wood, breaking up into splinters or slivers.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=splinter",
+    "positive_examples": ["youtu.be/KXhwErBuMgY?start=30&end=40", "youtu.be/2zKFMrXOIIM?start=30&end=40", "youtu.be/1vTcgIFYqS0?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qs1cx",
+    "name": "Crack",
+    "description": "Abrupt sounds of individual ruptures in a rigid substance under stress.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=crack",
+    "positive_examples": ["youtu.be/7uOf0j0P8HU?start=30&end=40", "youtu.be/RnwN5cfvtm4?start=30&end=40", "youtu.be/3bGqkpfyk6k?start=230&end=240", "youtu.be/oRINjxOZKt8?start=150&end=160"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pc8l3",
+    "name": "Snap",
+    "description": "The sound of a thin and rigid element breaking suddenly and abruptly.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=snap",
+    "positive_examples": ["youtu.be/NuMmJD2JrBI?start=30&end=40", "youtu.be/aJP8tmE_77E?start=3&end=13", "youtu.be/Cw1OYx8S4-Y?start=30&end=40", "youtu.be/FCkRdsB6a-U?start=0&end=9", "youtu.be/GxtlETpVSYU?start=8&end=18"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/039jq",
+    "name": "Glass",
+    "description": "Sounds associated with the non-crystalline amorphous solid that is often transparent and has widespread practical, technological, and decorative uses.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Glass",
+    "positive_examples": ["youtu.be/PN10dchsywY?start=70&end=80", "youtu.be/LBbNXGVJCWw?start=110&end=120", "youtu.be/uN7Hp-Yk8OQ?start=330&end=340", "youtu.be/VWPIFiqTHWs?start=180&end=190", "youtu.be/n3cOIGJUlPQ?start=530&end=540", "youtu.be/723KuaTtsVc?start=50&end=60", "youtu.be/E1QaQHjCAv4?start=230&end=240", "youtu.be/qlnoKIMMWm4?start=110&end=120", "youtu.be/LT5wHi8Atmg?start=70&end=80"],
+    "child_ids": ["/m/07q7njn", "/m/07rn7sz"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07q7njn",
+    "name": "Chink, clink",
+    "description": "A short light metallic sound.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=chink",
+    "positive_examples": ["youtu.be/MtzyuvdvfpQ?start=2&end=12", "youtu.be/N8YbmQ_YvW4?start=30&end=40", "youtu.be/aWsU1yATn5U?start=8&end=18", "youtu.be/5YhaZSsAQ6M?start=70&end=80", "youtu.be/8-qDda-c6yo?start=30&end=40", "youtu.be/8efvnCaFuzQ?start=17&end=27"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rn7sz",
+    "name": "Shatter",
+    "description": "The sound of a brittle rigid substance rapidly breaking into many pieces.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=shatter",
+    "positive_examples": ["youtu.be/rBUWlPPHunk?start=50&end=60", "youtu.be/gkac73Rq7dU?start=350&end=360", "youtu.be/PDtzyKfzAc8?start=180&end=190", "youtu.be/_O0n0l_tL1Q?start=150&end=160", "youtu.be/1d4ASeSEXVI?start=220&end=230"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04k94",
+    "name": "Liquid",
+    "description": "Sounds of a fluid that conforms to the shape of its container but retains a constant volume independent of pressure.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Liquid",
+    "positive_examples": ["youtu.be/5ntpW4iXtP8?start=70&end=80", "youtu.be/ES8lAqq8cSg?start=270&end=280", "youtu.be/EvNPF1oGjPQ?start=10&end=20", "youtu.be/vKLoUE_DBVQ?start=230&end=240", "youtu.be/1QkOu15rjXM?start=40&end=50", "youtu.be/EyOMSnIc9SY?start=440&end=450", "youtu.be/qtKiqaRZ9x8?start=10&end=20"],
+    "child_ids": ["/m/07rrlb6", "/m/07qlwh6", "/m/07r5v4s", "/m/07prgkl", "/m/07p7b8y", "/m/07qlf79", "/m/07ptzwd", "/m/07ptfmf", "/m/0dv3j"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rrlb6",
+    "name": "Splash, splatter",
+    "description": "The sound of a liquid colliding with a hard surface.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=splash",
+    "positive_examples": ["youtu.be/rFF12MllDhg?start=210&end=220", "youtu.be/whfUQXL3luQ?start=10&end=20", "youtu.be/IOwEFjW1ReU?start=50&end=60", "youtu.be/S-p4PzFB_mI?start=20&end=30", "youtu.be/XdSCT_cQDbE?start=10&end=20", "youtu.be/sW4wBBH37qA?start=10&end=20"],
+    "child_ids": ["/m/07p6mqd"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07p6mqd",
+    "name": "Slosh",
+    "description": "The sound of small waves of liquid held in a container breaking against the edges.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=slosh",
+    "positive_examples": ["youtu.be/1vvxtLJFbzk?start=140&end=150", "youtu.be/0D_D7pd2Auk?start=210&end=220", "youtu.be/0y5ZMfoo3EI?start=30&end=40", "youtu.be/8BmJ_BAnf-k?start=100&end=110", "youtu.be/i_IwowmdAOg?start=30&end=40", "youtu.be/5CjCEFSCFuw?start=30&end=40", "youtu.be/DlMgXSJq1vg?start=180&end=190"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qlwh6",
+    "name": "Squish",
+    "description": "Sounds made by a liquid-saturated material being squeezed.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=squish",
+    "positive_examples": ["youtu.be/3EmVk33-7ng?start=30&end=40", "youtu.be/H8COAreN7CI?start=30&end=40", "youtu.be/1oH7EmcORMk?start=30&end=40", "youtu.be/Wf2-FDI22Xg?start=220&end=230", "youtu.be/0Lr0d7HoFRQ?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r5v4s",
+    "name": "Drip",
+    "description": "The sound of liquid falling in drops.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=drip",
+    "positive_examples": ["youtu.be/egSo8OqYcak?start=190&end=200", "youtu.be/RiIo5obGWgQ?start=70&end=80", "youtu.be/WUOXH-9cfbM?start=30&end=40", "youtu.be/mqSklGvTBo0?start=60&end=70"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07prgkl",
+    "name": "Pour",
+    "description": "The sound of liquid being transferred in a steady stream.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=pour",
+    "positive_examples": ["youtu.be/vSwJupCXq6g?start=10&end=20", "youtu.be/klF5jHsp2rs?start=150&end=160", "youtu.be/7NBoEcVv0U8?start=70&end=80", "youtu.be/_WHA4Awjq1Q?start=200&end=210", "youtu.be/IAP0Hr4zJcE?start=570&end=580", "youtu.be/lIWoEaiHEV8?start=380&end=390", "youtu.be/qavftbteuzU?start=570&end=580", "youtu.be/laey-lg_NQ4?start=470&end=480"],
+    "child_ids": ["/m/07pqc89", "/t/dd00088"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pqc89",
+    "name": "Trickle, dribble",
+    "description": "The sound of a liquid flowing slowly in an unsteady stream or drops.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=trickle",
+    "positive_examples": ["youtu.be/KatU7SuscEU?start=130&end=140", "youtu.be/5-26yY_4M6c?start=590&end=600", "youtu.be/zMEi4gB_m_0?start=30&end=40", "youtu.be/j8TblDlV7ms?start=120&end=130"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00088",
+    "name": "Gush",
+    "description": "The sound of a liquid coming out of a pipe or other opening rapidly and in large volumes.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/nb-qnjlexk4?start=200&end=210", "youtu.be/es8e2wKAyAg?start=110&end=120"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07p7b8y",
+    "name": "Fill (with liquid)",
+    "description": "The sound of a container being filled with liquid.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=fill",
+    "positive_examples": ["youtu.be/XDEoGiMbmtc?start=270&end=280", "youtu.be/ZoW4eL72fYA?start=210&end=220", "youtu.be/KRXChlhyrrw?start=120&end=130", "youtu.be/A8up3toh8Js?start=250&end=260", "youtu.be/ZM-nZ8Yh9b0?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qlf79",
+    "name": "Spray",
+    "description": "The sound of a liquid being transferred in a scatter or jet of droplets.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=spray",
+    "positive_examples": ["youtu.be/YDbxVJEFyvI?start=14&end=24", "youtu.be/wKByBE9Gy_8?start=500&end=510", "youtu.be/yq6m58KXxcs?start=30&end=40", "youtu.be/FYW1xkJBWBE?start=10&end=20", "youtu.be/UTsDmkLU7Og?start=30&end=40", "youtu.be/04EocSVWMoM?start=30&end=40", "youtu.be/6sYf3-kmw0k?start=30&end=40", "youtu.be/nsEhTV5-e2s?start=27&end=37"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07ptzwd",
+    "name": "Pump (liquid)",
+    "description": "The sound of a liquid being drawn or poured with a pump.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=pump",
+    "positive_examples": ["youtu.be/7bhWazNlIAY?start=370&end=380", "youtu.be/yQLgFJ3T51Q?start=180&end=190", "youtu.be/8W7uDxY5nB4?start=30&end=40", "youtu.be/k2CCMOJ2ubY?start=90&end=100", "youtu.be/sfkMAdEyB4c?start=140&end=150", "youtu.be/hZ9a8YVFOmo?start=30&end=40", "youtu.be/5Fc4wjBLQeM?start=300&end=310", "youtu.be/JGmCVlieEj0?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07ptfmf",
+    "name": "Stir",
+    "description": "The sound of moving an implement through a fluid substance.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=stir",
+    "positive_examples": ["youtu.be/USAby5e7hwI?start=30&end=40", "youtu.be/5hUK9ubSMZU?start=300&end=310", "youtu.be/KHSsK-2wDIo?start=240&end=250", "youtu.be/6DXtiywoWyQ?start=300&end=310", "youtu.be/3AmLt4xnIg8?start=200&end=210", "youtu.be/cNcj8z_wv7E?start=270&end=280"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0dv3j",
+    "name": "Boiling",
+    "description": "The sound of a liquid that is reaching the temperature at which it transitions to a vapor, resulting in bubbles emerging at the surface.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Boiling",
+    "positive_examples": ["youtu.be/inTsmf3BslU?start=180&end=190", "youtu.be/PPadmzjMODM?start=30&end=40", "youtu.be/7asRT4sLUMw?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00089",
+    "name": "Miscellaneous sources",
+    "description": "Portmanteau class for sound categories that clearly suggest specific sources not covered in the other categories.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/0790c", "/m/04179zz", "/m/0dl83", "/t/dd00091"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/0790c",
+    "name": "Sonar",
+    "description": "Sounds associated with underwater sensing via acoustic signals. A classic sonar sound involves reverberant reflections of an emitted tone pip.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sonar",
+    "positive_examples": ["youtu.be/_l2qH62qG-Y?start=30&end=40", "youtu.be/rbN9akpEJh4?start=40&end=50", "youtu.be/f47LeLK_ucU?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/04179zz",
+    "name": "Duck call (hunting tool)",
+    "description": "The sound of a tool which imitates the communication calls of waterfowl and is used primarily by hunters to lure prey.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Duck_call",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0dl83",
+    "name": "Arrow",
+    "description": "Sounds of a shafted projectile that is shot with a bow.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Arrow",
+    "positive_examples": ["youtu.be/STeG7lU2seQ?start=70&end=80", "youtu.be/uFROlibANvw?start=40&end=50", "youtu.be/AAdoBK3LG_s?start=110&end=120", "youtu.be/SgZSBDALO1k?start=210&end=220", "youtu.be/sb4VwqX1Wss?start=130&end=140", "youtu.be/lPbA3GnfWDQ?start=30&end=40", "youtu.be/KP74BeNnPjU?start=60&end=70", "youtu.be/FfMwEVBCmaQ?start=360&end=370"],
+    "child_ids": ["/m/07rqsjt", "/m/07qnq_y", "/m/07pk7mg"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rqsjt",
+    "name": "Whoosh, swoosh, swish",
+    "description": "A sibilant sound caused by a rigid object sweeping through the air.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=whoosh",
+    "positive_examples": ["youtu.be/jRocgDvVV6U?start=30&end=40", "youtu.be/-xuq3kOwGGw?start=30&end=40", "youtu.be/HuoE9pT4DFw?start=0&end=5", "youtu.be/DdMAiFT2dIY?start=30&end=40", "youtu.be/1SDz3QpoPRk?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qnq_y",
+    "name": "Thump, thud",
+    "description": "A heavy dull sound, as made by impact of heavy objects with a relatively soft point of contact.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=thump",
+    "positive_examples": ["youtu.be/t6rniZNuoM4?start=60&end=70", "youtu.be/t4Q8i_J-Fos?start=50&end=60", "youtu.be/gNMsHIMAHXs?start=280&end=290", "youtu.be/StjeR1EIv0A?start=410&end=420", "youtu.be/b4a1SE8pJtw?start=150&end=160", "youtu.be/cx8hGMuV5Ok?start=420&end=430", "youtu.be/NLilfM4RVOA?start=50&end=60", "youtu.be/_FDKLplMbf4?start=320&end=330"],
+    "child_ids": ["/m/07rrh0c", "/t/dd00108"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rrh0c",
+    "name": "Thunk",
+    "description": "A partly dull hollow sound with a damped resonance.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=thunk",
+    "positive_examples": ["youtu.be/Ze1hkRWoz-M?start=110&end=120", "youtu.be/txiZk4ap_4c?start=100&end=110", "youtu.be/e57je4YO9cM?start=230&end=240", "youtu.be/DPI_-objvnY?start=110&end=120", "youtu.be/Q4mvcscgRdA?start=30&end=40", "youtu.be/HzQphRe4bgM?start=130&end=140", "youtu.be/qD9Uvxrq63U?start=100&end=110"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00108",
+    "name": "Clunk",
+    "description": "A predominantly low-frequency impact noise that starts with a cleaner, high-frequency click, suggesting the contact of rigid surfaces (as of a car door closing).",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/x-dLBbkPEKA?start=26&end=36", "youtu.be/fdD2UwvJdC4?start=20&end=30", "youtu.be/p-nnE3kbpCQ?start=30&end=40", "youtu.be/KULfVYWeYgw?start=30&end=40", "youtu.be/d3-_V1rijLo?start=20&end=30", "youtu.be/otLsSpCumO8?start=30&end=40", "youtu.be/aQ7m0KUB0xY?start=30&end=40", "youtu.be/HTQ7u3pcdYs?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pk7mg",
+    "name": "Wobble",
+    "description": "The sound of a structure shaking unsteadily back and forth, as in response to an impact.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=wobble",
+    "positive_examples": ["youtu.be/AesYVC3ej1g?start=340&end=350"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00091",
+    "name": "Sound equipment",
+    "description": "Sounds that suggest the involvement of electronic audio processing equipment.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/a_eC1dvlFyQ?start=60&end=70", "youtu.be/yZJCg_RBPpg?start=290&end=300", "youtu.be/wJsvxEHIUwc?start=280&end=290", "youtu.be/UEDM20GlRlA?start=10&end=20", "youtu.be/oEr9yy3dx-w?start=100&end=110"],
+    "child_ids": ["/m/0hg7b", "/m/0b_fwt", "/m/01vfsf", "/m/02rr_"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/0hg7b",
+    "name": "Microphone",
+    "description": "Sounds whose origin lie with the microphone used in the recording, rather than the external sound source that was intended to be recorded.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Microphone",
+    "positive_examples": [],
+    "child_ids": ["/t/dd00092"],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0b_fwt",
+    "name": "Electronic tuner",
+    "description": "Sounds produced by an electronic device whose purpose is to aid in the tuning of musical instruments.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Electronic_tuner",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/01vfsf",
+    "name": "Guitar amplifier",
+    "description": "Sounds specifically associated with an audio amplifier intended for use with an electric guitar, such as overdrive distortion.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Guitar_amplifier",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/02rr_",
+    "name": "Effects unit",
+    "description": "Sounds associated with an electronic device that alters how a musical instrument or other audio source sounds. Some effects subtly \"color\" a sound while others transform it dramatically.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Effects_unit",
+    "positive_examples": ["youtu.be/aAmyLNfCbyo?start=580&end=590", "youtu.be/7lTBoMcuy10?start=190&end=200", "youtu.be/ND-Fs2VaFL0?start=30&end=40", "youtu.be/8FiXfyDdaZo?start=160&end=170", "youtu.be/thvxJisK52g?start=50&end=60", "youtu.be/PFr8GwUVzfw?start=300&end=310", "youtu.be/GsAUcq1V2HY?start=30&end=40", "youtu.be/UMkFu4MsDjc?start=160&end=170"],
+    "child_ids": ["/m/07m2kt"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07m2kt",
+    "name": "Chorus effect",
+    "description": "The ensemble sound produced by an electronic effects unit which outputs simultaneous versions of the input source with small variations in pitch and timbre.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Chorus_effect",
+    "positive_examples": ["youtu.be/QK200gvvi68?start=60&end=70", "youtu.be/XXzpCKOVswg?start=200&end=210", "youtu.be/vKNGqQ3GRB8?start=90&end=100"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00133",
+    "name": "Specific impact sounds",
+    "description": "Transient contact sounds that are strongly suggestive of the particular objects involved in the collision.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/018w8"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/018w8",
+    "name": "Basketball bounce",
+    "description": "The sound of a basketball bouncing on a hard surface, such as a basketball court.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Basketball",
+    "positive_examples": ["youtu.be/-64NRxM2YLg?start=60&end=70", "youtu.be/2Tg8LHzMOgs?start=150&end=160", "youtu.be/WXtRxqxRIHQ?start=50&end=60", "youtu.be/zjxL61AXNTI?start=60&end=70", "youtu.be/ZGYGusrK84E?start=220&end=230", "youtu.be/GUSqE3a1P3I?start=100&end=110"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00098",
+    "name": "Source-ambiguous sounds",
+    "description": "Portmanteau class for sounds that do not immediately suggest specific source objects, but which are more likely to be perceived and described according to their acoustic properties.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/t/dd00099", "/t/dd00109", "/t/dd00110", "/m/05n1m", "/m/028v0c", "/t/dd00122"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/t/dd00099",
+    "name": "Generic impact sounds",
+    "description": "Sounds of impacts or collisions preferentially described by their acoustic properties, rather than by immediately referring to their assumed source object(s).",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/07pws3f", "/m/07ryjzk", "/m/07rdhzs", "/m/07pjjrj", "/m/07pc8lb", "/m/07pqn27", "/m/07r4wb8", "/m/07qcpgn", "/m/07qnq_y", "/m/07rbp7_", "/m/07pyf11"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/07pws3f",
+    "name": "Bang",
+    "description": "A brief and loud noise.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=bang",
+    "positive_examples": ["youtu.be/0zsRRg6NZDQ?start=21&end=31", "youtu.be/ayhkvgG1Cvw?start=210&end=220", "youtu.be/Oe6sYXWAM7E?start=90&end=100", "youtu.be/rhG_ie69Nwc?start=300&end=310"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07ryjzk",
+    "name": "Slap, smack",
+    "description": "The sharp sound of a flat object striking another (e.g., an open hand hitting a face).",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=slap",
+    "positive_examples": ["youtu.be/-gfaj2Evqus?start=290&end=300", "youtu.be/KDQV3eSkhZ4?start=70&end=80", "youtu.be/toWBIJlu2NM?start=80&end=90", "youtu.be/yjEZx7TvwcA?start=60&end=70", "youtu.be/kasvqBhDBC0?start=240&end=250", "youtu.be/ls_QsNFNDbg?start=10&end=20", "youtu.be/v-Al9LqV9Mo?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rdhzs",
+    "name": "Whack, thwack",
+    "description": "The sound of a partially rigid object forcefully striking another object, which may be preceded by the sound of the rapid, driven motion of one object (as of a baseball bat hitting a ball).",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=whack",
+    "positive_examples": ["youtu.be/redtHVmxs7s?start=30&end=40", "youtu.be/dVi2QoAYsAQ?start=180&end=190", "youtu.be/aB5CD4u16gM?start=40&end=50", "youtu.be/zruJV_pq4z0?start=270&end=280", "youtu.be/e-lOchEQ1i0?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pjjrj",
+    "name": "Smash, crash",
+    "description": "The sound of a rigid structure violently breaking into many pieces.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=smash",
+    "positive_examples": ["youtu.be/-3MV6T3u9Ig?start=30&end=40", "youtu.be/-DTgp1cbyug?start=0&end=2", "youtu.be/Ywc4_D3sKHQ?start=30&end=40", "youtu.be/PBTPWOf_E-w?start=250&end=260", "youtu.be/c0nVFint5bk?start=160&end=170", "youtu.be/5lLMWk_-fQw?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pc8lb",
+    "name": "Breaking",
+    "description": "The sound of a rigid object become separated into pieces or fragments.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=break",
+    "positive_examples": ["youtu.be/frZUEXzWE5Q?start=30&end=40", "youtu.be/1SAdEjaSf3g?start=6&end=16", "youtu.be/mKTTCj3WrLg?start=30&end=40", "youtu.be/LF-070rGEbQ?start=230&end=240", "youtu.be/FeaKHpQ4UhE?start=90&end=100", "youtu.be/wyv4blKX3No?start=390&end=400"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pqn27",
+    "name": "Bouncing",
+    "description": "The sound of an elastic, non-destructive collision in which one or both objects spring back. Depending on the situation, there may be multiple such collisions in a characteristic pattern, as of a ball bouncing.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=bounce",
+    "positive_examples": ["youtu.be/Tk2v1UaTgmk?start=40&end=50", "youtu.be/Od85JwO7ChQ?start=10&end=20", "youtu.be/FSVfPifghQ4?start=50&end=60", "youtu.be/00XaUxjGuX8?start=170&end=180", "youtu.be/BKnuN5hoZnM?start=40&end=50", "youtu.be/QErefA2Ms4c?start=390&end=400", "youtu.be/tHcW8l5ifLQ?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rbp7_",
+    "name": "Whip",
+    "description": "The sound of whipping, i.e., the greatly accelerated motion of the tip of a flexible structure, as the result of concentrated angular momentum.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=whip",
+    "positive_examples": ["youtu.be/LhbzdtNRTKs?start=30&end=40", "youtu.be/ivoEsA_OErY?start=30&end=40", "youtu.be/9qMbQFMHA5g?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pyf11",
+    "name": "Flap",
+    "description": "The noisy sound of a flexible surface, such as a flag, moving back-and-forth in the air and optionally coming into contact with an adjacent hard surface.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=flap",
+    "positive_examples": ["youtu.be/-1MpcvB9PAI?start=30&end=40", "youtu.be/M3301jxTkto?start=5&end=15", "youtu.be/7dIIVzcYhD4?start=310&end=320"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00109",
+    "name": "Surface contact",
+    "description": "Sounds produced by a more extended interaction between two objects or surfaces instead of a collision or bounce.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/07qb_dv", "/m/07qv4k0", "/m/07pdjhy", "/m/07s8j8t", "/m/07pt6mm"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/07qb_dv",
+    "name": "Scratch",
+    "description": "The sound of a hard, sharp point of contact leaving a permanent groove in a hard surface.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=scratch",
+    "positive_examples": ["youtu.be/tgHySwhil9s?start=50&end=60", "youtu.be/Y9R0M2gQE04?start=30&end=40", "youtu.be/yUEDrDKIYV0?start=450&end=460", "youtu.be/7GapruwcCO0?start=300&end=310", "youtu.be/NG_Pa0_Rc74?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qv4k0",
+    "name": "Scrape",
+    "description": "The sound of a hard edge dragging across a surface.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=scrape",
+    "positive_examples": ["youtu.be/CDXoMKXrn58?start=30&end=40", "youtu.be/SAVRtzEodx4?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pdjhy",
+    "name": "Rub",
+    "description": "The sound of two surfaces moving smoothly over each other with pressure but without excessive friction.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=rub",
+    "positive_examples": ["youtu.be/LSEjPSU7wSA?start=210&end=220", "youtu.be/hngBJnxLVmQ?start=180&end=190", "youtu.be/AXsR125JDEA?start=520&end=530", "youtu.be/fHmROtp_U00?start=410&end=420", "youtu.be/MDPCZrtDl5c?start=450&end=460", "youtu.be/cLuDhdm-1tc?start=20&end=30", "youtu.be/H5nQnPCk0Uo?start=100&end=110", "youtu.be/4ugXkiWI-7A?start=25&end=35"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07s8j8t",
+    "name": "Roll",
+    "description": "The sound of an object moving by turning over or rotating.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=roll",
+    "positive_examples": ["youtu.be/2TE4hAMo9EE?start=4&end=14", "youtu.be/3250CBWhvWE?start=30&end=40", "youtu.be/45fwQe0d62o?start=30&end=40", "youtu.be/Fx0tr98DzN8?start=0&end=8", "youtu.be/OoAtJAR6qto?start=0&end=5"],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/07pt6mm",
+    "name": "Grind",
+    "description": "The sound of a substance being reduced to small pieces or particles by pounding or abrading, or the sound of two surfaces rubbing with high friction that suggests that one or both surfaces are being disintergrated.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=grind",
+    "positive_examples": ["youtu.be/6jborgl8I1c?start=30&end=40", "youtu.be/KcNqclVaRCg?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00110",
+    "name": "Deformable shell",
+    "description": "Sounds that are associated with shells, rigid sheets, or other predominantly two-dimensional surfaces.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/07plct2", "/t/dd00112", "/m/07qcx4z"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/07plct2",
+    "name": "Crushing",
+    "description": "The sound of a brittle, rigid structure breaking into small pieces or catastrophically deforming.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=crush",
+    "positive_examples": ["youtu.be/-LRl10YdS-U?start=30&end=40", "youtu.be/R9aRI18jBsg?start=40&end=50", "youtu.be/0bbgeqkDm6U?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00112",
+    "name": "Crumpling, crinkling",
+    "description": "The sound of a rigid but flexible sheet, such as paper or aluminum, buckling into a smaller volume.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/R5Sa5FuBghs?start=80&end=90", "youtu.be/A70nDKXBvd0?start=70&end=80", "youtu.be/6oxdgmtwhPo?start=50&end=60", "youtu.be/OZete7K0H9Q?start=100&end=110", "youtu.be/Oceb2JMUNWE?start=40&end=50", "youtu.be/al801VjCvn0?start=150&end=160", "youtu.be/4q8KuEMFfhA?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qcx4z",
+    "name": "Tearing",
+    "description": "The sound of a flat or smooth surface separating abruptly.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=tear",
+    "positive_examples": ["youtu.be/OVt4xBfulms?start=40&end=50", "youtu.be/BIluBHK8DO0?start=70&end=80", "youtu.be/oS8kziiAWTk?start=40&end=50", "youtu.be/xgrsFb35uew?start=440&end=450", "youtu.be/vwze3eMulhs?start=50&end=60"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/05n1m",
+    "name": "Onomatopoeia",
+    "description": "A class of sounds named to phonetically imitate, resemble, or suggest the sound it describes.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Onomatopoeia",
+    "positive_examples": [],
+    "child_ids": ["/t/dd000138", "/m/07rjwbb", "/m/07qh7jl", "/m/07qn4z3", "/m/07rqsjt", "/m/07qwyj0", "/m/07s34ls", "/m/07qmpdm", "/m/07p9k1k", "/m/07qc9xj", "/m/07phhsh", "/m/07r_r9m", "/m/07qyrcz", "/m/07qfgpx", "/t/dd00118", "/m/07q34h3", "/m/07rcgpl", "/m/07qlwh6", "/m/07p78v5", "/t/dd00121", "/m/07pzfmf", "/m/07s12q4", "/m/07qs1cx", "/m/07pc8l3"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/t/dd000138",
+    "name": "Brief tone",
+    "description": "Short-duration sounds composed of strong harmonics with a distinct pitch.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/02fs_r", "/m/07qwdck", "/m/07phxs1", "/m/07rv4dm", "/m/07rpk1c", "/m/07pggtn", "/m/07pjwq1", "/m/07q6cd_", "/m/07s02z0", "/m/07q8k13"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/02fs_r",
+    "name": "Beep, bleep",
+    "description": "A short, single tone, generally made by a computer or other machine and typically high-pitched.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Beep_(sound)",
+    "positive_examples": ["youtu.be/iAKUYTMv23Y?start=55&end=65", "youtu.be/EotkYg493i0?start=7&end=17", "youtu.be/XnfPKj7_y4c?start=20&end=30", "youtu.be/l5CEprbZ0OE?start=30&end=40", "youtu.be/ht4cuUz_X14?start=60&end=70", "youtu.be/Q7Ohn9lAM0s?start=8&end=18", "youtu.be/jBVlmCUGv3M?start=30&end=40", "youtu.be/YmtRXXJribE?start=170&end=180", "youtu.be/SlUOFN4uc2I?start=14&end=24"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qwdck",
+    "name": "Ping",
+    "description": "A sharp high-pitched resonant sound with a clear decay.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=ping",
+    "positive_examples": ["youtu.be/FiSh0F3XnxM?start=30&end=40", "youtu.be/N1ZKrgbnGAk?start=10&end=20", "youtu.be/CkfqM_atyeI?start=90&end=100", "youtu.be/Pln4GLIMqKY?start=30&end=40", "youtu.be/2f3h6QRLyDk?start=30&end=40", "youtu.be/rnNdkwGZph0?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07phxs1",
+    "name": "Ding",
+    "description": "A high-pitched ringing sound, as of a small metal object being struck.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=ding",
+    "positive_examples": ["youtu.be/sjW5I8bhufY?start=7&end=17", "youtu.be/9ejLc44MJCY?start=50&end=60", "youtu.be/KiByOwi-V7w?start=110&end=120", "youtu.be/lLaooX_97tM?start=120&end=130", "youtu.be/khT36zSVvtg?start=140&end=150", "youtu.be/93VprpYqN4o?start=160&end=170"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rv4dm",
+    "name": "Clang",
+    "description": "A loud, resonant, discordant noise, as of a large and partly hollow metal structure begin struck.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=clang",
+    "positive_examples": ["youtu.be/eG_CHAeuu0A?start=70&end=80", "youtu.be/sIdGNeRCUHg?start=30&end=40", "youtu.be/10sNKRTjv4Q?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rpk1c",
+    "name": "Twang",
+    "description": "A sharp, vibrating sound, as of a branch whipping back into shape, or a bow after releasing an arrow.  Musical plucked strings are not included.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=twang",
+    "positive_examples": ["youtu.be/eqox9z6yadA?start=0&end=2", "youtu.be/xlO2Wy86Jys?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07s02z0",
+    "name": "Squeal",
+    "description": "A short, high-pitched tone without a sharp attack and with a perceptible variation in pitch.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=squeal",
+    "positive_examples": ["youtu.be/VLcAu0p8NE4?start=210&end=220", "youtu.be/RKUGuaVaW4Q?start=230&end=240", "youtu.be/TAl6LU38u8M?start=30&end=40", "youtu.be/2gx1koonRlE?start=100&end=110"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07q8k13",
+    "name": "Screech",
+    "description": "A high-pitched noise with a rough quality resembling the cry of a human or other animal.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=screech",
+    "positive_examples": ["youtu.be/0nCj9XmrqGQ?start=2&end=12"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qh7jl",
+    "name": "Creak",
+    "description": "A high-pitched noise with a perceptible variation in pitch as a result of pressure being shifted or applied on a surface, most commonly on wood.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=creak",
+    "positive_examples": ["youtu.be/572i4h3JcnU?start=210&end=220", "youtu.be/Cl_EaIRJRtM?start=29&end=39", "youtu.be/1z1sXjQ6Szs?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qwyj0",
+    "name": "Rustle",
+    "description": "A sound of light, thin objects, such as dried leaves, rubbing against one another.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=rustle",
+    "positive_examples": ["youtu.be/-8vMtYGbkN0?start=30&end=40", "youtu.be/8EhFLlt7Rnk?start=30&end=40", "youtu.be/84uFe8TgQmY?start=80&end=90", "youtu.be/HmbYRIsQFRE?start=0&end=8", "youtu.be/JwA0-o35yBQ?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07s34ls",
+    "name": "Whir",
+    "description": "A quiet sound of a small object, typically mechanical, in rapid, cyclic motion.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=whir",
+    "positive_examples": ["youtu.be/yFpW-T9dDUY?start=30&end=40", "youtu.be/Qf0_UKxpPl8?start=30&end=40", "youtu.be/FBPLX-RS0zY?start=30&end=40", "youtu.be/lXG4YpTn8pE?start=30&end=40", "youtu.be/BI4fjQBZliY?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qmpdm",
+    "name": "Clatter",
+    "description": "An irregular rattling noise, often produced by rapid movement, consisting of a cluster of transient sounds.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=clatter",
+    "positive_examples": ["youtu.be/3cZ1A6osRZg?start=5&end=15", "youtu.be/vrnIFkMSokk?start=17&end=27"],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/07p9k1k",
+    "name": "Sizzle",
+    "description": "The sound of many small bubbles bursting, most often caused by fat vaporizing as it is heated.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=sizzle",
+    "positive_examples": ["youtu.be/1HGzcj92CEE?start=210&end=220", "youtu.be/AqrSHCCehgY?start=30&end=40", "youtu.be/7rLP0ZG0Fps?start=390&end=400", "youtu.be/quO3yc9wxOg?start=30&end=40", "youtu.be/USAby5e7hwI?start=20&end=30", "youtu.be/pYbP2qDmtlY?start=170&end=180", "youtu.be/J1KvjY6dhOA?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qc9xj",
+    "name": "Clicking",
+    "description": "A short, pitchless, transient sound, as of a gentle impact between small hard objects.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=click",
+    "positive_examples": ["youtu.be/U58FSo_rAhI?start=370&end=380", "youtu.be/MR1pVYnWERs?start=180&end=190", "youtu.be/GkpLUcvxKSw?start=430&end=440", "youtu.be/iF8uTeM79LY?start=480&end=490", "youtu.be/7iYtmGtabDk?start=500&end=510", "youtu.be/f3nsAF4s6mY?start=450&end=460"],
+    "child_ids": ["/m/07qjznt", "/m/07rv9rh", "/m/07rwm0c"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rwm0c",
+    "name": "Clickety-clack",
+    "description": "The sound of fast and rhythmic clicking of machinery, such as keystrokes on a typewriter or steel wheels running on tracks.  Does not include the sound of horses feet (use /m/07rv9rh).",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=clickety-clack",
+    "positive_examples": ["youtu.be/xIKrqNqSyy4?start=13&end=23", "youtu.be/eM0Xs-NQwLM?start=460&end=470", "youtu.be/BW-0GDDoxFI?start=30&end=40", "youtu.be/1vt9phoCrdY?start=40&end=50", "youtu.be/ZiGOglchf5E?start=170&end=180", "youtu.be/4ZRm2_XWgSo?start=8&end=18"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07phhsh",
+    "name": "Rumble",
+    "description": "A loud, low-pitched, dull, continuous noise.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=rumble",
+    "positive_examples": ["youtu.be/EKsUrMobexk?start=60&end=70", "youtu.be/Ex56cROdjss?start=170&end=180", "youtu.be/nF3DgONcYSQ?start=30&end=40", "youtu.be/dpIMT_E53ss?start=10&end=20", "youtu.be/YhOccauNQtA?start=90&end=100", "youtu.be/O3N2oUBWUjo?start=6&end=16", "youtu.be/Br_tSpJoQSg?start=90&end=100"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07r_r9m",
+    "name": "Blare",
+    "description": "A loud harsh or strident noise, often a warning sound.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=blare",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/07qyrcz",
+    "name": "Plop",
+    "description": "The sound of a small object dropping into a liquid without a splash.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=plop",
+    "positive_examples": ["youtu.be/1leOTk_mzdA?start=20&end=30", "youtu.be/I2uWNEkXy3o?start=200&end=210"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07qfgpx",
+    "name": "Jingle, tinkle",
+    "description": "An irregular pattern of short metallic sounds, especially from small metal objects such as keys or coins shaking against each other.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=jingle",
+    "positive_examples": ["youtu.be/EW3ZkpsGNBA?start=10&end=20", "youtu.be/q7oAC59AP9c?start=1&end=11", "youtu.be/rcjv5ARPGMc?start=30&end=40", "youtu.be/gS_lDm2zjak?start=0&end=10"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00118",
+    "name": "Fizz",
+    "description": "The sound of the popping of many small bubbles, most often as gas is released from solution, such as in a carbonated beverage.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/bvEA9WionJc?start=20&end=30", "youtu.be/Cy56gEufE7E?start=170&end=180", "youtu.be/X4S4paFuHX4?start=110&end=120"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07q34h3",
+    "name": "Puff",
+    "description": "The sound of a gas, such as air, being blown forcefully in a short burst.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=puff",
+    "positive_examples": ["youtu.be/igrJbMKwioI?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07rcgpl",
+    "name": "Hum",
+    "description": "A continuous, dull tone.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=hum",
+    "positive_examples": ["youtu.be/WxxeWEBoVys?start=30&end=40", "youtu.be/cDVmKSYc4HY?start=240&end=250", "youtu.be/0R6KIVvlyfQ?start=30&end=40", "youtu.be/tHfn-Hc-kRE?start=120&end=130"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07p78v5",
+    "name": "Zing",
+    "description": "A brief high-pitched buzzing or humming sound.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=zing",
+    "positive_examples": ["youtu.be/rTuTeQVEcDs?start=30&end=40", "youtu.be/F7Kf8aTJbOU?start=30&end=40", "youtu.be/FmcdlDqtrFQ?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00121",
+    "name": "Boing",
+    "description": "A bouncing or spring-like sound with a tonal component that sweeps upwards.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/p1lMVPToEY0?start=210&end=220", "youtu.be/agLvQZD7Wr4?start=590&end=600", "youtu.be/1levp6fUO28?start=260&end=270", "youtu.be/D5fDXY7RxR0?start=20&end=30", "youtu.be/iYbA-P5Y8Rk?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07s12q4",
+    "name": "Crunch",
+    "description": "The sound of a brittle substance being crushed.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=crunch",
+    "positive_examples": ["youtu.be/7iKYHaoItuU?start=30&end=40", "youtu.be/Vx_5MCemF0o?start=540&end=550", "youtu.be/EvR0XweufUs?start=30&end=40", "youtu.be/9ao5CaBafF4?start=210&end=220", "youtu.be/Am1ipsgofdg?start=520&end=530", "youtu.be/k0iBnLQjdxo?start=100&end=110", "youtu.be/J6P5zKL3tu4?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/028v0c",
+    "name": "Silence",
+    "description": "The absence of audible sound or presence of sounds of very low intensity.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Silence",
+    "positive_examples": ["youtu.be/Jwjk9wxUoPg?start=200&end=210", "youtu.be/JZMj1suEC4g?start=290&end=300", "youtu.be/ITOF0fX8NjY?start=200&end=210", "youtu.be/u7Mq0AX6TRU?start=200&end=210", "youtu.be/Wyoj8hAUAtc?start=290&end=300", "youtu.be/m7jdjVxj4Gc?start=30&end=40", "youtu.be/4N2FV9ZuusU?start=140&end=150", "youtu.be/KrN-TxlSkT8?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00122",
+    "name": "Other sourceless",
+    "description": "A class for sound categories not represented by other classes that are peceived by their sound instead of their source.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/m/01v_m0", "/m/0c1dj", "/m/07pt_g0", "/m/01fhw5", "/m/017gp", "/m/05szwhw"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/01v_m0",
+    "name": "Sine wave",
+    "description": "A continuous, pure tone of fixed pitch and amplitude.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sine_wave",
+    "positive_examples": ["youtu.be/0FOegaxNaqk?start=210&end=220", "youtu.be/Z2SmKZVU-cE?start=60&end=70", "youtu.be/kFz9rZjCFkQ?start=30&end=40", "youtu.be/iVPrW-aRC_s?start=80&end=90", "youtu.be/4mfg3_dVVaU?start=20&end=30"],
+    "child_ids": ["/m/0b9m1", "/m/0hdsk"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0b9m1",
+    "name": "Harmonic",
+    "description": "A sine tone whose frequency is an integer multiple of some fundamental tone.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Harmonic",
+    "positive_examples": ["youtu.be/TWnrcjA6VTk?start=60&end=70"],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0hdsk",
+    "name": "Chirp tone",
+    "description": "A tone whose frequency increases or decreases with time.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Chirp",
+    "positive_examples": ["youtu.be/-kE7IL6pnKU?start=20&end=30"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0c1dj",
+    "name": "Sound effect",
+    "description": "An artificially created or enhanced sound used to emphasize artistic or other content of films, television shows, live performances, animation, video games, music, or other media.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sound_effect",
+    "positive_examples": ["youtu.be/-1cGAf0KSvo?start=1&end=11", "youtu.be/-25RvGqa7wQ?start=30&end=40", "youtu.be/-DoFDKsAOo4?start=30&end=40", "youtu.be/-Ia8FPe6GDE?start=0&end=6", "youtu.be/-TDBk9Unpuc?start=240&end=250", "youtu.be/-Th_4dhrDaM?start=9&end=19", "youtu.be/-bX_9jVt6hQ?start=30&end=40", "youtu.be/XgMWhtZ7ugo?start=310&end=320"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07pt_g0",
+    "name": "Pulse",
+    "description": "A sound that is modulated in short, regular bursts at approximately 1 Hz.  This class is not for heartbeat sounds, use /m/01jg02.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=pulse",
+    "positive_examples": ["youtu.be/_CM-Opj41xk?start=160&end=170", "youtu.be/SCf5rx_OyYM?start=100&end=110", "youtu.be/dQvTJnthAV8?start=80&end=90", "youtu.be/fRwmCHUBjBQ?start=380&end=390"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01fhw5",
+    "name": "Infrasound",
+    "description": "A sound of very low frequency (e.g., below 20 Hz) such that is not perceived, or barely perceived, by human listeners.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Infrasound",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/017gp",
+    "name": "Bass (frequency range)",
+    "description": "Low frequency sound energy in the range from 16-256 Hz.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Bass_(sound)",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/05szwhw",
+    "name": "Ringing (of resonator)",
+    "description": "The sound of a simple linear resonator in free oscillation in response to an impulse of excitation, usually ending in an exponentially decaying sine tone.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Ringing_(signal)",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/t/dd00123",
+    "name": "Channel, environment and background",
+    "description": "A class for sound categories that suggest information about attributes other than the foreground or target objects.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/t/dd00093", "/m/096m7z", "/m/07bm98"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/t/dd00093",
+    "name": "Acoustic environment",
+    "description": "A class for sounds that convey the spatiality of the recording.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": ["/t/dd00125", "/t/dd00126", "/t/dd00127", "/t/dd00128", "/t/dd00129", "/m/01b9nn", "/m/01jnbd"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/t/dd00125",
+    "name": "Inside, small room",
+    "description": "Sounds that appear to have been recorded within a small room, such as one that can accommodate no more than 15 people.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/eqWF_TDX4NM?start=190&end=200", "youtu.be/rLqyFZBYlD4?start=410&end=420", "youtu.be/k3_EmfJcNaY?start=100&end=110", "youtu.be/-vxWG4YoKZM?start=120&end=130", "youtu.be/ONXKc7AVfNY?start=310&end=320", "youtu.be/QZ9oN_zqEdc?start=310&end=320", "youtu.be/L7GtX6Kvr4s?start=60&end=70", "youtu.be/oIoaqgtM9NU?start=80&end=90"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00126",
+    "name": "Inside, large room or hall",
+    "description": "Sounds that appear to have been recorded in a large room or hall, often with clearly perceptible reverberation.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/2Jddu5vI4QY?start=70&end=80", "youtu.be/avlwY9gdjV0?start=240&end=250", "youtu.be/a4jcJ7QZ-OQ?start=150&end=160", "youtu.be/KPq-sqU58-Y?start=100&end=110", "youtu.be/zPMchtKMXkc?start=100&end=110", "youtu.be/cbirYMm7Vzk?start=420&end=430"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00127",
+    "name": "Inside, public space",
+    "description": "Sounds that appear to have been recorded in a public space such as store, restaurant, or travel terminus, often characterized by both reverberation and continuous background noise.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/d5PnDZ0LMDw?start=510&end=520", "youtu.be/Qtm98j24sQU?start=160&end=170", "youtu.be/GAXY3-A4EU0?start=10&end=20", "youtu.be/6kBgDyL1IPM?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00128",
+    "name": "Outside, urban or manmade",
+    "description": "Sounds that appear to have been recorded outdoors in a human-constructed environment.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/BzVGMdWM27I?start=400&end=410", "youtu.be/n878F0QbyYk?start=90&end=100", "youtu.be/Buf__Z-1cfQ?start=120&end=130", "youtu.be/fdR79DRDZKA?start=30&end=40", "youtu.be/H7V96qPFZ3g?start=40&end=50", "youtu.be/rhtw3CBDw3I?start=10&end=20", "youtu.be/LmsnecVb_GU?start=330&end=340"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/t/dd00129",
+    "name": "Outside, rural or natural",
+    "description": "Sounds that appear to have been recorded outdoors in a natural, non-manmade environment.",
+    "citation_uri": "",
+    "positive_examples": ["youtu.be/9oeGmqm6g8E?start=60&end=70", "youtu.be/-RbwX4LX-2U?start=170&end=180", "youtu.be/PRpUxcQtvNo?start=300&end=310", "youtu.be/FyhUO5Luq6Y?start=290&end=300", "youtu.be/W8qYyw3F5kA?start=520&end=530", "youtu.be/4Ohhodom94c?start=70&end=80", "youtu.be/TtXooTU9_6s?start=100&end=110", "youtu.be/TM9EFeC9ZUk?start=380&end=390", "youtu.be/w2_oQgcIpqI?start=70&end=80"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01b9nn",
+    "name": "Reverberation",
+    "description": "The sound of an acoustic environment that includes substantial reflection from multiple walls or other hard surfaces. Reverberation is generally perceived as being able to 'hear' the presence and size of the room or space in which the sound is made.  The reflected sounds should remain audible for hundreds of milliseconds or longer.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Reverberation",
+    "positive_examples": ["youtu.be/DqM1zpXPUgs?start=520&end=530", "youtu.be/QARJ4o82SrM?start=430&end=440", "youtu.be/f3HnJ2DhIyQ?start=180&end=190", "youtu.be/MsnMRiqmouI?start=170&end=180", "youtu.be/HpLcGBgPh5s?start=110&end=120", "youtu.be/FcHvkDWXPno?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01jnbd",
+    "name": "Echo",
+    "description": "A sound which is a delayed and attenuated repetition of an earlier sound, for example because the sound wave has been reflected back from a distant, planar surface. To be perceived as an echo, the repetion must be delayed by around 100 milliseconds or more.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Echo",
+    "positive_examples": ["youtu.be/OplvFkbmN-8?start=190&end=200", "youtu.be/P6AQcAJG8NU?start=160&end=170", "youtu.be/I3X2Yl0snS4?start=30&end=40", "youtu.be/ijsyajsdSoU?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/096m7z",
+    "name": "Noise",
+    "description": "A sound that has no perceptible structure and that typically interferes with the perception of more interesting or important sounds.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Noise_(radio)",
+    "positive_examples": ["youtu.be/lTiF59wDZ5o?start=100&end=110", "youtu.be/Q_rZIH5_5C0?start=80&end=90", "youtu.be/RjF9D8xDYFg?start=30&end=40"],
+    "child_ids": ["/m/093_4n", "/m/07qfr4h", "/m/07szfh9", "/m/0chx_", "/m/0cj0r", "/m/07p_0gm", "/m/01jwx6"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/093_4n",
+    "name": "Background noise",
+    "description": "Sounds present alongside a sound of interest but typically weaker in energy and generally not of interest.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Background_noise",
+    "positive_examples": ["youtu.be/Ea0mjqDst9E?start=80&end=90", "youtu.be/utMYmua1SkE?start=30&end=40", "youtu.be/hRJM4JH3rjE?start=410&end=420", "youtu.be/qQBAvAZHvAg?start=10&end=20", "youtu.be/tQYVJlOnx8s?start=60&end=70", "youtu.be/f8AwggqxxVM?start=140&end=150"],
+    "child_ids": ["/m/06_y0by", "/m/09d1b1", "/m/07rgkc5", "/m/06xkwv", "/m/0g12c5", "/m/08p9q4"],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06_y0by",
+    "name": "Environmental noise",
+    "description": "The combined sounds of transport, industrial, and recreational activities.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Environmental_noise",
+    "positive_examples": ["youtu.be/LmafBI1fKw0?start=340&end=350", "youtu.be/8_M3lTg3_oU?start=10&end=20", "youtu.be/OEVLtm3IzWw?start=40&end=50"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/09d1b1",
+    "name": "Tape hiss",
+    "description": "A high frequency noise present on analog magnetic tape recordings caused by the size of the magnetic particles used to make the tape.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Tape_hiss",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/07rgkc5",
+    "name": "Static",
+    "description": "A crackling or hissing noise caused by electrical interference.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=static",
+    "positive_examples": ["youtu.be/zQv5mqOaysE?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06xkwv",
+    "name": "Mains hum",
+    "description": "A low, continuous tone caused by electromagnetic interference from the alternating current of the mains electricity. The fundamental frequency of this sound is usually 50 Hz or 60 Hz, depending on the local power-line frequency.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Mains_hum",
+    "positive_examples": ["youtu.be/GH-sJJ04axg?start=520&end=530", "youtu.be/fd3DJ0rY_RU?start=270&end=280", "youtu.be/xf0TIS26BUE?start=70&end=80"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0g12c5",
+    "name": "Distortion",
+    "description": "A sound that has been modified in a nonlinear fashion, usually in electronic equipment, to introduce sound correlated with the original signal. In many cases, notably with amplified electric musical instruments, distortion is introduced as an effect by increasing the gain and clipping the source signal.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Distortion_(music)",
+    "positive_examples": ["youtu.be/EAHYCGhoyM4?start=30&end=40", "youtu.be/MXtktxGEdOY?start=30&end=40", "youtu.be/L2ImCbQsRUk?start=60&end=70", "youtu.be/PaIuJvwzZW8?start=40&end=50", "youtu.be/F1PUkKI4sR0?start=40&end=50", "youtu.be/VCEOxg9ZX24?start=230&end=240"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/08p9q4",
+    "name": "Sidetone",
+    "description": "The audible feedback on a telecommunications channel that allows the speaker to know that the channel is operational.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sidetone",
+    "positive_examples": ["youtu.be/Qmw5vuWbdkM?start=160&end=170", "youtu.be/afnR1C7HTh8?start=30&end=40", "youtu.be/j-8EgxtL-Tw?start=510&end=520"],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/07szfh9",
+    "name": "Cacophony",
+    "description": "A loud, confusing, disagreeable sound, such as many voices shouting simultaneously.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=cacophony",
+    "positive_examples": ["youtu.be/-r4PDh9kiuo?start=90&end=100", "youtu.be/YGTJ2LlaSAQ?start=30&end=40", "youtu.be/ruaeTvNFGTQ?start=530&end=540", "youtu.be/Y-Zxw19hwZQ?start=80&end=90"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0chx_",
+    "name": "White noise",
+    "description": "A random, unstructured sound in which the value at any moment provides no information about the value at any other moment. White noise has equal energy in all frequency bands.",
+    "citation_uri": "http://en.wikipedia.org/wiki/White_noise",
+    "positive_examples": ["youtu.be/IEdT5i6ogWI?start=360&end=370", "youtu.be/4oIp7EgT7B4?start=80&end=90", "youtu.be/G_iWfCQ3fOU?start=110&end=120", "youtu.be/9DKPBZ00Q3A?start=17&end=27"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0cj0r",
+    "name": "Pink noise",
+    "description": "Unstructured noise whose energy decreases with frequency such that equal amounts of energy are distributed in logarithmic bands of frequency, typically octaves.  Pink noise sounds more like a rumble where white noise sounds like a hiss.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Pink_noise",
+    "positive_examples": ["youtu.be/XKNWjAq3xUk?start=162&end=172"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/07p_0gm",
+    "name": "Throbbing",
+    "description": "A dull, continunous sound with a strong rhythmic modulation.",
+    "citation_uri": "http://wordnetweb.princeton.edu/perl/webwn?s=throbbing",
+    "positive_examples": ["youtu.be/K2E-WWG597Q?start=30&end=40", "youtu.be/8Py7bmA96xA?start=30&end=40", "youtu.be/fTE53ntPQf4?start=40&end=50", "youtu.be/nD3ZyFWYlLM?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/01jwx6",
+    "name": "Vibration",
+    "description": "The general class of sounds caused by a periodic mechanical oscillation.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Vibration",
+    "positive_examples": ["youtu.be/-FpGTCaiioc?start=30&end=40", "youtu.be/T_g9P-K-9Ac?start=30&end=40", "youtu.be/LriokFTJZt4?start=40&end=50", "youtu.be/OR2yfr-Cb4Y?start=3&end=13", "youtu.be/CBX4Kl8ibRM?start=30&end=40"],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/07bm98",
+    "name": "Sound reproduction",
+    "description": "A class for sounds that reveal the particular equipment used to capture or reproduce the sound.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Sound_recording_and_reproduction",
+    "positive_examples": [],
+    "child_ids": ["/m/07c52", "/m/06bz3", "/m/0cfpc", "/m/01b7fy", "/m/025l19", "/m/0174nj", "/m/01www", "/m/04zc0"],
+    "restrictions": ["abstract"]
+  },
+  {
+    "id": "/m/07c52",
+    "name": "Television",
+    "description": "A sound that appears to have been produced by a television set.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Television",
+    "positive_examples": ["youtu.be/VrUCCto21RU?start=20&end=30", "youtu.be/zdkybSg9Ddw?start=130&end=140", "youtu.be/irMaO2tcCns?start=260&end=270"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/06bz3",
+    "name": "Radio",
+    "description": "A sound that appears to have been produced by a radio receiver.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Radio",
+    "positive_examples": ["youtu.be/soyKe4M8EUM?start=180&end=190", "youtu.be/E0Q6l3_VTLY?start=590&end=600", "youtu.be/UAT_j1ma23E?start=50&end=60", "youtu.be/MdjoPGi_A2Y?start=110&end=120", "youtu.be/3m2i2PQubjc?start=30&end=40", "youtu.be/AQXT9gOjT4s?start=30&end=40", "youtu.be/ogIv5VmM71Y?start=200&end=210"],
+    "child_ids": [],
+    "restrictions": []
+  },
+  {
+    "id": "/m/0cfpc",
+    "name": "Loudspeaker",
+    "description": "A sound that appears to have been produced by a loudspeaker.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Loudspeaker",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/01b7fy",
+    "name": "Headphones",
+    "description": "A sound that appears to have been produced by headphones.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Headphones",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/025l19",
+    "name": "Recording",
+    "description": "A sound that appears to come from a recording of a sound, rather than the original sound itself.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Recording",
+    "positive_examples": [],
+    "child_ids": ["/m/07hvw1"],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/07hvw1",
+    "name": "Field recording",
+    "description": "A sound that appears to have been recorded in some specific environment, usually with the intention of capturing and representing that environment.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Field_recording",
+    "positive_examples": ["youtu.be/Gxc0gxJpato?start=490&end=500", "youtu.be/2HxnUDbhgFM?start=30&end=40", "youtu.be/6KVFGJVJ6QY?start=18&end=28", "youtu.be/wDGzCV1lJJY?start=190&end=200", "youtu.be/1en9fyEUfYU?start=10&end=20"],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/0174nj",
+    "name": "Gramophone record",
+    "description": "A sound which appears to come from a gramophone or vinyl record disc being played on a turntable.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Gramophone_record",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/01www",
+    "name": "Compact disc",
+    "description": "A sound which appears to come from a digital audio Compact Disc.",
+    "citation_uri": "http://en.wikipedia.org/wiki/Compact_disc",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  },
+  {
+    "id": "/m/04zc0",
+    "name": "MP3",
+    "description": "A sound which appears to come from a compressed digital file using the MP3 format, discernible by containing nearly imperceptible compression artifacts.",
+    "citation_uri": "",
+    "positive_examples": [],
+    "child_ids": [],
+    "restrictions": ["blacklist"]
+  }
+]
diff --git a/AR/exps/beats/quantizer.py b/AR/exps/beats/quantizer.py
new file mode 100644
index 0000000000000000000000000000000000000000..449cbe05ef9845bf64b91b25eddfb49fca5a3618
--- /dev/null
+++ b/AR/exps/beats/quantizer.py
@@ -0,0 +1,235 @@
+# --------------------------------------------------------
+# BEATs: Audio Pre-Training with Acoustic Tokenizers (https://arxiv.org/abs/2212.09058)
+# Github source: https://github.com/microsoft/unilm/tree/master/beats
+# Copyright (c) 2022 Microsoft
+# Licensed under The MIT License [see LICENSE for details]
+# Based on VQGAN code bases
+# https://github.com/CompVis/taming-transformers
+# --------------------------------------------------------'
+import torch
+import torch.distributed as distributed
+import torch.nn as nn
+import torch.nn.functional as F
+
+try:
+    from einops import rearrange, repeat
+except ImportError:
+    pass
+
+
+def l2norm(t):
+    return F.normalize(t, p=2, dim=-1)
+
+
+def ema_inplace(moving_avg, new, decay):
+    moving_avg.data.mul_(decay).add_(new, alpha=(1 - decay))
+
+
+def sample_vectors(samples, num):
+    num_samples, device = samples.shape[0], samples.device
+
+    if num_samples >= num:
+        indices = torch.randperm(num_samples, device=device)[:num]
+    else:
+        indices = torch.randint(0, num_samples, (num, ), device=device)
+
+    return samples[indices]
+
+
+def kmeans(samples, num_clusters, num_iters=10, use_cosine_sim=False):
+    dim, dtype, device = samples.shape[-1], samples.dtype, samples.device
+
+    means = sample_vectors(samples, num_clusters)
+
+    for _ in range(num_iters):
+        if use_cosine_sim:
+            dists = samples @ means.t()
+        else:
+            diffs = rearrange(samples, 'n d -> n () d') \
+                    - rearrange(means, 'c d -> () c d')
+            dists = -(diffs**2).sum(dim=-1)
+
+        buckets = dists.max(dim=-1).indices
+        bins = torch.bincount(buckets, minlength=num_clusters)
+        zero_mask = bins == 0
+        bins_min_clamped = bins.masked_fill(zero_mask, 1)
+
+        new_means = buckets.new_zeros(num_clusters, dim, dtype=dtype)
+        new_means.scatter_add_(0, repeat(buckets, 'n -> n d', d=dim), samples)
+        new_means = new_means / bins_min_clamped[..., None]
+
+        if use_cosine_sim:
+            new_means = l2norm(new_means)
+
+        means = torch.where(zero_mask[..., None], means, new_means)
+
+    return means, bins
+
+
+class EmbeddingEMA(nn.Module):
+    def __init__(self,
+                 num_tokens,
+                 codebook_dim,
+                 decay=0.99,
+                 eps=1e-5,
+                 kmeans_init=True,
+                 codebook_init_path=''):
+        super().__init__()
+        self.num_tokens = num_tokens
+        self.codebook_dim = codebook_dim
+        self.decay = decay
+        self.eps = eps
+        if codebook_init_path == '':
+            if not kmeans_init:
+                weight = torch.randn(num_tokens, codebook_dim)
+                weight = l2norm(weight)
+            else:
+                weight = torch.zeros(num_tokens, codebook_dim)
+            self.register_buffer('initted', torch.Tensor([not kmeans_init]))
+        else:
+            print(f"load init codebook weight from {codebook_init_path}")
+            codebook_ckpt_weight = torch.load(
+                codebook_init_path, map_location='cpu')
+            weight = codebook_ckpt_weight.clone()
+            self.register_buffer('initted', torch.Tensor([True]))
+
+        self.weight = nn.Parameter(weight, requires_grad=False)
+        self.cluster_size = nn.Parameter(
+            torch.zeros(num_tokens), requires_grad=False)
+        self.embed_avg = nn.Parameter(weight.clone(), requires_grad=False)
+        # self.register_buffer('initted', torch.Tensor([not kmeans_init]))
+        self.update = True
+
+    @torch.jit.ignore
+    def init_embed_(self, data):
+        if self.initted:
+            return
+        print("Performing Kemans init for codebook")
+        embed, cluster_size = kmeans(
+            data, self.num_tokens, 10, use_cosine_sim=True)
+        self.weight.data.copy_(embed)
+        self.cluster_size.data.copy_(cluster_size)
+        self.initted.data.copy_(torch.Tensor([True]))
+
+    def forward(self, embed_id):
+        return F.embedding(embed_id, self.weight)
+
+    def cluster_size_ema_update(self, new_cluster_size):
+        self.cluster_size.data.mul_(self.decay).add_(
+            new_cluster_size, alpha=1 - self.decay)
+
+    def embed_avg_ema_update(self, new_embed_avg):
+        self.embed_avg.data.mul_(self.decay).add_(
+            new_embed_avg, alpha=1 - self.decay)
+
+    def weight_update(self, num_tokens):
+        n = self.cluster_size.sum()
+        smoothed_cluster_size = (
+            (self.cluster_size + self.eps) / (n + num_tokens * self.eps) * n)
+        # normalize embedding average with smoothed cluster size
+        embed_normalized = self.embed_avg / smoothed_cluster_size.unsqueeze(1)
+        # embed_normalized = l2norm(self.embed_avg / smoothed_cluster_size.unsqueeze(1))
+        self.weight.data.copy_(embed_normalized)
+
+
+def norm_ema_inplace(moving_avg, new, decay):
+    moving_avg.data.mul_(decay).add_(new, alpha=(1 - decay))
+    moving_avg.data.copy_(l2norm(moving_avg.data))
+
+
+class NormEMAVectorQuantizer(nn.Module):
+    def __init__(self,
+                 n_embed,
+                 embedding_dim,
+                 beta,
+                 decay=0.99,
+                 eps=1e-5,
+                 statistic_code_usage=True,
+                 kmeans_init=False,
+                 codebook_init_path=''):
+        super().__init__()
+        self.codebook_dim = embedding_dim
+        self.num_tokens = n_embed
+        self.beta = beta
+        self.decay = decay
+
+        # learnable = True if orthogonal_reg_weight > 0 else False
+        self.embedding = EmbeddingEMA(self.num_tokens, self.codebook_dim, decay,
+                                      eps, kmeans_init, codebook_init_path)
+
+        self.statistic_code_usage = statistic_code_usage
+        if statistic_code_usage:
+            self.register_buffer('cluster_size', torch.zeros(n_embed))
+        if distributed.is_available() and distributed.is_initialized():
+            print(
+                "ddp is enable, so use ddp_reduce to sync the statistic_code_usage for each gpu!"
+            )
+            self.all_reduce_fn = distributed.all_reduce
+        else:
+            self.all_reduce_fn = nn.Identity()
+
+    def reset_cluster_size(self, device):
+        if self.statistic_code_usage:
+            self.register_buffer('cluster_size', torch.zeros(self.num_tokens))
+            self.cluster_size = self.cluster_size.to(device)
+
+    def forward(self, z):
+        # reshape z -> (batch, height, width, channel) and flatten
+        # z, 'b c h w -> b h w c'
+        # z = rearrange(z, 'b c h w -> b h w c')
+        # z = z.transpose(1, 2)
+        z = l2norm(z)
+        z_flattened = z.reshape(-1, self.codebook_dim)
+
+        self.embedding.init_embed_(z_flattened)
+
+        d = z_flattened.pow(2).sum(dim=1, keepdim=True) + \
+            self.embedding.weight.pow(2).sum(dim=1) - 2 * \
+            torch.einsum('bd,nd->bn', z_flattened, self.embedding.weight)  # 'n d -> d n'
+
+        encoding_indices = torch.argmin(d, dim=1)
+
+        z_q = self.embedding(encoding_indices).view(z.shape)
+
+        encodings = F.one_hot(encoding_indices, self.num_tokens).type(z.dtype)
+
+        if not self.training:
+            with torch.no_grad():
+                cluster_size = encodings.sum(0)
+                self.all_reduce_fn(cluster_size)
+                ema_inplace(self.cluster_size, cluster_size, self.decay)
+
+        if self.training and self.embedding.update:
+            # EMA cluster size
+
+            bins = encodings.sum(0)
+            self.all_reduce_fn(bins)
+
+            # self.embedding.cluster_size_ema_update(bins)
+            ema_inplace(self.cluster_size, bins, self.decay)
+
+            zero_mask = (bins == 0)
+            bins = bins.masked_fill(zero_mask, 1.)
+
+            embed_sum = z_flattened.t() @ encodings
+            self.all_reduce_fn(embed_sum)
+
+            embed_normalized = (embed_sum / bins.unsqueeze(0)).t()
+            embed_normalized = l2norm(embed_normalized)
+
+            embed_normalized = torch.where(
+                zero_mask[..., None], self.embedding.weight, embed_normalized)
+            norm_ema_inplace(self.embedding.weight, embed_normalized,
+                             self.decay)
+
+        # compute loss for embedding
+        loss = self.beta * F.mse_loss(z_q.detach(), z)
+
+        # preserve gradients
+        z_q = z + (z_q - z).detach()
+
+        # reshape back to match original input shape
+        # z_q, 'b h w c -> b c h w'
+        # z_q = rearrange(z_q, 'b h w c -> b c h w')
+        # z_q = z_q.transpose(1, 2)
+        return z_q, loss, encoding_indices
diff --git a/AR/exps/get_beats_librilight.py b/AR/exps/get_beats_librilight.py
new file mode 100644
index 0000000000000000000000000000000000000000..d3a21c47400fe2b564d4f417fe98278991ec27af
--- /dev/null
+++ b/AR/exps/get_beats_librilight.py
@@ -0,0 +1,321 @@
+# Use AudioTag tool BEATs to filter out audios who's top1 tag is not 'speech'
+# non_speech.npy, 存储一个 python dict 表示非 speech 类型的音频的 tag, 更小，加载和搜索速度更快
+# audio_tag 目录存储 {utt_id}.txt, 第一行是小写的 top1 tag 
+import argparse
+import os
+import time
+import traceback
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+
+import librosa
+import numpy as np
+import torch
+import tqdm
+from AR.exps.beats.BEATs import BEATs
+from AR.exps.beats.BEATs import BEATsConfig
+from AR.exps.beats.config import id_name_dict
+from soundstorm.s2.exps.hubert.feature_utils import get_shard_range
+from soundstorm.utils import check_txt_file
+
+
+def get_BEATs_top1(wav,
+                   BEATs_model,
+                   BEATs_label_dict,
+                   device: str='cpu',
+                   topk: int=1):
+    wav = torch.tensor(wav).unsqueeze(0).to(device)
+    padding_mask = torch.zeros(wav.shape).bool().to(device)
+    probs = BEATs_model.extract_features(wav, padding_mask=padding_mask)[0]
+    # 单条推理
+    probs = probs[0]
+    topk_label_prob, topk_label_idx = probs.topk(k=topk)
+    topk_label = [
+        BEATs_label_dict[label_idx.item()] for label_idx in topk_label_idx
+    ]
+    topk_label_name = [id_name_dict[label] for label in topk_label]
+    top1_label = topk_label_name[0]
+    return top1_label
+
+
+def process_sentence(args,
+                     fp: Path,
+                     train_dump_dir: Path,
+                     dev_dump_dir: Path,
+                     test_dump_dir: Path,
+                     VAD_dict,
+                     BEATs_model,
+                     BEATs_label_dict,
+                     device: str='cpu'):
+    utt_id = fp.stem
+    sr = args.sr
+    record = []
+    train_audio_tag_dir = train_dump_dir / "audio_tag"
+    train_audio_tag_dir.mkdir(parents=True, exist_ok=True)
+
+    dev_audio_tag_dir = dev_dump_dir / "audio_tag"
+    dev_audio_tag_dir.mkdir(parents=True, exist_ok=True)
+
+    test_audio_tag_dir = test_dump_dir / "audio_tag"
+    test_audio_tag_dir.mkdir(parents=True, exist_ok=True)
+
+    try:
+        # get info for path
+        wav_path_list = str(fp).strip().split('/')
+        sub_dataset, spk_id, book_name = wav_path_list[-4], wav_path_list[
+            -3], wav_path_list[-2]
+        wav_name = wav_path_list[-1][:-5]
+        assert wav_name == utt_id
+        # key_name for big wav
+        key_name = f'{wav_name}#{sub_dataset}#{spk_id}#{book_name}'
+        # 判断 VAD 字典中不存在该条音频信息的情况
+        if key_name not in VAD_dict.keys():
+            print(key_name, 'not in VAD_dict !')
+            return record
+        wav = None
+        sorted_split_VAD_dict = sorted(VAD_dict[key_name].items())
+        len_dict = len(sorted_split_VAD_dict)
+        for index, item in enumerate(sorted_split_VAD_dict):
+            split_name, value = item
+            start, end = value
+            # train | dev | test
+            if index == len_dict - 1:
+                subset = 'test'
+                audio_tag_path = test_audio_tag_dir / (split_name + ".txt")
+            elif index == len_dict - 2:
+                subset = 'dev'
+                audio_tag_path = dev_audio_tag_dir / (split_name + ".txt")
+            else:
+                subset = 'train'
+                audio_tag_path = train_audio_tag_dir / (split_name + ".txt")
+
+            if os.path.exists(audio_tag_path) and check_txt_file(
+                    audio_tag_path):
+                # print(audio_tag_path, 'exits!')
+                pass
+            else:
+                # 这里加判断保证在 sub wav 的循环中只 load 一次
+                if wav is None:
+                    # load big wav
+                    # 在最外层 load 如果 sub wav 的特征都存在了就会白白消耗 load 的时间
+                    wav, _ = librosa.load(str(fp), sr=sr)
+                sub_wav = wav[int(start * sr):int(end * sr)]
+                audio_tag_top1 = get_BEATs_top1(
+                    wav=sub_wav,
+                    BEATs_model=BEATs_model,
+                    BEATs_label_dict=BEATs_label_dict,
+                    device=device)
+
+                with open(audio_tag_path, 'w') as f:
+                    f.write(audio_tag_top1)
+
+            sub_record = {
+                "utt_id": split_name,
+                "audio_tag_path": audio_tag_path,
+                "subset": subset
+            }
+            # recodrd 变成 List of Dict
+            record.append(sub_record)
+    except Exception:
+        print("occur Exception")
+        traceback.print_exc()
+        # record 有可能是一个不完整的 List
+        return record
+    return record
+
+
+def process_sentences(args,
+                      fps: Path,
+                      train_dump_dir: Path,
+                      dev_dump_dir: Path,
+                      test_dump_dir: Path,
+                      VAD_dict,
+                      BEATs_model,
+                      BEATs_label_dict,
+                      device: str='cpu',
+                      nprocs: int=1):
+    print("nprocs:", nprocs)
+    if nprocs == 1:
+        results = []
+        for fp in tqdm.tqdm(fps, total=len(fps)):
+            record = process_sentence(
+                args=args,
+                fp=fp,
+                train_dump_dir=train_dump_dir,
+                dev_dump_dir=dev_dump_dir,
+                test_dump_dir=test_dump_dir,
+                VAD_dict=VAD_dict,
+                BEATs_model=BEATs_model,
+                BEATs_label_dict=BEATs_label_dict,
+                device=device)
+            if record:
+                results.append(record)
+    else:
+        with ThreadPoolExecutor(nprocs) as pool:
+            futures = []
+            with tqdm.tqdm(total=len(fps)) as progress:
+                for fp in fps:
+                    future = pool.submit(process_sentence, args, fp,
+                                         train_dump_dir, dev_dump_dir,
+                                         test_dump_dir, VAD_dict, BEATs_model,
+                                         BEATs_label_dict, device)
+                    future.add_done_callback(lambda p: progress.update())
+                    futures.append(future)
+
+                results = []
+                for ft in futures:
+                    record = ft.result()
+                    if record:
+                        results.append(record)
+
+    # torch.save() to a large `.pth` file
+    non_speech_dict = dict()
+    non_speech_dict['train'] = {}
+    non_speech_dict['dev'] = {}
+    non_speech_dict['test'] = {}
+    # record 是 List of Dict, 一条大 wav 一个 record，一条小 wav 一个 sub_recored
+    print(f"start to save {args.rank}_{args.nshard}.npy ...")
+    save_start_time = time.time()
+    for record in tqdm.tqdm(results, total=len(results), colour='green'):
+        for sub_record in record:
+            # 这里加 try, 因为 txt 文件可能损坏
+            try:
+                utt_id = sub_record["utt_id"]
+                subset = sub_record["subset"]
+                audio_tag_top1 = check_txt_file(sub_record["audio_tag_path"])
+                if audio_tag_top1 is not False:
+                    if 'speech' not in audio_tag_top1.lower():
+                        non_speech_dict[subset][utt_id] = audio_tag_top1
+                    else:
+                        # print(f'audio tag result of {utt_id} is speech')
+                        pass
+                else:
+                    print(f'audio tag result of {utt_id} is False')
+            except Exception:
+                print(f"{utt_id} occur Exception")
+                traceback.print_exc()
+                continue
+
+    train_filename = train_dump_dir / f'non_speech_{args.rank}_{args.nshard}.npy'
+    dev_filename = dev_dump_dir / f'non_speech_{args.rank}_{args.nshard}.npy'
+    test_filename = test_dump_dir / f'non_speech_{args.rank}_{args.nshard}.npy'
+    np.save(train_filename, non_speech_dict['train'])
+    print(f"npy file '{train_filename}' write down")
+
+    np.save(dev_filename, non_speech_dict['dev'])
+    print(f"npy file '{dev_filename}' write down")
+
+    np.save(test_filename, non_speech_dict['test'])
+    print(f"npy file '{test_filename}' write down")
+    print('time of save stage:', time.time() - save_start_time)
+
+
+def main():
+    # parse config and args
+    parser = argparse.ArgumentParser(
+        description="Use AudioTag tool BEATs to filter out audios who's top1 tag is not 'speech'."
+    )
+
+    parser.add_argument(
+        "--data_dir", default=None, type=str, help="directory to dataset.")
+
+    parser.add_argument(
+        "--dump_dir",
+        type=str,
+        required=True,
+        help="directory to dump feature files.")
+
+    parser.add_argument(
+        "--num-cpu", type=int, default=1, help="number of process.")
+
+    parser.add_argument(
+        '--sr', type=int, default=16000, help='sample rate of model')
+
+    # For LibriLight dataset
+    parser.add_argument(
+        "--sub_dataset",
+        default="small",
+        type=str,
+        help="name of sub dataset of LibriLight",
+        choices=['small', 'medium', 'large', 'duplicate'], )
+    parser.add_argument(
+        "--VAD_path", type=str, default='./VAD/librilight_segment_dict.npy')
+    parser.add_argument("--nshard", type=int, default=3)
+    parser.add_argument("--rank", type=int, default=0)
+
+    # for BEATs
+    parser.add_argument(
+        "--BEATs_ckpt_path",
+        type=str,
+        default='./pretrained_model/BEATs_iter1_finetuned_on_AS2M_cpt1.pt')
+
+    args = parser.parse_args()
+
+    data_dir = Path(args.data_dir).expanduser()
+    dump_dir = Path(args.dump_dir).expanduser()
+    # use absolute path
+    dump_dir = dump_dir.resolve()
+    dump_dir.mkdir(parents=True, exist_ok=True)
+
+    assert data_dir.is_dir()
+
+    # sub_dataset here
+    sub_dataset_dir = data_dir / args.sub_dataset
+    # olny spk_id in list, sort by lexicographical order 
+    speaker_list = sorted(os.listdir(sub_dataset_dir))
+    start, end = get_shard_range(len(speaker_list), args.nshard, args.rank)
+    # speaker_list for this rank
+    speaker_list = speaker_list[start:end]
+
+    all_wav_files = []
+
+    for speaker in speaker_list:
+        wav_files = sorted(list((sub_dataset_dir / speaker).rglob("*/*.flac")))
+        # filter out ._*.flac
+        wav_files = [
+            file for file in wav_files if not file.name.startswith('._')
+        ]
+        all_wav_files += wav_files
+
+    print(f"num of wav files in rank {args.rank}:", len(all_wav_files))
+    # get VAD info
+    VAD_dict = np.load(args.VAD_path, allow_pickle=True).item()
+
+    sub_dataset_dump_dir = dump_dir / args.sub_dataset
+    sub_dataset_dump_dir.mkdir(parents=True, exist_ok=True)
+    train_dump_dir = sub_dataset_dump_dir / "train"
+    train_dump_dir.mkdir(parents=True, exist_ok=True)
+    dev_dump_dir = sub_dataset_dump_dir / "dev"
+    dev_dump_dir.mkdir(parents=True, exist_ok=True)
+    test_dump_dir = sub_dataset_dump_dir / "test"
+    test_dump_dir.mkdir(parents=True, exist_ok=True)
+
+    BEATs_ckpt = torch.load(args.BEATs_ckpt_path)
+
+    BEATs_cfg = BEATsConfig(BEATs_ckpt['cfg'])
+    BEATs_model = BEATs(BEATs_cfg)
+    BEATs_model.load_state_dict(BEATs_ckpt['model'])
+    BEATs_model.eval()
+    # cpu or cuda
+    device = 'cpu'
+    BEATs_model.to(device)
+
+    BEATs_label_dict = BEATs_ckpt['label_dict']
+
+    # 每条大 wav 分出一个 dev 一个 test，比例大概是 96:2:2
+    if all_wav_files:
+        process_sentences(
+            args=args,
+            fps=all_wav_files,
+            train_dump_dir=train_dump_dir,
+            dev_dump_dir=dev_dump_dir,
+            test_dump_dir=test_dump_dir,
+            VAD_dict=VAD_dict,
+            BEATs_model=BEATs_model,
+            BEATs_label_dict=BEATs_label_dict,
+            device=device,
+            nprocs=args.num_cpu)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/AR/exps/get_phones.py b/AR/exps/get_phones.py
new file mode 100644
index 0000000000000000000000000000000000000000..4132a0dd587071e3043897d58b5c034e61ed89d6
--- /dev/null
+++ b/AR/exps/get_phones.py
@@ -0,0 +1,232 @@
+"""
+1. read text of dataset
+2. text -> IPA by GruutPhonemizer
+3. save out a *.npy dict for all text
+my_dict = {"utt_id1": text1, "utt_id2": text2}
+np.save(output_filename, my_dict)
+my_dict = np.load(output_filename, allow_pickle=True).item()
+"""
+import argparse
+import os
+from concurrent.futures import ThreadPoolExecutor
+from operator import itemgetter
+from pathlib import Path
+from typing import List
+
+import numpy as np
+import tqdm
+from AR.text_processing.phonemizer import GruutPhonemizer
+
+
+def read_txt(txt_file):
+    utt_name = txt_file.stem
+    utt_id = utt_name.split('.')[0]
+    try:
+        with open(txt_file, 'r') as file:
+            txt = file.readline()
+        record = {"utt_id": utt_id, "txt": txt}
+    except Exception:
+        print("occur Exception")
+        traceback.print_exc()
+        return None
+    return record
+
+
+def read_txts(txt_files: List[Path], nprocs: int=1):
+    if nprocs == 1:
+        results = []
+        for txt_file in tqdm.tqdm(txt_files, total=len(txt_files)):
+            record = read_txt(txt_file=txt_file)
+            if record:
+                results.append(record)
+    else:
+        with ThreadPoolExecutor(nprocs) as pool:
+            futures = []
+            with tqdm.tqdm(total=len(txt_files)) as progress:
+                for txt_file in txt_files:
+                    future = pool.submit(read_txt, txt_file)
+                    future.add_done_callback(lambda p: progress.update())
+                    futures.append(future)
+
+                results = []
+                for ft in futures:
+                    record = ft.result()
+                    if record:
+                        results.append(record)
+
+    results.sort(key=itemgetter("utt_id"))
+    return_list = []
+    for item in results:
+        return_list.append((item["utt_id"], item["txt"]))
+    return return_list
+
+
+def process_sentence(item, phonemizer):
+    utt_id, text = item
+    try:
+        phonemes = phonemizer.phonemize(text, espeak=False)
+        record = {"utt_id": utt_id, "phonemes": phonemes}
+    except Exception:
+        print("occur Exception")
+        traceback.print_exc()
+        return None
+    return record
+
+
+def process_sentences(items, phonemizer, output_dir, nprocs: int=1):
+    if nprocs == 1:
+        results = []
+        for item in tqdm.tqdm(items, total=len(items)):
+            record = process_sentence(item=item, phonemizer=phonemizer)
+            if record:
+                results.append(record)
+    else:
+        with ThreadPoolExecutor(nprocs) as pool:
+            futures = []
+            with tqdm.tqdm(total=len(items)) as progress:
+                for item in items:
+                    future = pool.submit(process_sentence, item, phonemizer)
+                    future.add_done_callback(lambda p: progress.update())
+                    futures.append(future)
+
+                results = []
+                for ft in futures:
+                    record = ft.result()
+                    if record:
+                        results.append(record)
+    results.sort(key=itemgetter("utt_id"))
+    npy_dict = {}
+    for item in results:
+        utt_id = item["utt_id"]
+        phonemes = item["phonemes"]
+        npy_dict[utt_id] = phonemes
+    filename = output_dir / 'phonemes.npy'
+    np.save(filename, npy_dict)
+    print(f"npy file '{filename}' write down")
+
+
+def main():
+    # parse config and args
+    parser = argparse.ArgumentParser(description="Get phones for datasets")
+
+    parser.add_argument(
+        "--dataset",
+        default="ljspeech",
+        type=str,
+        help="name of dataset, should in {ljspeech, libritts} now")
+
+    parser.add_argument(
+        "--data_dir", default=None, type=str, help="directory to dataset.")
+
+    parser.add_argument(
+        "--dump_dir",
+        type=str,
+        required=True,
+        help="directory to dump feature files.")
+    parser.add_argument(
+        "--num-cpu", type=int, default=1, help="number of process.")
+
+    args = parser.parse_args()
+
+    data_dir = Path(args.data_dir).expanduser()
+    dump_dir = Path(args.dump_dir).expanduser()
+    # use absolute path
+    dump_dir = dump_dir.resolve()
+    dump_dir.mkdir(parents=True, exist_ok=True)
+
+    assert data_dir.is_dir()
+
+    if args.dataset == "ljspeech":
+        data_dict = {}
+        text_path = data_dir / 'metadata.csv'
+        with open(text_path, 'r') as rf:
+            for line in rf:
+                line_list = line.strip().split('|')
+                utt_id = line_list[0]
+                raw_text = line_list[-1]
+                data_dict[utt_id] = raw_text
+
+        sorted_dict = sorted(data_dict.items())
+
+        num_train = 12900
+        num_dev = 100
+        # (utt_id, txt)
+        train_txts = sorted_dict[:num_train]
+        dev_txts = sorted_dict[num_train:num_train + num_dev]
+        test_txts = sorted_dict[num_train + num_dev:]
+
+    elif args.dataset == "libritts":
+        '''
+        we use train-clean-100、train-clean-360、train-other-500 here 
+        and split dev and test from them, don't use test-* and dev-* cause the speakers are disjoint
+        the file structure is LibriTTS_R/train-clean-100/spkid/*/*.wav
+        there are about 2311 in these subsets, we split 1 dev and 1 test wav out from each speaker
+        '''
+        txt_files = []
+        train_txt_files = []
+        dev_txt_files = []
+        test_txt_files = []
+        sub_num_dev = 1
+        for sub_dataset_name in {
+                "train-clean-100", "train-clean-360", "train-other-500"
+        }:
+            sub_dataset_dir = data_dir / sub_dataset_name
+            # filter out hidden files
+            speaker_list = [
+                file for file in os.listdir(sub_dataset_dir)
+                if not file.startswith('.')
+            ]
+            for speaker in speaker_list:
+                txt_files = sorted(
+                    list((sub_dataset_dir / speaker).rglob(
+                        "*/*.normalized.txt")))
+                # filter out ._*.wav
+                txt_files = [
+                    file for file in txt_files if not file.name.startswith('._')
+                ]
+                train_txt_files += txt_files[:-sub_num_dev * 2]
+                dev_txt_files += txt_files[-sub_num_dev * 2:-sub_num_dev]
+                test_txt_files += txt_files[-sub_num_dev:]
+        print("len(train_txt_files):", len(train_txt_files))
+        print("len(dev_txt_files):", len(dev_txt_files))
+        print("len(test_txt_files):", len(test_txt_files))
+
+        train_txts = read_txts(train_txt_files)
+        dev_txts = read_txts(dev_txt_files)
+        test_txts = read_txts(test_txt_files)
+
+    else:
+        print("dataset should in {ljspeech, libritts} now!")
+
+    train_dump_dir = dump_dir / "train"
+    train_dump_dir.mkdir(parents=True, exist_ok=True)
+    dev_dump_dir = dump_dir / "dev"
+    dev_dump_dir.mkdir(parents=True, exist_ok=True)
+    test_dump_dir = dump_dir / "test"
+    test_dump_dir.mkdir(parents=True, exist_ok=True)
+
+    phonemizer = GruutPhonemizer(language='en-us')
+
+    # process for the 3 sections
+    if train_txts:
+        process_sentences(
+            items=train_txts,
+            output_dir=train_dump_dir,
+            phonemizer=phonemizer,
+            nprocs=args.num_cpu)
+    if dev_txts:
+        process_sentences(
+            items=dev_txts,
+            output_dir=dev_dump_dir,
+            phonemizer=phonemizer,
+            nprocs=args.num_cpu)
+    if test_txts:
+        process_sentences(
+            items=test_txts,
+            output_dir=test_dump_dir,
+            phonemizer=phonemizer,
+            nprocs=args.num_cpu)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/AR/exps/get_phones_librilight.py b/AR/exps/get_phones_librilight.py
new file mode 100644
index 0000000000000000000000000000000000000000..a9254dad7da0490bc5032f3a5e4d8832217760e7
--- /dev/null
+++ b/AR/exps/get_phones_librilight.py
@@ -0,0 +1,198 @@
+"""
+1. read text of dataset, for LibriLight read txt_*.npy -> 需要整理成 list(utt_id, txt) 的形式
+2. text -> IPA by GruutPhonemizer
+3. save out a *.npy dict for all text
+4. LibriLight 每个 split 分开处理
+my_dict = {"utt_id1": text1, "utt_id2": text2}
+np.save(output_filename, my_dict)
+my_dict = np.load(output_filename, allow_pickle=True).item()
+"""
+import argparse
+import os
+import time
+import traceback
+from concurrent.futures import ThreadPoolExecutor
+from operator import itemgetter
+from pathlib import Path
+
+import numpy as np
+import tqdm
+from AR.text_processing.phonemizer import GruutPhonemizer
+from soundstorm.utils import check_txt_file
+
+
+def read_txts(txt_file: Path, nprocs: int=1):
+    '''
+    txt_file: path of npy dict, {"utt_id1": text1, "utt_id2": text2}
+    '''
+    txt_dict = np.load(txt_file, allow_pickle=True).item()
+    #[(utt_id, txt), ...]
+    return_list = list(txt_dict.items())
+    return return_list
+
+
+def process_sentence(item, phonemizer, output_dir):
+    utt_id, text = item
+    phonemes_dir = output_dir / "phonemes"
+    phonemes_dir.mkdir(parents=True, exist_ok=True)
+    phonemes_path = phonemes_dir / (utt_id + ".txt")
+    try:
+        if os.path.exists(phonemes_path) and check_txt_file(phonemes_path):
+            # print(phonemes_path, 'exits!')
+            pass
+        else:
+            phonemes = phonemizer.phonemize(text, espeak=False)
+            with open(phonemes_path, 'w') as f:
+                f.write(phonemes)
+        record = {"utt_id": utt_id, "phonemes_path": phonemes_path}
+    except Exception:
+        print("occur Exception")
+        traceback.print_exc()
+        return None
+    return record
+
+
+def process_sentences(args, items, phonemizer, output_dir, nprocs: int=1):
+    print("nprocs:", nprocs)
+    if nprocs == 1:
+        results = []
+        for item in tqdm.tqdm(items, total=len(items)):
+            record = process_sentence(
+                item=item, phonemizer=phonemizer, output_dir=output_dir)
+            if record:
+                results.append(record)
+    else:
+        with ThreadPoolExecutor(nprocs) as pool:
+            futures = []
+            with tqdm.tqdm(total=len(items)) as progress:
+                for item in items:
+                    future = pool.submit(process_sentence, item, phonemizer,
+                                         output_dir)
+                    future.add_done_callback(lambda p: progress.update())
+                    futures.append(future)
+
+                results = []
+                for ft in futures:
+                    record = ft.result()
+                    if record:
+                        results.append(record)
+
+    results.sort(key=itemgetter("utt_id"))
+
+    npy_dict = {}
+    print(f"start to save {args.rank}_{args.nshard}.npy ...")
+    save_start_time = time.time()
+    for item in tqdm.tqdm(results, total=len(results), colour='green'):
+        # 这里加 try, 因为 txt 文件可能损坏
+        try:
+            utt_id = item["utt_id"]
+            phonemes = check_txt_file(item["phonemes_path"])
+            if phonemes is not False:
+                npy_dict[utt_id] = phonemes
+            else:
+                print(f'phonemes of {utt_id} is False')
+        except Exception:
+            print(f"{utt_id} occur Exception")
+            traceback.print_exc()
+            continue
+
+    filename = output_dir / f'phonemes_{args.rank}_{args.nshard}.npy'
+    np.save(filename, npy_dict)
+    print(f"npy file '{filename}' write down")
+    print('time of save stage:', time.time() - save_start_time)
+
+
+def main():
+    # parse config and args
+    parser = argparse.ArgumentParser(
+        description="Get phones for LibriLight dataset from txt_*.npy")
+
+    parser.add_argument(
+        "--dump_dir",
+        type=str,
+        required=True,
+        help="directory to dump feature files.")
+    parser.add_argument(
+        "--num-cpu", type=int, default=1, help="number of process.")
+
+    parser.add_argument(
+        '--train_txt_dir',
+        type=str,
+        default='dump/small/train/',
+        help='dir of train txt files')
+    parser.add_argument(
+        '--dev_txt_dir',
+        type=str,
+        default='dump/small/dev/',
+        help='dir of dev txt files')
+    parser.add_argument(
+        '--test_txt_dir',
+        type=str,
+        default='dump/small/test/',
+        help='dir of test txt files')
+
+    parser.add_argument(
+        "--sub_dataset",
+        default="small",
+        type=str,
+        help="name of sub dataset of LibriLight",
+        choices=['small', 'medium', 'large', 'duplicate'], )
+    parser.add_argument("--nshard", type=int, default=3)
+    parser.add_argument("--rank", type=int, default=0)
+
+    args = parser.parse_args()
+    print(f"nshard: {args.nshard}, rank: {args.rank}")
+
+    train_txt_dir = Path(args.train_txt_dir)
+    dev_txt_dir = Path(args.dev_txt_dir)
+    test_txt_dir = Path(args.test_txt_dir)
+
+    dump_dir = Path(args.dump_dir).expanduser()
+    # use absolute path
+    dump_dir = dump_dir.resolve()
+    dump_dir.mkdir(parents=True, exist_ok=True)
+
+    train_txt_file = train_txt_dir / f'txt_{args.rank}_{args.nshard}.npy'
+    dev_txt_file = dev_txt_dir / f'txt_{args.rank}_{args.nshard}.npy'
+    test_txt_file = test_txt_dir / f'txt_{args.rank}_{args.nshard}.npy'
+
+    train_txts = read_txts(train_txt_file)
+    dev_txts = read_txts(dev_txt_file)
+    test_txts = read_txts(test_txt_file)
+
+    sub_dataset_dump_dir = dump_dir / args.sub_dataset
+    sub_dataset_dump_dir.mkdir(parents=True, exist_ok=True)
+    train_dump_dir = sub_dataset_dump_dir / "train"
+    train_dump_dir.mkdir(parents=True, exist_ok=True)
+    dev_dump_dir = sub_dataset_dump_dir / "dev"
+    dev_dump_dir.mkdir(parents=True, exist_ok=True)
+    test_dump_dir = sub_dataset_dump_dir / "test"
+    test_dump_dir.mkdir(parents=True, exist_ok=True)
+    phonemizer = GruutPhonemizer(language='en-us')
+
+    # process for the 3 sections
+    if train_txts:
+        process_sentences(
+            args=args,
+            items=train_txts,
+            output_dir=train_dump_dir,
+            phonemizer=phonemizer,
+            nprocs=args.num_cpu)
+    if dev_txts:
+        process_sentences(
+            args=args,
+            items=dev_txts,
+            output_dir=dev_dump_dir,
+            phonemizer=phonemizer,
+            nprocs=args.num_cpu)
+    if test_txts:
+        process_sentences(
+            args=args,
+            items=test_txts,
+            output_dir=test_dump_dir,
+            phonemizer=phonemizer,
+            nprocs=args.num_cpu)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/AR/exps/get_txt_librilight.py b/AR/exps/get_txt_librilight.py
new file mode 100644
index 0000000000000000000000000000000000000000..71b74b5b813f311018827425928510acc09f65b8
--- /dev/null
+++ b/AR/exps/get_txt_librilight.py
@@ -0,0 +1,255 @@
+import argparse
+import os
+import time
+import traceback
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+
+import librosa
+import numpy as np
+import tqdm
+import whisper
+from soundstorm.s2.exps.hubert.feature_utils import get_shard_range
+from soundstorm.utils import check_txt_file
+
+
+def process_sentence(args,
+                     fp: Path,
+                     train_dump_dir: Path,
+                     dev_dump_dir: Path,
+                     test_dump_dir: Path,
+                     VAD_dict):
+    asr_model = whisper.load_model("tiny.en")
+    utt_id = fp.stem
+    sr = args.sr
+    record = []
+    train_txt_dir = train_dump_dir / "txt"
+    train_txt_dir.mkdir(parents=True, exist_ok=True)
+
+    dev_txt_dir = dev_dump_dir / "txt"
+    dev_txt_dir.mkdir(parents=True, exist_ok=True)
+
+    test_txt_dir = test_dump_dir / "txt"
+    test_txt_dir.mkdir(parents=True, exist_ok=True)
+
+    try:
+        # get info for path
+        wav_path_list = str(fp).strip().split('/')
+        sub_dataset, spk_id, book_name = wav_path_list[-4], wav_path_list[
+            -3], wav_path_list[-2]
+        wav_name = wav_path_list[-1][:-5]
+        assert wav_name == utt_id
+        # key_name for big wav
+        key_name = f'{wav_name}#{sub_dataset}#{spk_id}#{book_name}'
+        # 判断 VAD 字典中不存在该条音频信息的情况
+        if key_name not in VAD_dict.keys():
+            print(key_name, 'not in VAD_dict !')
+            return record
+        wav = None
+        sorted_split_VAD_dict = sorted(VAD_dict[key_name].items())
+        len_dict = len(sorted_split_VAD_dict)
+        for index, item in enumerate(sorted_split_VAD_dict):
+            split_name, value = item
+            start, end = value
+            # train | dev | test
+            if index == len_dict - 1:
+                subset = 'test'
+                txt_path = test_txt_dir / (split_name + ".txt")
+            elif index == len_dict - 2:
+                subset = 'dev'
+                txt_path = dev_txt_dir / (split_name + ".txt")
+            else:
+                subset = 'train'
+                txt_path = train_txt_dir / (split_name + ".txt")
+
+            if os.path.exists(txt_path) and check_txt_file(txt_path):
+                # print(txt_path, 'exits!')
+                pass
+            else:
+                # 这里加判断保证在 sub wav 的循环中只 load 一次
+                if wav is None:
+                    # load big wav
+                    # 在最外层 load 如果 sub wav 的特征都存在了就会白白消耗 load 的时间
+                    wav, _ = librosa.load(str(fp), sr=sr)
+                sub_wav = wav[int(start * sr):int(end * sr)]
+                asr_result = asr_model.transcribe(sub_wav)["text"]
+                with open(txt_path, 'w') as f:
+                    f.write(asr_result)
+
+            sub_record = {
+                "utt_id": split_name,
+                "txt_path": txt_path,
+                "subset": subset
+            }
+            # recodrd 变成 List of Dict
+            record.append(sub_record)
+    except Exception:
+        print("occur Exception")
+        traceback.print_exc()
+        # record 有可能是一个不完整的 List
+        return record
+    return record
+
+
+def process_sentences(args,
+                      fps: Path,
+                      train_dump_dir: Path,
+                      dev_dump_dir: Path,
+                      test_dump_dir: Path,
+                      VAD_dict,
+                      nprocs: int=1):
+    print("nprocs:", nprocs)
+    if nprocs == 1:
+        results = []
+        for fp in tqdm.tqdm(fps, total=len(fps)):
+            record = process_sentence(
+                args=args,
+                fp=fp,
+                train_dump_dir=train_dump_dir,
+                dev_dump_dir=dev_dump_dir,
+                test_dump_dir=test_dump_dir,
+                VAD_dict=VAD_dict)
+            if record:
+                results.append(record)
+    else:
+        with ThreadPoolExecutor(nprocs) as pool:
+            futures = []
+            with tqdm.tqdm(total=len(fps)) as progress:
+                for fp in fps:
+                    future = pool.submit(process_sentence, args, fp,
+                                         train_dump_dir, dev_dump_dir,
+                                         test_dump_dir, VAD_dict)
+                    future.add_done_callback(lambda p: progress.update())
+                    futures.append(future)
+
+                results = []
+                for ft in futures:
+                    record = ft.result()
+                    if record:
+                        results.append(record)
+
+    # torch.save() to a large `.pth` file
+    txt_dict = dict()
+    txt_dict['train'] = {}
+    txt_dict['dev'] = {}
+    txt_dict['test'] = {}
+    # record 是 List of Dict, 一条大 wav 一个 record，一条小 wav 一个 sub_recored
+    print(f"start to save {args.rank}_{args.nshard}.npy ...")
+    save_start_time = time.time()
+    for record in tqdm.tqdm(results, total=len(results), colour='green'):
+        for sub_record in record:
+            # 这里加 try, 因为 txt 文件可能损坏
+            try:
+                utt_id = sub_record["utt_id"]
+                subset = sub_record["subset"]
+                asr_result = check_txt_file(sub_record["txt_path"])
+                if asr_result is not False:
+                    txt_dict[subset][utt_id] = asr_result
+                else:
+                    print(f'asr result of {utt_id} is False')
+            except Exception:
+                print(f"{utt_id} occur Exception")
+                traceback.print_exc()
+                continue
+
+    train_filename = train_dump_dir / f'txt_{args.rank}_{args.nshard}.npy'
+    dev_filename = dev_dump_dir / f'txt_{args.rank}_{args.nshard}.npy'
+    test_filename = test_dump_dir / f'txt_{args.rank}_{args.nshard}.npy'
+    np.save(train_filename, txt_dict['train'])
+    print(f"npy file '{train_filename}' write down")
+
+    np.save(dev_filename, txt_dict['dev'])
+    print(f"npy file '{dev_filename}' write down")
+
+    np.save(test_filename, txt_dict['test'])
+    print(f"npy file '{test_filename}' write down")
+    print('time of save stage:', time.time() - save_start_time)
+
+
+def main():
+    # parse config and args
+    parser = argparse.ArgumentParser(
+        description="Preprocess audio and then extract features for LibriLight.")
+
+    parser.add_argument(
+        "--data_dir", default=None, type=str, help="directory to dataset.")
+
+    parser.add_argument(
+        "--dump_dir",
+        type=str,
+        required=True,
+        help="directory to dump feature files.")
+
+    parser.add_argument(
+        "--num-cpu", type=int, default=1, help="number of process.")
+
+    parser.add_argument(
+        '--sr', type=int, default=16000, help='sample rate of model')
+
+    # For LibriLight dataset
+    parser.add_argument(
+        "--sub_dataset",
+        default="small",
+        type=str,
+        help="name of sub dataset of LibriLight",
+        choices=['small', 'medium', 'large', 'duplicate'], )
+    parser.add_argument(
+        "--VAD_path", type=str, default='./VAD/librilight_segment_dict.npy')
+    parser.add_argument("--nshard", type=int, default=3)
+    parser.add_argument("--rank", type=int, default=0)
+
+    args = parser.parse_args()
+
+    data_dir = Path(args.data_dir).expanduser()
+    dump_dir = Path(args.dump_dir).expanduser()
+    # use absolute path
+    dump_dir = dump_dir.resolve()
+    dump_dir.mkdir(parents=True, exist_ok=True)
+
+    assert data_dir.is_dir()
+
+    # sub_dataset here
+    sub_dataset_dir = data_dir / args.sub_dataset
+    # olny spk_id in list, sort by lexicographical order 
+    speaker_list = sorted(os.listdir(sub_dataset_dir))
+    start, end = get_shard_range(len(speaker_list), args.nshard, args.rank)
+    # speaker_list for this rank
+    speaker_list = speaker_list[start:end]
+
+    all_wav_files = []
+
+    for speaker in speaker_list:
+        wav_files = sorted(list((sub_dataset_dir / speaker).rglob("*/*.flac")))
+        # filter out ._*.flac
+        wav_files = [
+            file for file in wav_files if not file.name.startswith('._')
+        ]
+        all_wav_files += wav_files
+
+    print(f"num of wav files in rank {args.rank}:", len(all_wav_files))
+    # get VAD info
+    VAD_dict = np.load(args.VAD_path, allow_pickle=True).item()
+
+    sub_dataset_dump_dir = dump_dir / args.sub_dataset
+    sub_dataset_dump_dir.mkdir(parents=True, exist_ok=True)
+    train_dump_dir = sub_dataset_dump_dir / "train"
+    train_dump_dir.mkdir(parents=True, exist_ok=True)
+    dev_dump_dir = sub_dataset_dump_dir / "dev"
+    dev_dump_dir.mkdir(parents=True, exist_ok=True)
+    test_dump_dir = sub_dataset_dump_dir / "test"
+    test_dump_dir.mkdir(parents=True, exist_ok=True)
+
+    # 每条大 wav 分出一个 dev 一个 test，比例大概是 96:2:2
+    if all_wav_files:
+        process_sentences(
+            args=args,
+            fps=all_wav_files,
+            train_dump_dir=train_dump_dir,
+            dev_dump_dir=dev_dump_dir,
+            test_dump_dir=test_dump_dir,
+            VAD_dict=VAD_dict,
+            nprocs=args.num_cpu)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/AR/exps/split_train_val.py b/AR/exps/split_train_val.py
new file mode 100644
index 0000000000000000000000000000000000000000..45486b9b2214e583acc6a1131ab840af25050f5e
--- /dev/null
+++ b/AR/exps/split_train_val.py
@@ -0,0 +1,35 @@
+import numpy
+import pandas
+
+semantic_path = 'dump/semantic.tsv'
+phoneme_path = 'dump/phoneme.npy'
+train_semantic_path = 'dump/semantic_train.tsv'
+train_phoneme_path = 'dump/phoneme_train.npy'
+dev_semantic_path = 'dump/semantic_dev.tsv'
+dev_phoneme_path = 'dump/phoneme_dev.npy'
+
+# 读取dump/semantic.tsv
+semantic_df = pandas.read_csv(semantic_path, sep='\t')
+# pd.DataFrame(columns=["item_name", "semantic_audio"])
+# # 读取dump/phoneme.npy
+phoneme_dict = numpy.load(phoneme_path, allow_pickle=True).item()
+
+dev_num = 20
+# 随机从semantic_df中选取dev_num个
+dev_df = semantic_df.sample(n=dev_num)
+# 剩下的是train
+train_df = semantic_df.drop(dev_df.index)
+# 保存
+dev_df.to_csv(dev_semantic_path, sep='\t', index=False)
+train_df.to_csv(train_semantic_path, sep='\t', index=False)
+
+# 将dev_df中的item_name取出来 作为dev_phoneme_dict的key
+dev_item_names = dev_df['item_name'].tolist()
+dev_phoneme_dict = {k: phoneme_dict[k] for k in dev_item_names if k in phoneme_dict}
+train_phoneme_dict = {k: phoneme_dict[k] for k in phoneme_dict.keys() if k not in dev_item_names}
+
+numpy.save(dev_phoneme_path, dev_phoneme_dict)
+numpy.save(train_phoneme_path, train_phoneme_dict)
+
+
+
diff --git a/AR/exps/t2s.py b/AR/exps/t2s.py
new file mode 100644
index 0000000000000000000000000000000000000000..e160f8e706af38e7ec373bd67b46e695a1009b7f
--- /dev/null
+++ b/AR/exps/t2s.py
@@ -0,0 +1,197 @@
+# text to semantic
+import argparse
+import os
+import re
+import time
+from pathlib import Path
+
+import librosa
+import numpy as np
+import torch
+import whisper
+from AR.models.t2s_lightning_module import Text2SemanticLightningModule
+from AR.text_processing.phonemizer import GruutPhonemizer
+from AR.utils.io import load_yaml_config
+
+
+def get_batch(text, phonemizer):
+    # phoneme_ids 和 phoneme_ids_len 是需要的
+    phoneme = phonemizer.phonemize(text, espeak=False)
+    phoneme_ids = phonemizer.transform(phoneme)
+    phoneme_ids_len = len(phoneme_ids)
+    phoneme_ids = np.array(phoneme_ids)
+    # add batch axis here
+    phoneme_ids = torch.tensor(phoneme_ids).unsqueeze(0)
+    phoneme_ids_len = torch.tensor([phoneme_ids_len])
+    print("phoneme:", phoneme)
+    batch = {
+        # torch.Tensor (B, max_phoneme_length) 
+        "phoneme_ids": phoneme_ids,
+        # torch.Tensor (B)
+        "phoneme_ids_len": phoneme_ids_len
+    }
+    return batch
+
+
+def get_prompt(prompt_wav_path, asr_model, phonemizer, semantic_tokenizer):
+    sample_rate = 16000
+    # to get prompt
+    prompt_name = os.path.basename(prompt_wav_path).split('.')[0]
+    wav, _ = librosa.load(prompt_wav_path, sr=sample_rate)
+    # 取末尾 3s, 但是不包含最后 0.1s 防止 AR S1 infer 提前停止
+    wav = wav[-sample_rate * 3:-int(sample_rate * 0.1)]
+    # wav 需要挪出末尾的静音否则也可能提前停住
+    prompt_text = asr_model.transcribe(wav)["text"]
+    # 移除最后的句点, 防止 AR S1 infer 提前停止, 加了句点可能会有停顿
+    prompt_text = prompt_text.replace(".", "")
+    prompt_phoneme = phonemizer.phonemize(prompt_text, espeak=False)
+    prompt_phoneme_ids = phonemizer.transform(prompt_phoneme)
+    prompt_phoneme_ids_len = len(prompt_phoneme_ids)
+    # get prompt_semantic
+    # (T) -> (1, T)
+    wav = torch.tensor(wav).unsqueeze(0)
+    wav = wav.cuda()
+    # (1, T)
+    prompt_semantic_tokens = semantic_tokenizer.tokenize(wav).to(torch.int32)
+    prompt_phoneme_ids = torch.tensor(prompt_phoneme_ids).unsqueeze(0)
+    prompt_phoneme_ids_len = torch.tensor([prompt_phoneme_ids_len])
+
+    result = {
+        'prompt_name': prompt_name,
+        'prompt_phoneme_ids': prompt_phoneme_ids,
+        'prompt_semantic_tokens': prompt_semantic_tokens,
+        'prompt_phoneme_ids_len': prompt_phoneme_ids_len
+    }
+
+    return result
+
+
+def parse_args():
+    # parse args and config
+    parser = argparse.ArgumentParser(
+        description="Run SoundStorm AR S1 model for input text file")
+
+    parser.add_argument(
+        '--config_file',
+        type=str,
+        default='conf/default.yaml',
+        help='path of config file')
+
+    parser.add_argument(
+        "--text_file",
+        type=str,
+        help="text file to be convert to semantic tokens, a 'utt_id sentence' pair per line."
+    )
+
+    parser.add_argument(
+        '--ckpt_path',
+        type=str,
+        default='exp/default/ckpt/epoch=99-step=49000.ckpt',
+        help='Checkpoint file of SoundStorm AR S1 model.')
+
+    parser.add_argument(
+        '--prompt_wav_path',
+        type=str,
+        default=None,
+        help='extract prompt semantic and prompt phonemes from prompt wav')
+
+    # to get semantic tokens from prompt_wav
+    parser.add_argument("--hubert_path", type=str, default=None)
+    parser.add_argument("--quantizer_path", type=str, default=None)
+
+    parser.add_argument("--output_dir", type=str, help="output dir.")
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    args = parse_args()
+    config = load_yaml_config(args.config_file)
+
+    output_dir = Path(args.output_dir)
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    hz = 50
+    max_sec = config['data']['max_sec']
+
+    # get models
+    t2s_model = Text2SemanticLightningModule.load_from_checkpoint(
+        checkpoint_path=args.ckpt_path, config=config)
+    t2s_model.cuda()
+    t2s_model.eval()
+
+    phonemizer: GruutPhonemizer = GruutPhonemizer(language='en-us')
+
+    # models for prompt
+    asr_model = whisper.load_model("tiny.en")
+
+    semantic_tokenizer = SemanticTokenizer(
+        hubert_path=args.hubert_path,
+        quantizer_path=args.quantizer_path,
+        duplicate=True)
+
+    prompt_result = get_prompt(
+        prompt_wav_path=args.prompt_wav_path,
+        asr_model=asr_model,
+        phonemizer=phonemizer,
+        semantic_tokenizer=semantic_tokenizer)
+
+    # zero prompt => 输出的 semantic 包含的内容是对的但是音色是乱的
+    # (B, 1)
+    # prompt = torch.ones(
+    #     batch['phoneme_ids'].size(0), 1, dtype=torch.int32) * 0
+
+    prompt = prompt_result['prompt_semantic_tokens']
+    prompt_phoneme_ids_len = prompt_result['prompt_phoneme_ids_len']
+    prompt_phoneme_ids = prompt_result['prompt_phoneme_ids']
+
+    sentences = []
+    with open(args.text_file, 'rt', encoding='utf-8') as f:
+        for line in f:
+            if line.strip() != "":
+                items = re.split(r"\s+", line.strip(), 1)
+                utt_id = items[0]
+                sentence = " ".join(items[1:])
+            sentences.append((utt_id, sentence))
+    semantic_data = [['item_name', 'semantic_audio']]
+    for utt_id, sentence in sentences[1:]:
+        # 需要自己构造伪 batch 输入给模型
+        batch = get_batch(sentence, phonemizer)
+        # prompt 和真正的输入拼接
+        all_phoneme_ids = torch.cat(
+            [prompt_phoneme_ids, batch['phoneme_ids']], dim=1)
+        # 或者可以直接求 all_phoneme_ids 的 shape[-1]
+        all_phoneme_len = prompt_phoneme_ids_len + batch['phoneme_ids_len']
+        st = time.time()
+        with torch.no_grad():
+            pred_semantic = t2s_model.model.infer(
+                all_phoneme_ids.cuda(),
+                all_phoneme_len.cuda(),
+                prompt.cuda(),
+                top_k=config['inference']['top_k'],
+                early_stop_num=hz * max_sec)
+        print(f'{time.time() - st} sec used in T2S')
+
+        # 删除 prompt 对应的部分
+        prompt_len = prompt.shape[-1]
+        pred_semantic = pred_semantic[:, prompt_len:]
+
+        # bs = 1
+        pred_semantic = pred_semantic[0]
+        semantic_token = pred_semantic.detach().cpu().numpy().tolist()
+        semantic_token_str = ' '.join(str(x) for x in semantic_token)
+        semantic_data.append([utt_id, semantic_token_str])
+
+        delimiter = '\t'
+        filename = output_dir / f'{utt_id}_p_{prompt_result["prompt_name"]}_semantic_token.tsv'
+        with open(filename, 'w', encoding='utf-8') as writer:
+            for row in semantic_data:
+                line = delimiter.join(row)
+                writer.write(line + '\n')
+        # clean semantic token for next setence
+        semantic_data = [['item_name', 'semantic_audio']]
+
+
+if __name__ == "__main__":
+    main()
diff --git a/AR/exps/test.py b/AR/exps/test.py
new file mode 100644
index 0000000000000000000000000000000000000000..f04c49e24fd7048a36679a7166f6e1d49473fde2
--- /dev/null
+++ b/AR/exps/test.py
@@ -0,0 +1,139 @@
+# test from dump file
+import argparse
+import time
+from pathlib import Path
+
+import numpy as np
+import torch
+from AR.data.dataset import Text2SemanticDataset
+from AR.models.t2s_lightning_module import Text2SemanticLightningModule
+from AR.utils.io import load_yaml_config
+from torch.utils.data import DataLoader
+
+
+def parse_args():
+    # parse args and config
+    parser = argparse.ArgumentParser(
+        description="Run SoundStorm AR S1 model for test set.")
+
+    parser.add_argument(
+        '--config_file',
+        type=str,
+        default='conf/default.yaml',
+        help='path of config file')
+
+    # args for dataset
+    parser.add_argument(
+        '--test_semantic_path',
+        type=str,
+        default='dump/test/semantic_token.tsv')
+    parser.add_argument(
+        '--test_phoneme_path', type=str, default='dump/test/phonemes.npy')
+
+    parser.add_argument(
+        '--ckpt_path',
+        type=str,
+        default='exp/default/ckpt/epoch=99-step=49000.ckpt',
+        help='Checkpoint file of SoundStorm AR S1 model.')
+
+    parser.add_argument("--output_dir", type=str, help="output dir.")
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    args = parse_args()
+
+    config = load_yaml_config(args.config_file)
+
+    output_dir = Path(args.output_dir)
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    batch_size = 1
+    hz = 50
+    max_sec = config['data']['max_sec']
+
+    # get dataset
+    test_dataset = Text2SemanticDataset(
+        phoneme_path=args.test_phoneme_path,
+        semantic_path=args.test_semantic_path,
+        # max_sec 需要与训练时保持一致，不然可能会效果不好，重复漏字等
+        # 但是这里设置太短又会直接过滤掉太长的样本，为了防止被过滤掉，可以在 infer 的时候截断
+        max_sec=100,
+        max_sample=8,
+        pad_val=config['data']['pad_val'])
+    # get model
+    t2s_model = Text2SemanticLightningModule.load_from_checkpoint(
+        checkpoint_path=args.ckpt_path, config=config)
+    t2s_model.cuda()
+    t2s_model.eval()
+
+    # 获取 batch_size 条
+    # 创建 DataLoader，并指定 collate_fn 函数
+    dataloader = DataLoader(
+        test_dataset,
+        batch_size=batch_size,
+        shuffle=False,
+        collate_fn=test_dataset.collate)
+
+    item_names = test_dataset.__get_item_names__()
+
+    # 逐批次读取数据, bs=1、shuffle=False 时可以用 __get_item_names__ 对应
+    semantic_data = [['item_name', 'semantic_audio']]
+    for i, batch in enumerate(dataloader):
+        # 要保证 bs = 1
+        utt_id = item_names[i]
+        if i == 0:
+            print("utt_id:", utt_id)
+            # bs > 1 时会补零
+            # 与 validation_step() 保持一致
+            semantic_len = batch['semantic_ids'].size(1)
+            # 以 batch['semantic_ids'] 的前 150 个为 prompt
+            # 多次合成，前 prompt_len 个是一样的，而且和 prompt 一样
+            prompt_len = min(int(semantic_len * 0.5), 150)
+            # 输入纯文本时 prompt 该输入什么？=> see t2s.py
+            prompt = batch['semantic_ids'][:, :prompt_len]
+            # # zero prompt => 也可以输出文本内容正确的 semantic token, 但是音色是乱的
+            # 证明 semantic token 中还是包含了音色信息
+            # prompt = torch.ones(
+            #     batch['semantic_ids'].size(0), 1, dtype=torch.int32) * 0
+            # print("prompt:", prompt)
+            # print("prompt.shape:", prompt.shape)
+            np.save(output_dir / 'prompt.npy', prompt.detach().cpu().numpy())
+
+            st = time.time()
+            with torch.no_grad():
+                # calculate acc for test
+                loss, acc = t2s_model.model.forward(
+                    batch['phoneme_ids'].cuda(),
+                    batch['phoneme_ids_len'].cuda(),
+                    batch['semantic_ids'].cuda(),
+                    batch['semantic_ids_len'].cuda())
+                print("top_3_acc of this batch:", acc)
+                pred_semantic = t2s_model.model.infer(
+                    batch['phoneme_ids'].cuda(),
+                    batch['phoneme_ids_len'].cuda(),
+                    prompt.cuda(),
+                    top_k=config['inference']['top_k'],
+                    # hz * max_sec in train dataloader
+                    # 生成的长度是 1002 应该是有一些 pad
+                    early_stop_num=hz * max_sec)
+                # bs = 1
+                pred_semantic = pred_semantic[0]
+            print(f'{time.time() - st} sec used in T2S')
+            semantic_token = pred_semantic.detach().cpu().numpy().tolist()
+            semantic_token_str = ' '.join(str(x) for x in semantic_token)
+            semantic_data.append([utt_id, semantic_token_str])
+        else:
+            break
+    delimiter = '\t'
+    filename = output_dir / "semantic_token.tsv"
+    with open(filename, 'w', encoding='utf-8') as writer:
+        for row in semantic_data:
+            line = delimiter.join(row)
+            writer.write(line + '\n')
+
+
+if __name__ == "__main__":
+    main()
diff --git a/AR/exps/text.txt b/AR/exps/text.txt
new file mode 100644
index 0000000000000000000000000000000000000000..85b375e33322f8a652b4b431f69403f21d441cc3
--- /dev/null
+++ b/AR/exps/text.txt
@@ -0,0 +1,10 @@
+001 Life was like a box of chocolates, you never know what you're gonna get.
+002 With great power there must come great responsibility.
+003 To be or not to be, that’s a question.
+004 A man can be destroyed but not defeated
+005 Do not, for one repulse, give up the purpose that you resolved to effort.
+006 Death is just a part of life, something we're all destined to do.
+007 I think it's hard winning a war with words. 
+008 Don’t argue with the people of strong determination, because they may change the fact!
+009 Love you three thousand times.
+010 tidy tiger tied a tie tighter to tidy her tiny tall.
\ No newline at end of file
diff --git a/AR/exps/train.py b/AR/exps/train.py
new file mode 100644
index 0000000000000000000000000000000000000000..2f6f41f961e6a35f16c17d4941274bf027d8f934
--- /dev/null
+++ b/AR/exps/train.py
@@ -0,0 +1,103 @@
+# modified from https://github.com/feng-yufei/shared_debugging_code/blob/main/train_t2s.py
+import argparse
+import logging
+import os
+from pathlib import Path
+
+import torch
+from pytorch_lightning import seed_everything
+from pytorch_lightning import Trainer
+from pytorch_lightning.callbacks import ModelCheckpoint
+from pytorch_lightning.loggers import WandbLogger
+from pytorch_lightning.strategies import DDPStrategy
+from AR.data.data_module import Text2SemanticDataModule
+from AR.models.t2s_lightning_module import Text2SemanticLightningModule
+from soundstorm.utils.io import load_yaml_config
+logging.getLogger('numba').setLevel(logging.WARNING)
+logging.getLogger('matplotlib').setLevel(logging.WARNING)
+torch.set_float32_matmul_precision('high')
+from soundstorm.utils import get_newest_ckpt
+
+
+def main(args):
+    output_dir = Path(args.output_dir)
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    ckpt_dir = output_dir / 'ckpt'
+    ckpt_dir.mkdir(parents=True, exist_ok=True)
+
+    config = load_yaml_config(args.config_file)
+
+    seed_everything(config["train"]["seed"], workers=True)
+    ckpt_callback: ModelCheckpoint = ModelCheckpoint(
+        save_top_k=-1,
+        save_on_train_epoch_end=False,
+        every_n_epochs=config["train"]["save_every_n_epoch"],
+        dirpath=ckpt_dir)
+    logger = WandbLogger(
+        project="AR_S1",
+        name=output_dir.stem,
+        save_dir=output_dir,
+        # resume the loss curve
+        resume=True,
+        # id='k19kvsq8'
+    )
+    trainer: Trainer = Trainer(
+        max_epochs=config["train"]["epochs"],
+        accelerator='gpu',
+        devices=-1,
+        benchmark=False,
+        fast_dev_run=False,
+        strategy=DDPStrategy(find_unused_parameters=True),
+        precision=config["train"]["precision"],
+        logger=logger,
+        callbacks=[ckpt_callback])
+
+    model: Text2SemanticLightningModule = Text2SemanticLightningModule(
+        config, output_dir)
+
+    data_module: Text2SemanticDataModule = Text2SemanticDataModule(
+        config,
+        train_semantic_path=args.train_semantic_path,
+        train_phoneme_path=args.train_phoneme_path,
+        dev_semantic_path=args.dev_semantic_path,
+        dev_phoneme_path=args.dev_phoneme_path)
+
+    try:
+        # 使用正则表达式匹配文件名中的数字部分，并按数字大小进行排序
+        newest_ckpt_name = get_newest_ckpt(os.listdir(ckpt_dir))
+        ckpt_path = ckpt_dir / newest_ckpt_name
+    except Exception:
+        ckpt_path = None
+    print("ckpt_path:", ckpt_path)
+    trainer.fit(model, data_module, ckpt_path=ckpt_path)
+
+
+# srun --gpus-per-node=1 --ntasks-per-node=1 python train.py --path-to-configuration configurations/default.yaml
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        '--config_file',
+        type=str,
+        default='conf/default.yaml',
+        help='path of config file')
+    # args for dataset
+    parser.add_argument(
+        '--train_semantic_path',
+        type=str,
+        default='dump/train/semantic_token.tsv')
+    parser.add_argument(
+        '--train_phoneme_path', type=str, default='dump/train/phonemes.npy')
+    parser.add_argument(
+        '--dev_semantic_path', type=str, default='dump/dev/semantic_token.tsv')
+    parser.add_argument(
+        '--dev_phoneme_path', type=str, default='dump/dev/phonemes.npy')
+    parser.add_argument(
+        '--output_dir',
+        type=str,
+        default='exp/default',
+        help='directory to save the results')
+
+    args = parser.parse_args()
+    logging.info(str(args))
+    main(args)
diff --git a/AR/exps/train_librilight_6k.py b/AR/exps/train_librilight_6k.py
new file mode 100644
index 0000000000000000000000000000000000000000..f2c24ada7336d9a3a4f79135673fa6fad79fe922
--- /dev/null
+++ b/AR/exps/train_librilight_6k.py
@@ -0,0 +1,170 @@
+# modified from https://github.com/feng-yufei/shared_debugging_code/blob/main/train_t2s.py
+import argparse
+import logging
+import os
+from pathlib import Path
+
+import torch
+from pytorch_lightning import seed_everything
+from pytorch_lightning import Trainer
+from pytorch_lightning.callbacks import ModelCheckpoint
+from pytorch_lightning.loggers import WandbLogger
+from pytorch_lightning.strategies import DDPStrategy
+from AR.data.data_module_librilight_6k import Text2SemanticDataModule
+from AR.models.t2s_lightning_module import Text2SemanticLightningModule
+from soundstorm.utils import get_newest_ckpt
+from soundstorm.utils.io import load_yaml_config
+
+logging.getLogger('numba').setLevel(logging.WARNING)
+logging.getLogger('matplotlib').setLevel(logging.WARNING)
+torch.set_float32_matmul_precision('high')
+
+
+def main(args):
+    output_dir = Path(args.output_dir)
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    ckpt_dir = output_dir / 'ckpt'
+    ckpt_dir.mkdir(parents=True, exist_ok=True)
+
+    config = load_yaml_config(args.config_file)
+
+    seed_everything(config["train"]["seed"], workers=True)
+
+    ckpt_callback: ModelCheckpoint = ModelCheckpoint(
+        save_top_k=-1,
+        save_on_train_epoch_end=False,
+        every_n_train_steps=config["train"]["every_n_train_steps"],
+        dirpath=ckpt_dir)
+    logger = WandbLogger(
+        project="AR_S1_LibriLight",
+        name=output_dir.stem,
+        save_dir=output_dir,
+        # resume the loss curve
+        resume=True,
+        # id='k19kvsq8'
+    )
+    trainer: Trainer = Trainer(
+        max_epochs=config["train"]["epochs"],
+        accelerator='gpu',
+        devices=-1,
+        benchmark=False,
+        fast_dev_run=False,
+        strategy=DDPStrategy(find_unused_parameters=True),
+        precision=config["train"]["precision"],
+        logger=logger,
+        callbacks=[ckpt_callback])
+
+    model: Text2SemanticLightningModule = Text2SemanticLightningModule(
+        config, output_dir)
+
+    data_module: Text2SemanticDataModule = Text2SemanticDataModule(
+        config,
+        train_semantic_dirs=args.train_semantic_dirs,
+        train_phoneme_dirs=args.train_phoneme_dirs,
+        dev_semantic_dirs=args.dev_semantic_dirs,
+        dev_phoneme_dirs=args.dev_phoneme_dirs,
+        train_non_speech_dirs=args.train_non_speech_dirs,
+        dev_non_speech_dirs=args.dev_non_speech_dirs)
+    try:
+        newest_ckpt_name = get_newest_ckpt(os.listdir(ckpt_dir))
+        ckpt_path = ckpt_dir / newest_ckpt_name
+    except Exception:
+        ckpt_path = None
+
+    print("ckpt_path:", ckpt_path)
+    trainer.fit(model, data_module, ckpt_path=ckpt_path)
+
+
+# srun --gpus-per-node=1 --ntasks-per-node=1 python train.py --path-to-configuration configurations/default.yaml
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        '--config_file',
+        type=str,
+        default='conf/default.yaml',
+        help='path of config file')
+    # args for dataset
+    parser.add_argument(
+        '--train_semantic_dirs',
+        type=list,
+        nargs='+',
+        default=["dump/small/train/"],
+        help='dirs of train semantic')
+    parser.add_argument(
+        '--train_phoneme_dirs',
+        type=list,
+        nargs='+',
+        default=["dump/small/train/"],
+        help='dirs of train phoneme')
+    parser.add_argument(
+        '--dev_semantic_dirs',
+        type=list,
+        nargs='+',
+        default=["dump/small/dev/"],
+        help='dirs of dev semantic')
+    parser.add_argument(
+        '--dev_phoneme_dirs',
+        type=list,
+        nargs='+',
+        default=["dump/small/dev/"],
+        help='dirs of dev phoneme')
+    parser.add_argument(
+        '--output_dir',
+        type=str,
+        default='exp/default',
+        help='directory to save the results')
+
+    parser.add_argument(
+        '--train_non_speech_dirs',
+        type=list,
+        nargs='+',
+        default=None,
+        help='dirs of train non_speech data')
+
+    parser.add_argument(
+        '--dev_non_speech_dirs',
+        type=list,
+        nargs='+',
+        default=None,
+        help='dirs of dev non_speech data')
+
+    args = parser.parse_args()
+
+    new_train_semantic_dirs = []
+    new_train_phoneme_dirs = []
+    new_dev_semantic_dirs = []
+    new_dev_phoneme_dirs = []
+
+    new_train_non_speech_dirs = []
+    new_dev_non_speech_dirs = []
+
+    # format dataset dirs
+    for item in args.train_semantic_dirs:
+        new_train_semantic_dirs.append(''.join(item))
+    args.train_semantic_dirs = new_train_semantic_dirs
+
+    for item in args.train_phoneme_dirs:
+        new_train_phoneme_dirs.append(''.join(item))
+    args.train_phoneme_dirs = new_train_phoneme_dirs
+
+    for item in args.dev_semantic_dirs:
+        new_dev_semantic_dirs.append(''.join(item))
+    args.dev_semantic_dirs = new_dev_semantic_dirs
+
+    for item in args.dev_phoneme_dirs:
+        new_dev_phoneme_dirs.append(''.join(item))
+    args.dev_phoneme_dirs = new_dev_phoneme_dirs
+
+    if args.train_non_speech_dirs is not None:
+        for item in args.train_non_speech_dirs:
+            new_train_non_speech_dirs.append(''.join(item))
+        args.train_non_speech_dirs = new_train_non_speech_dirs
+
+    if args.dev_non_speech_dirs is not None:
+        for item in args.dev_non_speech_dirs:
+            new_dev_non_speech_dirs.append(''.join(item))
+        args.dev_non_speech_dirs = new_dev_non_speech_dirs
+
+    logging.info(str(args))
+    main(args)
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diff --git a/AR/models/t2s_lightning_module.py b/AR/models/t2s_lightning_module.py
new file mode 100644
index 0000000000000000000000000000000000000000..149d88e7d6567b089a3ff028199f62ca6a9cfec8
--- /dev/null
+++ b/AR/models/t2s_lightning_module.py
@@ -0,0 +1,128 @@
+# modified from https://github.com/feng-yufei/shared_debugging_code/blob/main/model/t2s_lightning_module.py
+import os,sys
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+from typing import Dict
+
+import torch
+from pytorch_lightning import LightningModule
+from AR.models.t2s_model import Text2SemanticDecoder
+from AR.modules.lr_schedulers import WarmupCosineLRSchedule
+from AR.modules.optim import ScaledAdam
+
+
+class Text2SemanticLightningModule(LightningModule):
+    def __init__(self, config, output_dir,is_train=True):
+        super().__init__()
+        self.config = config
+        self.top_k = 3
+        self.model = Text2SemanticDecoder(config=config, top_k=self.top_k)
+        pretrained_s1=config.get("pretrained_s1")
+        if(pretrained_s1 and is_train):
+            # print(self.load_state_dict(torch.load(pretrained_s1,map_location="cpu")["state_dict"]))
+            print(self.load_state_dict(torch.load(pretrained_s1,map_location="cpu")["weight"]))
+        if is_train:
+            self.automatic_optimization = False
+            self.save_hyperparameters()
+            self.eval_dir = output_dir / 'eval'
+            self.eval_dir.mkdir(parents=True, exist_ok=True)
+
+    def training_step(self, batch: Dict, batch_idx: int):
+
+        opt = self.optimizers()
+        scheduler = self.lr_schedulers()
+        loss, acc = self.model.forward(
+            batch['phoneme_ids'], batch['phoneme_ids_len'],
+            batch['semantic_ids'], batch['semantic_ids_len'],
+            batch['bert_feature'])
+        self.manual_backward(loss)
+        if batch_idx > 0 and batch_idx % 4 == 0:
+            opt.step()
+            opt.zero_grad()
+            scheduler.step()
+
+        self.log(
+            "total_loss",
+            loss,
+            on_step=True,
+            on_epoch=True,
+            prog_bar=True,
+            sync_dist=True)
+        self.log(
+            "lr",
+            scheduler.get_last_lr()[0],
+            on_epoch=True,
+            prog_bar=True,
+            sync_dist=True)
+        self.log(
+            f"top_{self.top_k}_acc",
+            acc,
+            on_step=True,
+            on_epoch=True,
+            prog_bar=True,
+            sync_dist=True)
+
+    def validation_step(self, batch: Dict, batch_idx: int):return
+        # # get loss
+        # loss, acc = self.model.forward(
+        #     batch['phoneme_ids'], batch['phoneme_ids_len'],
+        #     batch['semantic_ids'], batch['semantic_ids_len'],
+        #     batch['bert_feature']
+        # )
+        #
+        # self.log(
+        #     "val_total_loss",
+        #     loss,
+        #     on_step=True,
+        #     on_epoch=True,
+        #     prog_bar=True,
+        #     sync_dist=True)
+        # self.log(
+        #     f"val_top_{self.top_k}_acc",
+        #     acc,
+        #     on_step=True,
+        #     on_epoch=True,
+        #     prog_bar=True,
+        #     sync_dist=True)
+        #
+        # # get infer output
+        # semantic_len = batch['semantic_ids'].size(1)
+        # prompt_len = min(int(semantic_len * 0.5), 150)
+        # prompt = batch['semantic_ids'][:, :prompt_len]
+        # pred_semantic = self.model.infer(batch['phoneme_ids'],
+        #                                  batch['phoneme_ids_len'], prompt,
+        #                                  batch['bert_feature']
+        #                                  )
+        # save_name = f'semantic_toks_{batch_idx}.pt'
+        # save_path = os.path.join(self.eval_dir, save_name)
+        # torch.save(pred_semantic.detach().cpu(), save_path)
+
+    def configure_optimizers(self):
+        model_parameters = self.model.parameters()
+        parameters_names = []
+        parameters_names.append([
+            name_param_pair[0]
+            for name_param_pair in self.model.named_parameters()
+        ])
+        lm_opt = ScaledAdam(
+            model_parameters,
+            lr=0.01,
+            betas=(0.9, 0.95),
+            clipping_scale=2.0,
+            parameters_names=parameters_names,
+            show_dominant_parameters=False,
+            clipping_update_period=1000, )
+
+        return {
+            "optimizer": lm_opt,
+            "lr_scheduler": {
+                "scheduler":
+                WarmupCosineLRSchedule(
+                    lm_opt,
+                    init_lr=self.config['optimizer']['lr_init'],
+                    peak_lr=self.config['optimizer']['lr'],
+                    end_lr=self.config['optimizer']['lr_end'],
+                    warmup_steps=self.config['optimizer']['warmup_steps'],
+                    total_steps=self.config['optimizer']['decay_steps'])
+            }
+        }
diff --git a/AR/models/t2s_model.py b/AR/models/t2s_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f5337e5ab75cb0791a76be1ca35aff92281f7e5
--- /dev/null
+++ b/AR/models/t2s_model.py
@@ -0,0 +1,298 @@
+# modified from https://github.com/feng-yufei/shared_debugging_code/blob/main/model/t2s_model.py
+import torch
+from tqdm import tqdm
+
+from AR.models.utils import make_pad_mask
+from AR.models.utils import topk_sampling,sample,logits_to_probs,multinomial_sample_one_no_sync
+from AR.modules.embedding import SinePositionalEmbedding
+from AR.modules.embedding import TokenEmbedding
+from AR.modules.transformer import LayerNorm
+from AR.modules.transformer import TransformerEncoder
+from AR.modules.transformer import TransformerEncoderLayer
+from torch import nn
+from torch.nn import functional as F
+from torchmetrics.classification import MulticlassAccuracy
+
+default_config = {
+    "embedding_dim": 512,
+    "hidden_dim": 512,
+    "num_head": 8,
+    "num_layers": 12,
+    "num_codebook": 8,
+    "p_dropout": 0.0,
+    "vocab_size": 1024 + 1,
+    "phoneme_vocab_size": 512,
+    "EOS": 1024
+}
+
+
+class Text2SemanticDecoder(nn.Module):
+    def __init__(self, config, norm_first=False, top_k=3):
+        super(Text2SemanticDecoder, self).__init__()
+        self.model_dim = config['model']["hidden_dim"]
+        self.embedding_dim = config['model']["embedding_dim"]
+        self.num_head = config['model']["head"]
+        self.num_layers = config['model']["n_layer"]
+        self.norm_first = norm_first
+        self.vocab_size = config['model']["vocab_size"]
+        self.phoneme_vocab_size = config['model']["phoneme_vocab_size"]
+        self.p_dropout = config['model']["dropout"]
+        self.EOS = config['model']["EOS"]
+        self.norm_first = norm_first
+        assert self.EOS == self.vocab_size - 1
+        # should be same as num of kmeans bin
+        # assert self.EOS == 1024
+        self.bert_proj = nn.Linear(1024, self.embedding_dim)
+        self.ar_text_embedding = TokenEmbedding(
+            self.embedding_dim, self.phoneme_vocab_size, self.p_dropout)
+        self.ar_text_position = SinePositionalEmbedding(
+            self.embedding_dim, dropout=0.1, scale=False, alpha=True)
+        self.ar_audio_embedding = TokenEmbedding(
+            self.embedding_dim, self.vocab_size, self.p_dropout)
+        self.ar_audio_position = SinePositionalEmbedding(
+            self.embedding_dim, dropout=0.1, scale=False, alpha=True)
+
+        self.h = TransformerEncoder(
+            TransformerEncoderLayer(
+                d_model=self.model_dim,
+                nhead=self.num_head,
+                dim_feedforward=self.model_dim * 4,
+                dropout=0.1,
+                batch_first=True,
+                norm_first=norm_first, ),
+            num_layers=self.num_layers,
+            norm=LayerNorm(self.model_dim) if norm_first else None, )
+
+        self.ar_predict_layer = nn.Linear(
+            self.model_dim, self.vocab_size, bias=False)
+        self.loss_fct = nn.CrossEntropyLoss(reduction='sum')
+
+        self.ar_accuracy_metric = MulticlassAccuracy(
+            self.vocab_size,
+            top_k=top_k,
+            average="micro",
+            multidim_average="global",
+            ignore_index=self.EOS, )
+
+    def forward(self, x, x_lens, y, y_lens, bert_feature):
+        '''
+        x: phoneme_ids
+        y: semantic_ids
+        '''
+        x = self.ar_text_embedding(x)
+        x = x + self.bert_proj(bert_feature.transpose(1,2))
+        x = self.ar_text_position(x)
+        x_mask = make_pad_mask(x_lens)
+
+        y_mask = make_pad_mask(y_lens)
+        y_mask_int = y_mask.type(torch.int64)
+        codes = y.type(torch.int64) * (1 - y_mask_int)
+
+        # Training
+        # AR Decoder
+        y, targets = self.pad_y_eos(codes, y_mask_int, eos_id=self.EOS)
+        x_len = x_lens.max()
+        y_len = y_lens.max()
+        y_emb = self.ar_audio_embedding(y)
+        y_pos = self.ar_audio_position(y_emb)
+
+        xy_padding_mask = torch.concat([x_mask, y_mask], dim=1)
+        ar_xy_padding_mask = xy_padding_mask
+
+        x_attn_mask = F.pad(
+            torch.zeros((x_len, x_len), dtype=torch.bool, device=x.device),
+            (0, y_len),
+            value=True, )
+        y_attn_mask = F.pad(
+            torch.triu(
+                torch.ones(y_len, y_len, dtype=torch.bool, device=x.device),
+                diagonal=1, ),
+            (x_len, 0),
+            value=False, )
+        xy_attn_mask = torch.concat([x_attn_mask, y_attn_mask], dim=0)
+        bsz, src_len = x.shape[0], x_len + y_len
+        _xy_padding_mask = (ar_xy_padding_mask.view(bsz, 1, 1, src_len)
+                            .expand(-1, self.num_head, -1, -1)
+                            .reshape(bsz * self.num_head, 1, src_len))
+        xy_attn_mask = xy_attn_mask.logical_or(_xy_padding_mask)
+        new_attn_mask = torch.zeros_like(xy_attn_mask, dtype=x.dtype)
+        new_attn_mask.masked_fill_(xy_attn_mask, float("-inf"))
+        xy_attn_mask = new_attn_mask
+        # x 和完整的 y 一次性输入模型
+        xy_pos = torch.concat([x, y_pos], dim=1)
+        xy_dec, _ = self.h(
+            (xy_pos, None),
+            mask=xy_attn_mask, )
+        logits = self.ar_predict_layer(xy_dec[:, x_len:]).permute(0, 2, 1)
+        # loss
+        # from feiteng: 每次 duration 越多, 梯度更新也应该更多, 所以用 sum
+        loss = F.cross_entropy(logits, targets, reduction='sum')
+        acc = self.ar_accuracy_metric(logits.detach(), targets).item()
+        return loss, acc
+
+    # 需要看下这个函数和 forward 的区别以及没有 semantic 的时候 prompts 输入什么
+    def infer(self,
+              x,
+              x_lens,
+              prompts,
+              bert_feature,
+              top_k: int=-100,
+              early_stop_num: int=-1,
+              temperature: float=1.0):
+
+        x = self.ar_text_embedding(x)
+        x = x + self.bert_proj(bert_feature.transpose(1,2))
+        x = self.ar_text_position(x)
+
+        # AR Decoder
+        y = prompts
+        prefix_len = y.shape[1]
+        x_len = x.shape[1]
+        x_attn_mask = torch.zeros((x_len, x_len), dtype=torch.bool)
+        stop = False
+        for _ in tqdm(range(1500)):
+            y_emb = self.ar_audio_embedding(y)
+            y_pos = self.ar_audio_position(y_emb)
+            # x 和逐渐增长的 y 一起输入给模型
+            xy_pos = torch.concat([x, y_pos], dim=1)
+            y_len = y.shape[1]
+            x_attn_mask_pad = F.pad(
+                x_attn_mask,
+                (0, y_len),
+                value=True, )
+            y_attn_mask = F.pad(
+                torch.triu(
+                    torch.ones(y_len, y_len, dtype=torch.bool), diagonal=1),
+                (x_len, 0),
+                value=False, )
+            xy_attn_mask = torch.concat(
+                [x_attn_mask_pad, y_attn_mask], dim=0).to(y.device)
+
+            xy_dec, _ = self.h(
+                (xy_pos, None),
+                mask=xy_attn_mask, )
+            logits = self.ar_predict_layer(xy_dec[:, -1])
+            samples = topk_sampling(
+                logits, top_k=top_k, top_p=1.0, temperature=temperature)
+
+            if early_stop_num != -1 and (y.shape[1] - prefix_len
+                                         ) > early_stop_num:
+                print("use early stop num:", early_stop_num)
+                stop = True
+
+            if torch.argmax(
+                    logits, dim=-1)[0] == self.EOS or samples[0, 0] == self.EOS:
+                # print(torch.argmax(logits, dim=-1)[0] == self.EOS, samples[0, 0] == self.EOS)
+                stop = True
+            if stop:
+                if prompts.shape[1] == y.shape[1]:
+                    y = torch.concat([y, torch.zeros_like(samples)], dim=1)
+                    print('bad zero prediction')
+                print(f"T2S Decoding EOS [{prefix_len} -> {y.shape[1]}]")
+                break
+            # 本次生成的 semantic_ids 和之前的 y 构成新的 y
+            # print(samples.shape)#[1,1]#第一个1是bs
+            # import os
+            # os._exit(2333)
+            y = torch.concat([y, samples], dim=1)
+        return y
+
+    def pad_y_eos(self, y, y_mask_int, eos_id):
+        targets = F.pad(
+            y, (0, 1), value=0) + eos_id * F.pad(
+                y_mask_int, (0, 1), value=1)
+        # 错位
+        return targets[:, :-1], targets[:, 1:]
+
+    def infer_panel(self,
+              x,#####全部文本token
+              x_lens,
+              prompts,####参考音频token
+              bert_feature,
+              top_k: int=-100,
+              early_stop_num: int=-1,
+              temperature: float=1.0):
+
+        x = self.ar_text_embedding(x)
+        x = x + self.bert_proj(bert_feature.transpose(1,2))
+        x = self.ar_text_position(x)
+
+        # AR Decoder
+        y = prompts
+        prefix_len = y.shape[1]
+        x_len = x.shape[1]
+        x_attn_mask = torch.zeros((x_len, x_len), dtype=torch.bool)
+        stop = False
+        # print(1111111,self.num_layers)
+        cache={
+            "all_stage":self.num_layers,
+            "k":[None]*self.num_layers,###根据配置自己手写
+            "v":[None]*self.num_layers,
+            # "xy_pos":None,##y_pos位置编码每次都不一样的没法缓存，每次都要重新拼xy_pos.主要还是写法原因，其实是可以历史统一一样的，但也没啥计算量就不管了
+            "y_emb":None,##只需要对最新的samples求emb，再拼历史的就行
+            # "logits":None,###原版就已经只对结尾求再拼接了，不用管
+            # "xy_dec":None,###不需要，本来只需要最后一个做logits
+            "first_infer":1,
+            "stage":0
+        }
+        for idx in tqdm(range(1500)):
+            if(cache["first_infer"]==1):
+                y_emb = self.ar_audio_embedding(y)
+            else:
+                y_emb = torch.cat([cache["y_emb"],self.ar_audio_embedding(y[:,-1:])],1)
+            cache["y_emb"]=y_emb
+            y_pos = self.ar_audio_position(y_emb)
+            # x 和逐渐增长的 y 一起输入给模型
+            if(cache["first_infer"]==1):
+                xy_pos = torch.concat([x, y_pos], dim=1)
+            else:
+                xy_pos=y_pos[:,-1:]
+            y_len = y_pos.shape[1]
+            ###以下3个不做缓存
+            if (cache["first_infer"] == 1):
+                x_attn_mask_pad = F.pad(
+                        x_attn_mask,
+                        (0, y_len),###xx的纯0扩展到xx纯0+xy纯1，(x,x+y)
+                        value=True, )
+                y_attn_mask = F.pad(###yy的右上1扩展到左边xy的0,(y,x+y)
+                    torch.triu(
+                        torch.ones(y_len, y_len, dtype=torch.bool), diagonal=1),
+                    (x_len, 0),
+                    value=False, )
+                xy_attn_mask = torch.concat(
+                    [x_attn_mask_pad, y_attn_mask], dim=0).to(y.device)
+            else:
+                ###最右边一列（是错的）
+                # xy_attn_mask=torch.ones((1, x_len+y_len), dtype=torch.bool,device=xy_pos.device)
+                # xy_attn_mask[:,-1]=False
+                ###最下面一行（是对的）
+                xy_attn_mask = torch.zeros((1, x_len + y_len), dtype=torch.bool, device=xy_pos.device)
+            # pdb.set_trace()
+            ###缓存重头戏
+            # print(1111,xy_pos.shape,xy_attn_mask.shape,x_len,y_len)
+            xy_dec, _ = self.h(
+                (xy_pos, None),
+                mask=xy_attn_mask,cache=cache )
+            logits = self.ar_predict_layer(xy_dec[:, -1])##不用改，如果用了cache的默认就是只有一帧，取最后一帧一样的
+            # samples = topk_sampling(logits, top_k=top_k, top_p=1.0, temperature=temperature)
+            samples = sample(logits[0], y, top_k=top_k, top_p=1.0, repetition_penalty=1.35)[0].unsqueeze(0)
+            if early_stop_num != -1 and (y.shape[1] - prefix_len
+                                         ) > early_stop_num:
+                print("use early stop num:", early_stop_num)
+                stop = True
+
+            if torch.argmax(
+                    logits, dim=-1)[0] == self.EOS or samples[0, 0] == self.EOS:
+                # print(torch.argmax(logits, dim=-1)[0] == self.EOS, samples[0, 0] == self.EOS)
+                stop = True
+            if stop:
+                if prompts.shape[1] == y.shape[1]:
+                    y = torch.concat([y, torch.zeros_like(samples)], dim=1)
+                    print('bad zero prediction')
+                print(f"T2S Decoding EOS [{prefix_len} -> {y.shape[1]}]")
+                break
+            # 本次生成的 semantic_ids 和之前的 y 构成新的 y
+            # print(samples.shape)#[1,1]#第一个1是bs
+            y = torch.concat([y, samples], dim=1)
+            cache["first_infer"]=0
+        return y,idx
diff --git a/AR/models/utils.py b/AR/models/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..01454a7dcac915f044f9d146c128a568dabce092
--- /dev/null
+++ b/AR/models/utils.py
@@ -0,0 +1,164 @@
+# modified from https://github.com/feng-yufei/shared_debugging_code/blob/main/model/utils.py\
+import torch
+import torch.nn.functional as F
+import torchaudio
+
+
+def sequence_mask(length, max_length=None):
+    if max_length is None:
+        max_length = length.max()
+    x = torch.arange(max_length, dtype=length.dtype, device=length.device)
+    return x.unsqueeze(0) < length.unsqueeze(1)
+
+
+def make_pad_mask(lengths: torch.Tensor, max_len: int=0) -> torch.Tensor:
+    """
+    Args:
+      lengths:
+        A 1-D tensor containing sentence lengths.
+      max_len:
+        The length of masks.
+    Returns:
+      Return a 2-D bool tensor, where masked positions
+      are filled with `True` and non-masked positions are
+      filled with `False`.
+
+    #>>> lengths = torch.tensor([1, 3, 2, 5])
+    #>>> make_pad_mask(lengths)
+    tensor([[False,  True,  True,  True,  True],
+            [False, False, False,  True,  True],
+            [False, False,  True,  True,  True],
+            [False, False, False, False, False]])
+    """
+    assert lengths.ndim == 1, lengths.ndim
+    max_len = max(max_len, lengths.max())
+    n = lengths.size(0)
+    seq_range = torch.arange(0, max_len, device=lengths.device)
+    expaned_lengths = seq_range.unsqueeze(0).expand(n, max_len)
+
+    return expaned_lengths >= lengths.unsqueeze(-1)
+
+
+# https://github.com/microsoft/unilm/blob/master/xtune/src/transformers/modeling_utils.py
+def top_k_top_p_filtering(logits,
+                          top_k=0,
+                          top_p=1.0,
+                          filter_value=-float("Inf"),
+                          min_tokens_to_keep=1):
+    """Filter a distribution of logits using top-k and/or nucleus (top-p) filtering
+    Args:
+        logits: logits distribution shape (batch size, vocabulary size)
+        if top_k > 0: keep only top k tokens with highest probability (top-k filtering).
+        if top_p < 1.0: keep the top tokens with cumulative probability >= top_p (nucleus filtering).
+            Nucleus filtering is described in Holtzman et al. (http://arxiv.org/abs/1904.09751)
+        Make sure we keep at least min_tokens_to_keep per batch example in the output
+    From: https://gist.github.com/thomwolf/1a5a29f6962089e871b94cbd09daf317
+    """
+    if top_k > 0:
+        top_k = min(max(top_k, min_tokens_to_keep),
+                    logits.size(-1))  # Safety check
+        # Remove all tokens with a probability less than the last token of the top-k
+        indices_to_remove = logits < torch.topk(logits, top_k)[0][..., -1, None]
+        logits[indices_to_remove] = filter_value
+
+    if top_p < 1.0:
+        sorted_logits, sorted_indices = torch.sort(logits, descending=True)
+        cumulative_probs = torch.cumsum(
+            F.softmax(sorted_logits, dim=-1), dim=-1)
+
+        # Remove tokens with cumulative probability above the threshold (token with 0 are kept)
+        sorted_indices_to_remove = cumulative_probs > top_p
+        if min_tokens_to_keep > 1:
+            # Keep at least min_tokens_to_keep (set to min_tokens_to_keep-1 because we add the first one below)
+            sorted_indices_to_remove[..., :min_tokens_to_keep] = 0
+        # Shift the indices to the right to keep also the first token above the threshold
+        sorted_indices_to_remove[..., 1:] = sorted_indices_to_remove[
+            ..., :-1].clone()
+        sorted_indices_to_remove[..., 0] = 0
+
+        # scatter sorted tensors to original indexing
+        indices_to_remove = sorted_indices_to_remove.scatter(
+            1, sorted_indices, sorted_indices_to_remove)
+        logits[indices_to_remove] = filter_value
+    return logits
+
+
+def topk_sampling(logits, top_k=10, top_p=1.0, temperature=1.0):
+    # temperature: (`optional`) float
+    #     The value used to module the next token probabilities. Must be strictly positive. Default to 1.0.
+    # top_k: (`optional`) int
+    #     The number of highest probability vocabulary tokens to keep for top-k-filtering. Between 1 and infinity. Default to 50.
+    # top_p: (`optional`) float
+    #     The cumulative probability of parameter highest probability vocabulary tokens to keep for nucleus sampling. Must be between 0 and 1. Default to 1.
+
+    # Temperature (higher temperature => more likely to sample low probability tokens)
+    if temperature != 1.0:
+        logits = logits / temperature
+    # Top-p/top-k filtering
+    logits = top_k_top_p_filtering(logits, top_k=top_k, top_p=top_p)
+    # Sample
+    token = torch.multinomial(F.softmax(logits, dim=-1), num_samples=1)
+    return token
+
+
+from typing import Optional, Tuple
+def multinomial_sample_one_no_sync(
+    probs_sort,
+):  # Does multinomial sampling without a cuda synchronization
+    q = torch.empty_like(probs_sort).exponential_(1)
+    return torch.argmax(probs_sort / q, dim=-1, keepdim=True).to(dtype=torch.int)
+
+
+def logits_to_probs(
+    logits,
+    previous_tokens: Optional[torch.Tensor] = None,
+    temperature: float = 1.0,
+    top_k: Optional[int] = None,
+    top_p: Optional[int] = None,
+    repetition_penalty: float = 1.0,
+):
+    previous_tokens=previous_tokens.squeeze()
+    # print(logits.shape,previous_tokens.shape)
+    # pdb.set_trace()
+    if previous_tokens is not None and repetition_penalty != 1.0:
+        previous_tokens = previous_tokens.long()
+        score = torch.gather(logits, dim=0, index=previous_tokens)
+        score = torch.where(
+            score < 0, score * repetition_penalty, score / repetition_penalty
+        )
+        logits.scatter_(dim=0, index=previous_tokens, src=score)
+
+    if top_p is not None and top_p < 1.0:
+        sorted_logits, sorted_indices = torch.sort(logits, descending=True)
+        cum_probs = torch.cumsum(
+            torch.nn.functional.softmax(sorted_logits, dim=-1), dim=-1
+        )
+        sorted_indices_to_remove = cum_probs > top_p
+        sorted_indices_to_remove[0] = False  # keep at least one option
+        indices_to_remove = sorted_indices_to_remove.scatter(
+            dim=0, index=sorted_indices, src=sorted_indices_to_remove
+        )
+        logits = logits.masked_fill(indices_to_remove, -float("Inf"))
+
+    logits = logits / max(temperature, 1e-5)
+
+    if top_k is not None:
+        v, _ = torch.topk(logits, min(top_k, logits.size(-1)))
+        pivot = v.select(-1, -1).unsqueeze(-1)
+        logits = torch.where(logits < pivot, -float("Inf"), logits)
+
+    probs = torch.nn.functional.softmax(logits, dim=-1)
+    return probs
+
+
+def sample(
+    logits,
+    previous_tokens: Optional[torch.Tensor] = None,
+    **sampling_kwargs,
+) -> Tuple[torch.Tensor, torch.Tensor]:
+    probs = logits_to_probs(
+        logits=logits, previous_tokens=previous_tokens, **sampling_kwargs
+    )
+    idx_next = multinomial_sample_one_no_sync(probs)
+    return idx_next, probs
+
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diff --git a/AR/modules/activation.py b/AR/modules/activation.py
new file mode 100644
index 0000000000000000000000000000000000000000..50631e94e1a9a4e572813e524c79fce747c52940
--- /dev/null
+++ b/AR/modules/activation.py
@@ -0,0 +1,397 @@
+# modified from https://github.com/lifeiteng/vall-e/blob/main/valle/modules/activation.py
+from typing import Optional
+from typing import Tuple
+import torch
+from torch import Tensor
+from torch.nn import Linear
+from torch.nn import Module
+from torch.nn.init import constant_
+from torch.nn.init import xavier_normal_
+from torch.nn.init import xavier_uniform_
+from torch.nn.modules.linear import NonDynamicallyQuantizableLinear
+from torch.nn.parameter import Parameter
+
+from torch.nn import functional as F
+from AR.modules.patched_mha_with_cache import multi_head_attention_forward_patched
+F.multi_head_attention_forward=multi_head_attention_forward_patched
+
+class MultiheadAttention(Module):
+    r"""Allows the model to jointly attend to information
+    from different representation subspaces as described in the paper:
+    `Attention Is All You Need <https://arxiv.org/abs/1706.03762>`_.
+
+    Multi-Head Attention is defined as:
+
+    .. math::
+        \text{MultiHead}(Q, K, V) = \text{Concat}(head_1,\dots,head_h)W^O
+
+    where :math:`head_i = \text{Attention}(QW_i^Q, KW_i^K, VW_i^V)`.
+
+    ``forward()`` will use a special optimized implementation if all of the following
+    conditions are met:
+
+    - self attention is being computed (i.e., ``query``, ``key``, and ``value`` are the same tensor. This
+      restriction will be loosened in the future.)
+    - Either autograd is disabled (using ``torch.inference_mode`` or ``torch.no_grad``) or no tensor argument ``requires_grad``
+    - training is disabled (using ``.eval()``)
+    - dropout is 0
+    - ``add_bias_kv`` is ``False``
+    - ``add_zero_attn`` is ``False``
+    - ``batch_first`` is ``True`` and the input is batched
+    - ``kdim`` and ``vdim`` are equal to ``embed_dim``
+    - at most one of ``key_padding_mask`` or ``attn_mask`` is passed
+    - if a `NestedTensor <https://pytorch.org/docs/stable/nested.html>`_ is passed, neither ``key_padding_mask``
+      nor ``attn_mask`` is passed
+
+    If the optimized implementation is in use, a
+    `NestedTensor <https://pytorch.org/docs/stable/nested.html>`_ can be passed for
+    ``query``/``key``/``value`` to represent padding more efficiently than using a
+    padding mask. In this case, a `NestedTensor <https://pytorch.org/docs/stable/nested.html>`_
+    will be returned, and an additional speedup proportional to the fraction of the input
+    that is padding can be expected.
+
+    Args:
+        embed_dim: Total dimension of the model.
+        num_heads: Number of parallel attention heads. Note that ``embed_dim`` will be split
+            across ``num_heads`` (i.e. each head will have dimension ``embed_dim // num_heads``).
+        dropout: Dropout probability on ``attn_output_weights``. Default: ``0.0`` (no dropout).
+        bias: If specified, adds bias to input / output projection layers. Default: ``True``.
+        add_bias_kv: If specified, adds bias to the key and value sequences at dim=0. Default: ``False``.
+        add_zero_attn: If specified, adds a new batch of zeros to the key and value sequences at dim=1.
+            Default: ``False``.
+        kdim: Total number of features for keys. Default: ``None`` (uses ``kdim=embed_dim``).
+        vdim: Total number of features for values. Default: ``None`` (uses ``vdim=embed_dim``).
+        batch_first: If ``True``, then the input and output tensors are provided
+            as (batch, seq, feature). Default: ``False`` (seq, batch, feature).
+
+    Examples::
+
+        >>> # xdoctest: +SKIP
+        >>> multihead_attn = nn.MultiheadAttention(embed_dim, num_heads)
+        >>> attn_output, attn_output_weights = multihead_attn(query, key, value)
+
+    """
+    __constants__ = ["batch_first"]
+    bias_k: Optional[torch.Tensor]
+    bias_v: Optional[torch.Tensor]
+
+    def __init__(
+            self,
+            embed_dim,
+            num_heads,
+            dropout=0.0,
+            bias=True,
+            add_bias_kv=False,
+            add_zero_attn=False,
+            kdim=None,
+            vdim=None,
+            batch_first=False,
+            linear1_cls=Linear,
+            linear2_cls=Linear,
+            device=None,
+            dtype=None, ) -> None:
+        factory_kwargs = {"device": device, "dtype": dtype}
+        super(MultiheadAttention, self).__init__()
+        self.embed_dim = embed_dim
+        self.kdim = kdim if kdim is not None else embed_dim
+        self.vdim = vdim if vdim is not None else embed_dim
+        self._qkv_same_embed_dim = (self.kdim == embed_dim and
+                                    self.vdim == embed_dim)
+
+        self.num_heads = num_heads
+        self.dropout = dropout
+        self.batch_first = batch_first
+        self.head_dim = embed_dim // num_heads
+        assert (self.head_dim * num_heads == self.embed_dim
+                ), "embed_dim must be divisible by num_heads"
+
+        if add_bias_kv:
+            self.bias_k = Parameter(
+                torch.empty((1, 1, embed_dim), **factory_kwargs))
+            self.bias_v = Parameter(
+                torch.empty((1, 1, embed_dim), **factory_kwargs))
+        else:
+            self.bias_k = self.bias_v = None
+
+        if linear1_cls == Linear:
+            if not self._qkv_same_embed_dim:
+                self.q_proj_weight = Parameter(
+                    torch.empty((embed_dim, embed_dim), **factory_kwargs))
+                self.k_proj_weight = Parameter(
+                    torch.empty((embed_dim, self.kdim), **factory_kwargs))
+                self.v_proj_weight = Parameter(
+                    torch.empty((embed_dim, self.vdim), **factory_kwargs))
+                self.register_parameter("in_proj_weight", None)
+            else:
+                self.in_proj_weight = Parameter(
+                    torch.empty((3 * embed_dim, embed_dim), **factory_kwargs))
+                self.register_parameter("q_proj_weight", None)
+                self.register_parameter("k_proj_weight", None)
+                self.register_parameter("v_proj_weight", None)
+
+            if bias:
+                self.in_proj_bias = Parameter(
+                    torch.empty(3 * embed_dim, **factory_kwargs))
+            else:
+                self.register_parameter("in_proj_bias", None)
+            self.out_proj = NonDynamicallyQuantizableLinear(
+                embed_dim, embed_dim, bias=bias, **factory_kwargs)
+
+            self._reset_parameters()
+        else:
+            if not self._qkv_same_embed_dim:
+                raise NotImplementedError
+            else:
+                self.in_proj_linear = linear1_cls(
+                    embed_dim, 3 * embed_dim, bias=bias, **factory_kwargs)
+                self.in_proj_weight = self.in_proj_linear.weight
+
+                self.register_parameter("q_proj_weight", None)
+                self.register_parameter("k_proj_weight", None)
+                self.register_parameter("v_proj_weight", None)
+
+                if bias:
+                    self.in_proj_bias = self.in_proj_linear.bias
+                else:
+                    self.register_parameter("in_proj_bias", None)
+
+            self.out_proj = linear2_cls(
+                embed_dim, embed_dim, bias=bias, **factory_kwargs)
+
+            if self.bias_k is not None:
+                xavier_normal_(self.bias_k)
+            if self.bias_v is not None:
+                xavier_normal_(self.bias_v)
+
+        self.add_zero_attn = add_zero_attn
+
+    def _reset_parameters(self):
+        if self._qkv_same_embed_dim:
+            xavier_uniform_(self.in_proj_weight)
+        else:
+            xavier_uniform_(self.q_proj_weight)
+            xavier_uniform_(self.k_proj_weight)
+            xavier_uniform_(self.v_proj_weight)
+
+        if self.in_proj_bias is not None:
+            constant_(self.in_proj_bias, 0.0)
+            constant_(self.out_proj.bias, 0.0)
+
+        if self.bias_k is not None:
+            xavier_normal_(self.bias_k)
+        if self.bias_v is not None:
+            xavier_normal_(self.bias_v)
+
+    def __setstate__(self, state):
+        # Support loading old MultiheadAttention checkpoints generated by v1.1.0
+        if "_qkv_same_embed_dim" not in state:
+            state["_qkv_same_embed_dim"] = True
+
+        super(MultiheadAttention, self).__setstate__(state)
+
+    def forward(
+            self,
+            query: Tensor,
+            key: Tensor,
+            value: Tensor,
+            key_padding_mask: Optional[Tensor]=None,
+            need_weights: bool=True,
+            attn_mask: Optional[Tensor]=None,
+            average_attn_weights: bool=True,cache=None
+    ) -> Tuple[Tensor, Optional[Tensor]]:
+        r"""
+        Args:
+            query: Query embeddings of shape :math:`(L, E_q)` for unbatched input, :math:`(L, N, E_q)` when ``batch_first=False``
+                or :math:`(N, L, E_q)` when ``batch_first=True``, where :math:`L` is the target sequence length,
+                :math:`N` is the batch size, and :math:`E_q` is the query embedding dimension ``embed_dim``.
+                Queries are compared against key-value pairs to produce the output.
+                See "Attention Is All You Need" for more details.
+            key: Key embeddings of shape :math:`(S, E_k)` for unbatched input, :math:`(S, N, E_k)` when ``batch_first=False``
+                or :math:`(N, S, E_k)` when ``batch_first=True``, where :math:`S` is the source sequence length,
+                :math:`N` is the batch size, and :math:`E_k` is the key embedding dimension ``kdim``.
+                See "Attention Is All You Need" for more details.
+            value: Value embeddings of shape :math:`(S, E_v)` for unbatched input, :math:`(S, N, E_v)` when
+                ``batch_first=False`` or :math:`(N, S, E_v)` when ``batch_first=True``, where :math:`S` is the source
+                sequence length, :math:`N` is the batch size, and :math:`E_v` is the value embedding dimension ``vdim``.
+                See "Attention Is All You Need" for more details.
+            key_padding_mask: If specified, a mask of shape :math:`(N, S)` indicating which elements within ``key``
+                to ignore for the purpose of attention (i.e. treat as "padding"). For unbatched `query`, shape should be :math:`(S)`.
+                Binary and byte masks are supported.
+                For a binary mask, a ``True`` value indicates that the corresponding ``key`` value will be ignored for
+                the purpose of attention. For a float mask, it will be directly added to the corresponding ``key`` value.
+            need_weights: If specified, returns ``attn_output_weights`` in addition to ``attn_outputs``.
+                Default: ``True``.
+            attn_mask: If specified, a 2D or 3D mask preventing attention to certain positions. Must be of shape
+                :math:`(L, S)` or :math:`(N\cdot\text{num\_heads}, L, S)`, where :math:`N` is the batch size,
+                :math:`L` is the target sequence length, and :math:`S` is the source sequence length. A 2D mask will be
+                broadcasted across the batch while a 3D mask allows for a different mask for each entry in the batch.
+                Binary, byte, and float masks are supported. For a binary mask, a ``True`` value indicates that the
+                corresponding position is not allowed to attend. For a byte mask, a non-zero value indicates that the
+                corresponding position is not allowed to attend. For a float mask, the mask values will be added to
+                the attention weight.
+            average_attn_weights: If true, indicates that the returned ``attn_weights`` should be averaged across
+                heads. Otherwise, ``attn_weights`` are provided separately per head. Note that this flag only has an
+                effect when ``need_weights=True``. Default: ``True`` (i.e. average weights across heads)
+
+        Outputs:
+            - **attn_output** - Attention outputs of shape :math:`(L, E)` when input is unbatched,
+              :math:`(L, N, E)` when ``batch_first=False`` or :math:`(N, L, E)` when ``batch_first=True``,
+              where :math:`L` is the target sequence length, :math:`N` is the batch size, and :math:`E` is the
+              embedding dimension ``embed_dim``.
+            - **attn_output_weights** - Only returned when ``need_weights=True``. If ``average_attn_weights=True``,
+              returns attention weights averaged across heads of shape :math:`(L, S)` when input is unbatched or
+              :math:`(N, L, S)`, where :math:`N` is the batch size, :math:`L` is the target sequence length, and
+              :math:`S` is the source sequence length. If ``average_attn_weights=False``, returns attention weights per
+              head of shape :math:`(\text{num\_heads}, L, S)` when input is unbatched or :math:`(N, \text{num\_heads}, L, S)`.
+
+            .. note::
+                `batch_first` argument is ignored for unbatched inputs.
+        """
+        is_batched = query.dim() == 3
+        if key_padding_mask is not None:
+            _kpm_dtype = key_padding_mask.dtype
+            if _kpm_dtype != torch.bool and not torch.is_floating_point(
+                    key_padding_mask):
+                raise AssertionError(
+                    "only bool and floating types of key_padding_mask are supported"
+                )
+        why_not_fast_path = ""
+        if not is_batched:
+            why_not_fast_path = f"input not batched; expected query.dim() of 3 but got {query.dim()}"
+        elif query is not key or key is not value:
+            # When lifting this restriction, don't forget to either
+            # enforce that the dtypes all match or test cases where
+            # they don't!
+            why_not_fast_path = "non-self attention was used (query, key, and value are not the same Tensor)"
+        elif (self.in_proj_bias is not None and
+              query.dtype != self.in_proj_bias.dtype):
+            why_not_fast_path = f"dtypes of query ({query.dtype}) and self.in_proj_bias ({self.in_proj_bias.dtype}) don't match"
+        elif (self.in_proj_weight is not None and
+              query.dtype != self.in_proj_weight.dtype):
+            # this case will fail anyway, but at least they'll get a useful error message.
+            why_not_fast_path = f"dtypes of query ({query.dtype}) and self.in_proj_weight ({self.in_proj_weight.dtype}) don't match"
+        elif self.training:
+            why_not_fast_path = "training is enabled"
+        elif not self.batch_first:
+            why_not_fast_path = "batch_first was not True"
+        elif self.bias_k is not None:
+            why_not_fast_path = "self.bias_k was not None"
+        elif self.bias_v is not None:
+            why_not_fast_path = "self.bias_v was not None"
+        elif self.dropout:
+            why_not_fast_path = f"dropout was {self.dropout}, required zero"
+        elif self.add_zero_attn:
+            why_not_fast_path = "add_zero_attn was enabled"
+        elif not self._qkv_same_embed_dim:
+            why_not_fast_path = "_qkv_same_embed_dim was not True"
+        elif attn_mask is not None:
+            why_not_fast_path = "attn_mask was not None"
+        elif query.is_nested and key_padding_mask is not None:
+            why_not_fast_path = (
+                "key_padding_mask is not supported with NestedTensor input")
+        elif self.num_heads % 2 == 1:
+            why_not_fast_path = "num_heads is odd"
+        elif torch.is_autocast_enabled():
+            why_not_fast_path = "autocast is enabled"
+
+        if not why_not_fast_path:
+            tensor_args = (query, key, value, self.in_proj_weight,
+                           self.in_proj_bias, self.out_proj.weight,
+                           self.out_proj.bias, )
+            # We have to use list comprehensions below because TorchScript does not support
+            # generator expressions.
+            if torch.overrides.has_torch_function(tensor_args):
+                why_not_fast_path = "some Tensor argument has_torch_function"
+            elif not all([(x is None or x.is_cuda or "cpu" in str(x.device))
+                          for x in tensor_args]):
+                why_not_fast_path = (
+                    "some Tensor argument is neither CUDA nor CPU")
+            elif torch.is_grad_enabled() and any(
+                [x is not None and x.requires_grad for x in tensor_args]):
+                why_not_fast_path = (
+                    "grad is enabled and at least one of query or the "
+                    "input/output projection weights or biases requires_grad")
+            if not why_not_fast_path:
+                return torch._native_multi_head_attention(
+                    query,
+                    key,
+                    value,
+                    self.embed_dim,
+                    self.num_heads,
+                    self.in_proj_weight,
+                    self.in_proj_bias,
+                    self.out_proj.weight,
+                    self.out_proj.bias,
+                    key_padding_mask
+                    if key_padding_mask is not None else attn_mask,
+                    need_weights,
+                    average_attn_weights,
+                    1 if key_padding_mask is not None else 0
+                    if attn_mask is not None else None, )
+
+        any_nested = query.is_nested or key.is_nested or value.is_nested
+        assert not any_nested, (
+            "MultiheadAttention does not support NestedTensor outside of its fast path. "
+            + f"The fast path was not hit because {why_not_fast_path}")
+
+        if self.batch_first and is_batched:
+            # make sure that the transpose op does not affect the "is" property
+            if key is value:
+                if query is key:
+                    query = key = value = query.transpose(1, 0)
+                else:
+                    query, key = [x.transpose(1, 0) for x in (query, key)]
+                    value = key
+            else:
+                query, key, value = [
+                    x.transpose(1, 0) for x in (query, key, value)
+                ]
+
+        if not self._qkv_same_embed_dim:
+            attn_output, attn_output_weights = F.multi_head_attention_forward(
+                query,
+                key,
+                value,
+                self.embed_dim,
+                self.num_heads,
+                self.in_proj_weight,
+                self.in_proj_bias,
+                self.bias_k,
+                self.bias_v,
+                self.add_zero_attn,
+                self.dropout,
+                self.out_proj.weight,
+                self.out_proj.bias,
+                training=self.training,
+                key_padding_mask=key_padding_mask,
+                need_weights=need_weights,
+                attn_mask=attn_mask,
+                use_separate_proj_weight=True,
+                q_proj_weight=self.q_proj_weight,
+                k_proj_weight=self.k_proj_weight,
+                v_proj_weight=self.v_proj_weight,
+                average_attn_weights=average_attn_weights,cache=cache )
+        else:
+            attn_output, attn_output_weights = F.multi_head_attention_forward(
+                query,
+                key,
+                value,
+                self.embed_dim,
+                self.num_heads,
+                self.in_proj_weight,
+                self.in_proj_bias,
+                self.bias_k,
+                self.bias_v,
+                self.add_zero_attn,
+                self.dropout,
+                self.out_proj.weight,
+                self.out_proj.bias,
+                training=self.training,
+                key_padding_mask=key_padding_mask,
+                need_weights=need_weights,
+                attn_mask=attn_mask,
+                average_attn_weights=average_attn_weights,cache=cache )
+        if self.batch_first and is_batched:
+            return attn_output.transpose(1, 0), attn_output_weights
+        else:
+            return attn_output, attn_output_weights
diff --git a/AR/modules/embedding.py b/AR/modules/embedding.py
new file mode 100644
index 0000000000000000000000000000000000000000..35063c7c8913bc3891306bf44ba02d897f43a7b3
--- /dev/null
+++ b/AR/modules/embedding.py
@@ -0,0 +1,78 @@
+# modified from https://github.com/lifeiteng/vall-e/blob/main/valle/modules/embedding.py
+import math
+
+import torch
+from torch import nn
+
+
+class TokenEmbedding(nn.Module):
+    def __init__(
+            self,
+            embedding_dim: int,
+            vocab_size: int,
+            dropout: float=0.0, ):
+        super().__init__()
+
+        self.vocab_size = vocab_size
+        self.embedding_dim = embedding_dim
+
+        self.dropout = torch.nn.Dropout(p=dropout)
+        self.word_embeddings = nn.Embedding(self.vocab_size, self.embedding_dim)
+
+    @property
+    def weight(self) -> torch.Tensor:
+        return self.word_embeddings.weight
+
+    def embedding(self, index: int) -> torch.Tensor:
+        return self.word_embeddings.weight[index:index + 1]
+
+    def forward(self, x: torch.Tensor):
+        x = self.word_embeddings(x)
+        x = self.dropout(x)
+        return x
+
+
+class SinePositionalEmbedding(nn.Module):
+    def __init__(
+            self,
+            embedding_dim: int,
+            dropout: float=0.0,
+            scale: bool=False,
+            alpha: bool=False, ):
+        super().__init__()
+        self.embedding_dim = embedding_dim
+        self.x_scale = math.sqrt(embedding_dim) if scale else 1.0
+        self.alpha = nn.Parameter(torch.ones(1), requires_grad=alpha)
+        self.dropout = torch.nn.Dropout(p=dropout)
+
+        self.reverse = False
+        self.pe = None
+        self.extend_pe(torch.tensor(0.0).expand(1, 4000))
+
+    def extend_pe(self, x):
+        """Reset the positional encodings."""
+        if self.pe is not None:
+            if self.pe.size(1) >= x.size(1):
+                if self.pe.dtype != x.dtype or self.pe.device != x.device:
+                    self.pe = self.pe.to(dtype=x.dtype, device=x.device)
+                return
+        pe = torch.zeros(x.size(1), self.embedding_dim)
+        if self.reverse:
+            position = torch.arange(
+                x.size(1) - 1, -1, -1.0, dtype=torch.float32).unsqueeze(1)
+        else:
+            position = torch.arange(
+                0, x.size(1), dtype=torch.float32).unsqueeze(1)
+        div_term = torch.exp(
+            torch.arange(0, self.embedding_dim, 2, dtype=torch.float32) *
+            -(math.log(10000.0) / self.embedding_dim))
+        pe[:, 0::2] = torch.sin(position * div_term)
+        pe[:, 1::2] = torch.cos(position * div_term)
+        pe = pe.unsqueeze(0)
+        self.pe = pe.to(device=x.device, dtype=x.dtype).detach()
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        self.extend_pe(x)
+        output = x.unsqueeze(-1) if x.ndim == 2 else x
+        output = output * self.x_scale + self.alpha * self.pe[:, :x.size(1)]
+        return self.dropout(output)
diff --git a/AR/modules/lr_schedulers.py b/AR/modules/lr_schedulers.py
new file mode 100644
index 0000000000000000000000000000000000000000..955d8040c8028838a30850895c01eac2b7400df6
--- /dev/null
+++ b/AR/modules/lr_schedulers.py
@@ -0,0 +1,85 @@
+# modified from https://github.com/feng-yufei/shared_debugging_code/blob/main/model/lr_schedulers.py
+import math
+
+import torch
+from matplotlib import pyplot as plt
+from torch import nn
+from torch.optim import Adam
+
+
+class WarmupCosineLRSchedule(torch.optim.lr_scheduler._LRScheduler):
+    """
+    Implements Warmup learning rate schedule until 'warmup_steps', going from 'init_lr' to 'peak_lr' for multiple optimizers.
+    """
+
+    def __init__(self,
+                 optimizer,
+                 init_lr,
+                 peak_lr,
+                 end_lr,
+                 warmup_steps=10000,
+                 total_steps=400000,
+                 current_step=0):
+        self.init_lr = init_lr
+        self.peak_lr = peak_lr
+        self.end_lr = end_lr
+        self.optimizer = optimizer
+        self._warmup_rate = (peak_lr - init_lr) / warmup_steps
+        self._decay_rate = (end_lr - peak_lr) / (total_steps - warmup_steps)
+        self._current_step = current_step
+        self.lr = init_lr
+        self.warmup_steps = warmup_steps
+        self.total_steps = total_steps
+        self._last_lr = [self.lr]
+
+    def set_lr(self, lr):
+        self._last_lr = [g['lr'] for g in self.optimizer.param_groups]
+        for g in self.optimizer.param_groups:
+            # g['lr'] = lr
+            g['lr'] = self.end_lr###锁定用线性
+
+    def step(self):
+        if self._current_step < self.warmup_steps:
+            lr = self.init_lr + self._warmup_rate * self._current_step
+
+        elif self._current_step > self.total_steps:
+            lr = self.end_lr
+
+        else:
+            decay_ratio = (self._current_step - self.warmup_steps) / (
+                self.total_steps - self.warmup_steps)
+            if decay_ratio < 0.0 or decay_ratio > 1.0:
+                raise RuntimeError(
+                    "Decay ratio must be in [0.0, 1.0]. Fix LR scheduler settings."
+                )
+            coeff = 0.5 * (1.0 + math.cos(math.pi * decay_ratio))
+            lr = self.end_lr + coeff * (self.peak_lr - self.end_lr)
+
+        self.lr=lr=self.end_lr=0.002###锁定用线性###不听话，直接锁定！
+        self.set_lr(lr)
+        self.lr = lr
+        self._current_step += 1
+        return self.lr
+
+
+
+if __name__ == '__main__':
+    m = nn.Linear(10, 10)
+    opt = Adam(m.parameters(), lr=1e-4)
+    s = WarmupCosineLRSchedule(
+        opt,
+        1e-6,
+        2e-4,
+        1e-6,
+        warmup_steps=2000,
+        total_steps=20000,
+        current_step=0)
+    lrs = []
+    for i in range(25000):
+        s.step()
+        lrs.append(s.lr)
+        print(s.lr)
+
+    plt.plot(lrs)
+    plt.plot(range(0, 25000), lrs)
+    plt.show()
diff --git a/AR/modules/optim.py b/AR/modules/optim.py
new file mode 100644
index 0000000000000000000000000000000000000000..98785f05b2e3aa123ae22955d677b9f68efec256
--- /dev/null
+++ b/AR/modules/optim.py
@@ -0,0 +1,622 @@
+# Copyright      2022  Xiaomi Corp.        (authors: Daniel Povey)
+#
+# See ../LICENSE for clarification regarding multiple authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import contextlib
+import logging
+from collections import defaultdict
+from typing import List
+from typing import Tuple
+
+import torch
+from torch import Tensor
+from torch.optim import Optimizer
+
+
+class BatchedOptimizer(Optimizer):
+    """
+    This class adds to class Optimizer the capability to optimize parameters in batches:
+    it will stack the parameters and their grads for you so the optimizer can work
+    on tensors with an extra leading dimension.  This is intended for speed with GPUs,
+    as it reduces the number of kernels launched in the optimizer.
+
+    Args:
+      params:
+    """
+
+    def __init__(self, params, defaults):
+        super(BatchedOptimizer, self).__init__(params, defaults)
+
+    @contextlib.contextmanager
+    def batched_params(self, param_group, group_params_names):
+        """
+        This function returns (technically, yields) a list of
+          of tuples (p, state), where
+        p is a `fake` parameter that is stacked (over axis 0) from real parameters
+        that share the same shape, and its gradient is also stacked;
+        `state` is the state corresponding to this batch of parameters
+        (it will be physically located in the "state" for one of the real
+        parameters, the last one that has any particular shape and dtype).
+
+        This function is decorated as a context manager so that it can
+        write parameters back to their "real" locations.
+
+        The idea is, instead of doing:
+        <code>
+          for p in group["params"]:
+             state = self.state[p]
+             ...
+        </code>
+        you can do:
+        <code>
+          with self.batched_params(group["params"]) as batches:
+             for p, state, p_names in batches:
+                 ...
+        </code>
+
+        Args:
+          group: a parameter group, which is a list of parameters; should be
+                one of self.param_groups.
+          group_params_names: name for each parameter in group,
+                which is List[str].
+        """
+        batches = defaultdict(
+            list
+        )  # `batches` maps from tuple (dtype_as_str,*shape) to list of nn.Parameter
+        batches_names = defaultdict(
+            list
+        )  # `batches` maps from tuple (dtype_as_str,*shape) to list of str
+
+        assert len(param_group) == len(group_params_names)
+        for p, named_p in zip(param_group, group_params_names):
+            key = (str(p.dtype), *p.shape)
+            batches[key].append(p)
+            batches_names[key].append(named_p)
+
+        batches_names_keys = list(batches_names.keys())
+        sorted_idx = sorted(
+            range(len(batches_names)), key=lambda i: batches_names_keys[i])
+        batches_names = [
+            batches_names[batches_names_keys[idx]] for idx in sorted_idx
+        ]
+        batches = [batches[batches_names_keys[idx]] for idx in sorted_idx]
+
+        stacked_params_dict = dict()
+
+        # turn batches into a list, in deterministic order.
+        # tuples will contain tuples of (stacked_param, state, stacked_params_names),
+        # one for each batch in `batches`.
+        tuples = []
+
+        for batch, batch_names in zip(batches, batches_names):
+            p = batch[0]
+            # we arbitrarily store the state in the
+            # state corresponding to the 1st parameter in the
+            # group.  class Optimizer will take care of saving/loading state.
+            state = self.state[p]
+            p_stacked = torch.stack(batch)
+            grad = torch.stack([
+                torch.zeros_like(p) if p.grad is None else p.grad for p in batch
+            ])
+            p_stacked.grad = grad
+            stacked_params_dict[key] = p_stacked
+            tuples.append((p_stacked, state, batch_names))
+
+        yield tuples  # <-- calling code will do the actual optimization here!
+
+        for ((stacked_params, _state, _names), batch) in zip(tuples, batches):
+            for i, p in enumerate(batch):  # batch is list of Parameter
+                p.copy_(stacked_params[i])
+
+
+class ScaledAdam(BatchedOptimizer):
+    """
+     Implements 'Scaled Adam', a variant of Adam where we scale each parameter's update
+     proportional to the norm of that parameter; and also learn the scale of the parameter,
+     in log space, subject to upper and lower limits (as if we had factored each parameter as
+     param = underlying_param * log_scale.exp())
+
+
+     Args:
+          params:  The parameters or param_groups to optimize (like other Optimizer subclasses)
+              lr:  The learning rate.  We will typically use a learning rate schedule that starts
+                   at 0.03 and decreases over time, i.e. much higher than other common
+                   optimizers.
+     clipping_scale: (e.g. 2.0)
+                   A scale for gradient-clipping: if specified, the normalized gradients
+                   over the whole model will be clipped to have 2-norm equal to
+                   `clipping_scale` times the median 2-norm over the most recent period
+                   of `clipping_update_period` minibatches.  By "normalized gradients",
+                   we mean after multiplying by the rms parameter value for this tensor
+                   [for non-scalars]; this is appropriate because our update is scaled
+                   by this quantity.
+            betas: beta1,beta2 are momentum constants for regular momentum, and moving sum-sq grad.
+                   Must satisfy 0 < beta <= beta2 < 1.
+     scalar_lr_scale: A scaling factor on the learning rate, that we use to update the
+                   scale of each parameter tensor and scalar parameters of the mode..
+                   If each parameter were decomposed
+                   as p * p_scale.exp(), where (p**2).mean().sqrt() == 1.0, scalar_lr_scale
+                   would be a the scaling factor on the learning rate of p_scale.
+              eps:  A general-purpose epsilon to prevent division by zero
+    param_min_rms: Minimum root-mean-square value of parameter tensor, for purposes of
+                   learning the scale on the parameters (we'll constrain the rms of each non-scalar
+                   parameter tensor to be >= this value)
+    param_max_rms: Maximum root-mean-square value of parameter tensor, for purposes of
+                   learning the scale on the parameters (we'll constrain the rms of each non-scalar
+                   parameter tensor to be <= this value)
+       scalar_max: Maximum absolute value for scalar parameters (applicable if your
+                   model has any parameters with numel() == 1).
+    size_update_period: The periodicity, in steps, with which we update the size (scale)
+                   of the parameter tensor.  This is provided to save a little time
+                   in the update.
+     clipping_update_period: if clipping_scale is specified, this is the period
+    """
+
+    def __init__(
+            self,
+            params,
+            lr=3e-02,
+            clipping_scale=None,
+            betas=(0.9, 0.98),
+            scalar_lr_scale=0.1,
+            eps=1.0e-08,
+            param_min_rms=1.0e-05,
+            param_max_rms=3.0,
+            scalar_max=10.0,
+            size_update_period=4,
+            clipping_update_period=100,
+            parameters_names=None,
+            show_dominant_parameters=True, ):
+
+        assert parameters_names is not None, (
+            "Please prepare parameters_names,"
+            "which is a List[List[str]]. Each List[str] is for a group"
+            "and each str is for a parameter")
+        defaults = dict(
+            lr=lr,
+            clipping_scale=clipping_scale,
+            betas=betas,
+            scalar_lr_scale=scalar_lr_scale,
+            eps=eps,
+            param_min_rms=param_min_rms,
+            param_max_rms=param_max_rms,
+            scalar_max=scalar_max,
+            size_update_period=size_update_period,
+            clipping_update_period=clipping_update_period, )
+
+        super(ScaledAdam, self).__init__(params, defaults)
+        assert len(self.param_groups) == len(parameters_names)
+        self.parameters_names = parameters_names
+        self.show_dominant_parameters = show_dominant_parameters
+
+    def __setstate__(self, state):
+        super(ScaledAdam, self).__setstate__(state)
+
+    @torch.no_grad()
+    def step(self, closure=None):
+        """Performs a single optimization step.
+
+        Arguments:
+            closure (callable, optional): A closure that reevaluates the model
+                and returns the loss.
+        """
+        loss = None
+        if closure is not None:
+            with torch.enable_grad():
+                loss = closure()
+
+        batch = True
+
+        for group, group_params_names in zip(self.param_groups,
+                                             self.parameters_names):
+
+            with self.batched_params(group["params"],
+                                     group_params_names) as batches:
+
+                # batches is list of pairs (stacked_param, state).  stacked_param is like
+                # a regular parameter, and will have a .grad, but the 1st dim corresponds to
+                # a stacking dim, it is not a real dim.
+
+                if (len(batches[0][1]) ==
+                        0):  # if len(first state) == 0: not yet initialized
+                    clipping_scale = 1
+                else:
+                    clipping_scale = self._get_clipping_scale(group, batches)
+
+                for p, state, _ in batches:
+                    # Perform optimization step.
+                    # grad is not going to be None, we handled that when creating the batches.
+                    grad = p.grad
+                    if grad.is_sparse:
+                        raise RuntimeError(
+                            "ScaledAdam optimizer does not support sparse gradients"
+                        )
+                    # State initialization
+                    if len(state) == 0:
+                        self._init_state(group, p, state)
+
+                    self._step_one_batch(group, p, state, clipping_scale)
+
+        return loss
+
+    def _init_state(self, group: dict, p: Tensor, state: dict):
+        """
+        Initializes state dict for parameter 'p'.  Assumes that dim 0 of tensor p
+        is actually the batch dimension, corresponding to batched-together
+        parameters of a given shape.
+
+
+        Args:
+           group:   Dict to look up configuration values.
+               p: The parameter that we are initializing the state for
+           state: Dict from string to whatever state we are initializing
+        """
+        size_update_period = group["size_update_period"]
+
+        state["step"] = 0
+
+        kwargs = {"device": p.device, "dtype": p.dtype}
+
+        # 'delta' implements conventional momentum.  There are
+        # several different kinds of update going on, so rather than
+        # compute "exp_avg" like in Adam, we store and decay a
+        # parameter-change "delta", which combines all forms of
+        # update.  this is equivalent to how it's done in Adam,
+        # except for the first few steps.
+        state["delta"] = torch.zeros_like(
+            p, memory_format=torch.preserve_format)
+
+        batch_size = p.shape[0]
+        numel = p.numel() // batch_size
+        numel = p.numel()
+
+        if numel > 1:
+            # "param_rms" just periodically records the scalar root-mean-square value of
+            # the parameter tensor.
+            # it has a shape like (batch_size, 1, 1, 1, 1)
+            param_rms = (
+                (p**2).mean(dim=list(range(1, p.ndim)), keepdim=True).sqrt())
+            state["param_rms"] = param_rms
+
+            state["scale_exp_avg_sq"] = torch.zeros_like(param_rms)
+            state["scale_grads"] = torch.zeros(size_update_period,
+                                               *param_rms.shape, **kwargs)
+
+        # exp_avg_sq is the weighted sum of scaled gradients. as in Adam.
+        state["exp_avg_sq"] = torch.zeros_like(
+            p, memory_format=torch.preserve_format)
+
+    def _get_clipping_scale(self,
+                            group: dict,
+                            tuples: List[Tuple[Tensor, dict, List[str]]]
+                            ) -> float:
+        """
+        Returns a scalar factor <= 1.0 that dictates gradient clipping, i.e. we will scale the gradients
+        by this amount before applying the rest of the update.
+
+        Args:
+           group: the parameter group, an item in self.param_groups
+           tuples: a list of tuples of (param, state, param_names)
+                where param is a batched set of parameters,
+                with a .grad (1st dim is batch dim)
+                and state is the state-dict where optimization parameters are kept.
+                param_names is a List[str] while each str is name for a parameter
+                in batched set of parameters "param".
+        """
+        assert len(tuples) >= 1
+        clipping_scale = group["clipping_scale"]
+        (first_p, first_state, _) = tuples[0]
+        step = first_state["step"]
+        if clipping_scale is None or step == 0:
+            # no clipping.  return early on step == 0 because the other
+            # parameters' state won't have been initialized yet.
+            return 1.0
+        clipping_update_period = group["clipping_update_period"]
+
+        tot_sumsq = torch.tensor(0.0, device=first_p.device)
+        for (p, state, param_names) in tuples:
+            grad = p.grad
+            if grad.is_sparse:
+                raise RuntimeError(
+                    "ScaledAdam optimizer does not support sparse gradients")
+            if p.numel() == p.shape[0]:  # a batch of scalars
+                tot_sumsq += (grad**2).sum()  # sum() to change shape [1] to []
+            else:
+                tot_sumsq += ((grad * state["param_rms"])**2).sum()
+
+        tot_norm = tot_sumsq.sqrt()
+        if "model_norms" not in first_state:
+            first_state["model_norms"] = torch.zeros(
+                clipping_update_period, device=p.device)
+        first_state["model_norms"][step % clipping_update_period] = tot_norm
+
+        if step % clipping_update_period == 0:
+            # Print some stats.
+            # We don't reach here if step == 0 because we would have returned
+            # above.
+            sorted_norms = first_state["model_norms"].sort()[0].to("cpu")
+            quartiles = []
+            for n in range(0, 5):
+                index = min(
+                    clipping_update_period - 1,
+                    (clipping_update_period // 4) * n, )
+                quartiles.append(sorted_norms[index].item())
+
+            median = quartiles[2]
+            threshold = clipping_scale * median
+            first_state["model_norm_threshold"] = threshold
+            percent_clipped = (first_state["num_clipped"] * 100.0 /
+                               clipping_update_period
+                               if "num_clipped" in first_state else 0.0)
+            first_state["num_clipped"] = 0
+            quartiles = " ".join(["%.3e" % x for x in quartiles])
+            logging.info(
+                f"Clipping_scale={clipping_scale}, grad-norm quartiles {quartiles}, "
+                f"threshold={threshold:.3e}, percent-clipped={percent_clipped:.1f}"
+            )
+
+        if step < clipping_update_period:
+            return 1.0  # We have not yet estimated a norm to clip to.
+        else:
+            try:
+                model_norm_threshold = first_state["model_norm_threshold"]
+            except KeyError:
+                logging.info(
+                    "Warning: model_norm_threshold not in state: possibly "
+                    "you changed config when restarting, adding clipping_scale option?"
+                )
+                return 1.0
+            ans = min(1.0, (model_norm_threshold / (tot_norm + 1.0e-20)).item())
+            if ans < 1.0:
+                first_state["num_clipped"] += 1
+            if ans < 0.1:
+                logging.warn(
+                    f"Scaling gradients by {ans}, model_norm_threshold={model_norm_threshold}"
+                )
+                if self.show_dominant_parameters:
+                    assert p.shape[0] == len(param_names)
+                    self._show_gradient_dominating_parameter(tuples, tot_sumsq)
+            return ans
+
+    def _show_gradient_dominating_parameter(
+            self, tuples: List[Tuple[Tensor, dict, List[str]]],
+            tot_sumsq: Tensor):
+        """
+        Show information of parameter wihch dominanting tot_sumsq.
+
+        Args:
+           tuples: a list of tuples of (param, state, param_names)
+                where param is a batched set of parameters,
+                with a .grad (1st dim is batch dim)
+                and state is the state-dict where optimization parameters are kept.
+                param_names is a List[str] while each str is name for a parameter
+                in batched set of parameters "param".
+            tot_sumsq: sumsq of all parameters. Though it's could be calculated
+                from tuples, we still pass it to save some time.
+        """
+        all_sumsq_orig = {}
+        for (p, state, batch_param_names) in tuples:
+            # p is a stacked batch parameters.
+            batch_grad = p.grad
+            if p.numel() == p.shape[0]:  # a batch of scalars
+                batch_sumsq_orig = batch_grad**2
+                # Dummpy values used by following `zip` statement.
+                batch_rms_orig = torch.ones(p.shape[0])
+            else:
+                batch_rms_orig = state["param_rms"]
+                batch_sumsq_orig = ((batch_grad * batch_rms_orig)**2).sum(
+                    dim=list(range(1, batch_grad.ndim)))
+
+            for name, sumsq_orig, rms, grad in zip(batch_param_names,
+                                                   batch_sumsq_orig,
+                                                   batch_rms_orig, batch_grad):
+
+                proportion_orig = sumsq_orig / tot_sumsq
+                all_sumsq_orig[name] = (proportion_orig, sumsq_orig, rms, grad)
+
+        assert torch.isclose(
+            sum([value[0] for value in all_sumsq_orig.values()]).cpu(),
+            torch.tensor(1.0), )
+        sorted_by_proportion = {
+            k: v
+            for k, v in sorted(
+                all_sumsq_orig.items(),
+                key=lambda item: item[1][0],
+                reverse=True, )
+        }
+        dominant_param_name = next(iter(sorted_by_proportion))
+        (dominant_proportion, dominant_sumsq, dominant_rms,
+         dominant_grad, ) = sorted_by_proportion[dominant_param_name]
+        logging.info(f"Parameter Dominanting tot_sumsq {dominant_param_name}"
+                     f" with proportion {dominant_proportion:.2f},"
+                     f" where dominant_sumsq=(grad_sumsq*orig_rms_sq)"
+                     f"={dominant_sumsq:.3e},"
+                     f" grad_sumsq = {(dominant_grad**2).sum():.3e},"
+                     f" orig_rms_sq={(dominant_rms**2).item():.3e}")
+
+    def _step_one_batch(self,
+                        group: dict,
+                        p: Tensor,
+                        state: dict,
+                        clipping_scale: float):
+        """
+        Do the step for one parameter, which is actually going to be a batch of
+        `real` parameters, with dim 0 as the batch dim.
+        Args:
+                  group:  dict to look up configuration values
+                    p: parameter to update (actually multiple parameters stacked together
+                       as a batch)
+                  state: state-dict for p, to look up the optimizer state
+        """
+        lr = group["lr"]
+        size_update_period = group["size_update_period"]
+        beta1 = group["betas"][0]
+
+        grad = p.grad
+        if clipping_scale != 1.0:
+            grad = grad * clipping_scale
+        step = state["step"]
+        delta = state["delta"]
+
+        delta.mul_(beta1)
+        batch_size = p.shape[0]
+        numel = p.numel() // batch_size
+        if numel > 1:
+            # Update the size/scale of p, and set param_rms
+            scale_grads = state["scale_grads"]
+            scale_grads[step % size_update_period] = (p * grad).sum(
+                dim=list(range(1, p.ndim)), keepdim=True)
+            if step % size_update_period == size_update_period - 1:
+                param_rms = state["param_rms"]  # shape: (batch_size, 1, 1, ..)
+                param_rms.copy_((p**2)
+                                .mean(dim=list(range(1, p.ndim)), keepdim=True)
+                                .sqrt())
+                if step > 0:
+                    # self._size_update() learns the overall scale on the
+                    # parameter, by shrinking or expanding it.
+                    self._size_update(group, scale_grads, p, state)
+
+        if numel == 1:
+            # For parameters with 1 element we just use regular Adam.
+            # Updates delta.
+            self._step_scalar(group, p, state)
+        else:
+            self._step(group, p, state)
+
+        state["step"] = step + 1
+
+    def _size_update(self,
+                     group: dict,
+                     scale_grads: Tensor,
+                     p: Tensor,
+                     state: dict) -> None:
+        """
+               Called only where p.numel() > 1, this updates the scale of the parameter.
+               If we imagine: p =  underlying_param * scale.exp(), and we are doing
+               gradient descent on underlying param and on scale, this function does the update
+               on `scale`.
+
+               Args:
+              group: dict to look up configuration values
+        scale_grads: a tensor of shape (size_update_period, batch_size, 1, 1,...) containing
+                      grads w.r.t. the scales.
+                  p:  The parameter to update
+               state: The state-dict of p
+        """
+
+        param_rms = state["param_rms"]
+        beta1, beta2 = group["betas"]
+        size_lr = group["lr"] * group["scalar_lr_scale"]
+        param_min_rms = group["param_min_rms"]
+        param_max_rms = group["param_max_rms"]
+        eps = group["eps"]
+        step = state["step"]
+        batch_size = p.shape[0]
+
+        size_update_period = scale_grads.shape[0]
+        # correct beta2 for the size update period: we will have
+        # faster decay at this level.
+        beta2_corr = beta2**size_update_period
+
+        scale_exp_avg_sq = state[
+            "scale_exp_avg_sq"]  # shape: (batch_size, 1, 1, ..)
+        scale_exp_avg_sq.mul_(beta2_corr).add_(
+            (scale_grads**2).mean(dim=0),  # mean over dim `size_update_period`
+            alpha=1 - beta2_corr, )  # shape is (batch_size, 1, 1, ...)
+
+        # The 1st time we reach here is when size_step == 1.
+        size_step = (step + 1) // size_update_period
+        bias_correction2 = 1 - beta2_corr**size_step
+        # we don't bother with bias_correction1; this will help prevent divergence
+        # at the start of training.
+
+        denom = scale_exp_avg_sq.sqrt() + eps
+
+        scale_step = (-size_lr * (bias_correction2**0.5) *
+                      scale_grads.sum(dim=0) / denom)
+
+        is_too_small = param_rms < param_min_rms
+        is_too_large = param_rms > param_max_rms
+
+        # when the param gets too small, just don't shrink it any further.
+        scale_step.masked_fill_(is_too_small, 0.0)
+        # when it gets too large, stop it from getting any larger.
+        scale_step.masked_fill_(is_too_large, -size_lr * size_update_period)
+        delta = state["delta"]
+        # the factor of (1-beta1) relates to momentum.
+        delta.add_(p * scale_step, alpha=(1 - beta1))
+
+    def _step(self, group: dict, p: Tensor, state: dict):
+        """
+        This function does the core update of self.step(), in the case where the members of
+        the batch have more than 1 element.
+
+        Args:
+            group: A dict which will be used to look up configuration values
+                p: The parameter to be updated
+             grad: The grad of p
+            state: The state-dict corresponding to parameter p
+
+        This function modifies p.
+        """
+        grad = p.grad
+        lr = group["lr"]
+        beta1, beta2 = group["betas"]
+        eps = group["eps"]
+        param_min_rms = group["param_min_rms"]
+        step = state["step"]
+
+        exp_avg_sq = state["exp_avg_sq"]
+        exp_avg_sq.mul_(beta2).addcmul_(grad, grad, value=(1 - beta2))
+
+        this_step = state["step"] - (state["zero_step"]
+                                     if "zero_step" in state else 0)
+        bias_correction2 = 1 - beta2**(this_step + 1)
+        if bias_correction2 < 0.99:
+            # note: not in-place.
+            exp_avg_sq = exp_avg_sq * (1.0 / bias_correction2)
+
+        denom = exp_avg_sq.sqrt()
+        denom += eps
+        grad = grad / denom
+
+        alpha = -lr * (1 - beta1) * state["param_rms"].clamp(min=param_min_rms)
+
+        delta = state["delta"]
+        delta.add_(grad * alpha)
+        p.add_(delta)
+
+    def _step_scalar(self, group: dict, p: Tensor, state: dict):
+        """
+        A simplified form of the core update for scalar tensors, where we cannot get a good
+        estimate of the parameter rms.
+        """
+        beta1, beta2 = group["betas"]
+        scalar_max = group["scalar_max"]
+        eps = group["eps"]
+        lr = group["lr"] * group["scalar_lr_scale"]
+        grad = p.grad
+
+        exp_avg_sq = state["exp_avg_sq"]  # shape: (batch_size,)
+        exp_avg_sq.mul_(beta2).addcmul_(grad, grad, value=1 - beta2)
+
+        # bias_correction2 is like in Adam.  Don't bother with bias_correction1;
+        # slower update at the start will help stability anyway.
+        bias_correction2 = 1 - beta2**(state["step"] + 1)
+        denom = (exp_avg_sq / bias_correction2).sqrt() + eps
+
+        delta = state["delta"]
+        delta.add_(grad / denom, alpha=-lr * (1 - beta1))
+        p.clamp_(min=-scalar_max, max=scalar_max)
+        p.add_(delta)
diff --git a/AR/modules/patched_mha_with_cache.py b/AR/modules/patched_mha_with_cache.py
new file mode 100644
index 0000000000000000000000000000000000000000..bfb748e25d7933ad4ce18714486a02cde3358d30
--- /dev/null
+++ b/AR/modules/patched_mha_with_cache.py
@@ -0,0 +1,388 @@
+from torch.nn.functional import *
+from torch.nn.functional import _mha_shape_check,_canonical_mask,_none_or_dtype,_in_projection_packed
+# import torch
+# Tensor = torch.Tensor
+# from typing import Callable, List, Optional, Tuple, Union
+
+def multi_head_attention_forward_patched(
+    query: Tensor,
+    key: Tensor,
+    value: Tensor,
+    embed_dim_to_check: int,
+    num_heads: int,
+    in_proj_weight: Optional[Tensor],
+    in_proj_bias: Optional[Tensor],
+    bias_k: Optional[Tensor],
+    bias_v: Optional[Tensor],
+    add_zero_attn: bool,
+    dropout_p: float,
+    out_proj_weight: Tensor,
+    out_proj_bias: Optional[Tensor],
+    training: bool = True,
+    key_padding_mask: Optional[Tensor] = None,
+    need_weights: bool = True,
+    attn_mask: Optional[Tensor] = None,
+    use_separate_proj_weight: bool = False,
+    q_proj_weight: Optional[Tensor] = None,
+    k_proj_weight: Optional[Tensor] = None,
+    v_proj_weight: Optional[Tensor] = None,
+    static_k: Optional[Tensor] = None,
+    static_v: Optional[Tensor] = None,
+    average_attn_weights: bool = True,
+    is_causal: bool = False,cache=None
+) -> Tuple[Tensor, Optional[Tensor]]:
+    r"""
+    Args:
+        query, key, value: map a query and a set of key-value pairs to an output.
+            See "Attention Is All You Need" for more details.
+        embed_dim_to_check: total dimension of the model.
+        num_heads: parallel attention heads.
+        in_proj_weight, in_proj_bias: input projection weight and bias.
+        bias_k, bias_v: bias of the key and value sequences to be added at dim=0.
+        add_zero_attn: add a new batch of zeros to the key and
+                       value sequences at dim=1.
+        dropout_p: probability of an element to be zeroed.
+        out_proj_weight, out_proj_bias: the output projection weight and bias.
+        training: apply dropout if is ``True``.
+        key_padding_mask: if provided, specified padding elements in the key will
+            be ignored by the attention. This is an binary mask. When the value is True,
+            the corresponding value on the attention layer will be filled with -inf.
+        need_weights: output attn_output_weights.
+            Default: `True`
+            Note: `needs_weight` defaults to `True`, but should be set to `False`
+            For best performance when attention weights are not nedeeded.
+            *Setting needs_weights to `True`
+            leads to a significant performance degradation.*
+        attn_mask: 2D or 3D mask that prevents attention to certain positions. A 2D mask will be broadcasted for all
+            the batches while a 3D mask allows to specify a different mask for the entries of each batch.
+        is_causal: If specified, applies a causal mask as attention mask, and ignores
+            attn_mask for computing scaled dot product attention.
+            Default: ``False``.
+            .. warning::
+                is_causal is provides a hint that the attn_mask is the
+                causal mask.Providing incorrect hints can result in
+                incorrect execution, including forward and backward
+                compatibility.
+        use_separate_proj_weight: the function accept the proj. weights for query, key,
+            and value in different forms. If false, in_proj_weight will be used, which is
+            a combination of q_proj_weight, k_proj_weight, v_proj_weight.
+        q_proj_weight, k_proj_weight, v_proj_weight, in_proj_bias: input projection weight and bias.
+        static_k, static_v: static key and value used for attention operators.
+        average_attn_weights: If true, indicates that the returned ``attn_weights`` should be averaged across heads.
+            Otherwise, ``attn_weights`` are provided separately per head. Note that this flag only has an effect
+            when ``need_weights=True.``. Default: True
+
+
+    Shape:
+        Inputs:
+        - query: :math:`(L, E)` or :math:`(L, N, E)` where L is the target sequence length, N is the batch size, E is
+          the embedding dimension.
+        - key: :math:`(S, E)` or :math:`(S, N, E)`, where S is the source sequence length, N is the batch size, E is
+          the embedding dimension.
+        - value: :math:`(S, E)` or :math:`(S, N, E)` where S is the source sequence length, N is the batch size, E is
+          the embedding dimension.
+        - key_padding_mask: :math:`(S)` or :math:`(N, S)` where N is the batch size, S is the source sequence length.
+          If a FloatTensor is provided, it will be directly added to the value.
+          If a BoolTensor is provided, the positions with the
+          value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged.
+        - attn_mask: 2D mask :math:`(L, S)` where L is the target sequence length, S is the source sequence length.
+          3D mask :math:`(N*num_heads, L, S)` where N is the batch size, L is the target sequence length,
+          S is the source sequence length. attn_mask ensures that position i is allowed to attend the unmasked
+          positions. If a BoolTensor is provided, positions with ``True``
+          are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor
+          is provided, it will be added to the attention weight.
+        - static_k: :math:`(N*num_heads, S, E/num_heads)`, where S is the source sequence length,
+          N is the batch size, E is the embedding dimension. E/num_heads is the head dimension.
+        - static_v: :math:`(N*num_heads, S, E/num_heads)`, where S is the source sequence length,
+          N is the batch size, E is the embedding dimension. E/num_heads is the head dimension.
+
+        Outputs:
+        - attn_output: :math:`(L, E)` or :math:`(L, N, E)` where L is the target sequence length, N is the batch size,
+          E is the embedding dimension.
+        - attn_output_weights: Only returned when ``need_weights=True``. If ``average_attn_weights=True``, returns
+          attention weights averaged across heads of shape :math:`(L, S)` when input is unbatched or
+          :math:`(N, L, S)`, where :math:`N` is the batch size, :math:`L` is the target sequence length, and
+          :math:`S` is the source sequence length. If ``average_attn_weights=False``, returns attention weights per
+          head of shape :math:`(num_heads, L, S)` when input is unbatched or :math:`(N, num_heads, L, S)`.
+    """
+    tens_ops = (query, key, value, in_proj_weight, in_proj_bias, bias_k, bias_v, out_proj_weight, out_proj_bias)
+    if has_torch_function(tens_ops):
+        return handle_torch_function(
+            multi_head_attention_forward,
+            tens_ops,
+            query,
+            key,
+            value,
+            embed_dim_to_check,
+            num_heads,
+            in_proj_weight,
+            in_proj_bias,
+            bias_k,
+            bias_v,
+            add_zero_attn,
+            dropout_p,
+            out_proj_weight,
+            out_proj_bias,
+            training=training,
+            key_padding_mask=key_padding_mask,
+            need_weights=need_weights,
+            attn_mask=attn_mask,
+            is_causal=is_causal,
+            use_separate_proj_weight=use_separate_proj_weight,
+            q_proj_weight=q_proj_weight,
+            k_proj_weight=k_proj_weight,
+            v_proj_weight=v_proj_weight,
+            static_k=static_k,
+            static_v=static_v,
+            average_attn_weights=average_attn_weights,cache=cache
+        )
+
+    is_batched = _mha_shape_check(query, key, value, key_padding_mask, attn_mask, num_heads)
+
+    # For unbatched input, we unsqueeze at the expected batch-dim to pretend that the input
+    # is batched, run the computation and before returning squeeze the
+    # batch dimension so that the output doesn't carry this temporary batch dimension.
+    if not is_batched:
+        # unsqueeze if the input is unbatched
+        query = query.unsqueeze(1)
+        key = key.unsqueeze(1)
+        value = value.unsqueeze(1)
+        if key_padding_mask is not None:
+            key_padding_mask = key_padding_mask.unsqueeze(0)
+
+    # set up shape vars
+    tgt_len, bsz, embed_dim = query.shape
+    src_len, _, _ = key.shape
+
+    key_padding_mask = _canonical_mask(
+        mask=key_padding_mask,
+        mask_name="key_padding_mask",
+        other_type=_none_or_dtype(attn_mask),
+        other_name="attn_mask",
+        target_type=query.dtype
+    )
+
+    if is_causal and attn_mask is None:
+        raise RuntimeError(
+            "Need attn_mask if specifying the is_causal hint. "
+            "You may use the Transformer module method "
+            "`generate_square_subsequent_mask` to create this mask."
+        )
+
+    if is_causal and key_padding_mask is None and not need_weights:
+        # when we have a kpm or need weights, we need attn_mask
+        # Otherwise, we use the is_causal hint go as is_causal
+        # indicator to SDPA.
+        attn_mask = None
+    else:
+        attn_mask = _canonical_mask(
+            mask=attn_mask,
+            mask_name="attn_mask",
+            other_type=None,
+            other_name="",
+            target_type=query.dtype,
+            check_other=False,
+        )
+
+
+        if key_padding_mask is not None:
+            # We have the attn_mask, and use that to merge kpm into it.
+            # Turn off use of is_causal hint, as the merged mask is no
+            # longer causal.
+            is_causal = False
+
+    assert embed_dim == embed_dim_to_check, \
+        f"was expecting embedding dimension of {embed_dim_to_check}, but got {embed_dim}"
+    if isinstance(embed_dim, torch.Tensor):
+        # embed_dim can be a tensor when JIT tracing
+        head_dim = embed_dim.div(num_heads, rounding_mode='trunc')
+    else:
+        head_dim = embed_dim // num_heads
+    assert head_dim * num_heads == embed_dim, f"embed_dim {embed_dim} not divisible by num_heads {num_heads}"
+    if use_separate_proj_weight:
+        # allow MHA to have different embedding dimensions when separate projection weights are used
+        assert key.shape[:2] == value.shape[:2], \
+            f"key's sequence and batch dims {key.shape[:2]} do not match value's {value.shape[:2]}"
+    else:
+        assert key.shape == value.shape, f"key shape {key.shape} does not match value shape {value.shape}"
+
+    #
+    # compute in-projection
+    #
+    if not use_separate_proj_weight:
+        assert in_proj_weight is not None, "use_separate_proj_weight is False but in_proj_weight is None"
+        q, k, v = _in_projection_packed(query, key, value, in_proj_weight, in_proj_bias)
+    else:
+        assert q_proj_weight is not None, "use_separate_proj_weight is True but q_proj_weight is None"
+        assert k_proj_weight is not None, "use_separate_proj_weight is True but k_proj_weight is None"
+        assert v_proj_weight is not None, "use_separate_proj_weight is True but v_proj_weight is None"
+        if in_proj_bias is None:
+            b_q = b_k = b_v = None
+        else:
+            b_q, b_k, b_v = in_proj_bias.chunk(3)
+        q, k, v = _in_projection(query, key, value, q_proj_weight, k_proj_weight, v_proj_weight, b_q, b_k, b_v)
+    if(cache!=None):
+        if(cache["first_infer"]==1):
+            cache["k"][cache["stage"]]=k
+            # print(0,cache["k"].shape)
+            cache["v"][cache["stage"]]=v
+        else:###12个layer每个都要留自己的cache_kv
+            # print(1,cache["k"].shape)
+            cache["k"][cache["stage"]]=torch.cat([cache["k"][cache["stage"]],k],0)##本来时序是1，但是proj的时候可能transpose了所以时序到0维了
+            cache["v"][cache["stage"]]=torch.cat([cache["v"][cache["stage"]],v],0)
+            # print(2, cache["k"].shape)
+            src_len = cache["k"][cache["stage"]].shape[0]
+            k=cache["k"][cache["stage"]]
+            v=cache["v"][cache["stage"]]
+            # if attn_mask is not None:
+            #     attn_mask=attn_mask[-1:,]
+                # print(attn_mask.shape,attn_mask)
+        cache["stage"] = (cache["stage"] + 1) % cache["all_stage"]
+    # print(2333,cache)
+    # prep attention mask
+
+    attn_mask = _canonical_mask(
+        mask=attn_mask,
+        mask_name="attn_mask",
+        other_type=None,
+        other_name="",
+        target_type=q.dtype,
+        check_other=False,
+    )
+
+    if attn_mask is not None:
+        # ensure attn_mask's dim is 3
+        if attn_mask.dim() == 2:
+            correct_2d_size = (tgt_len, src_len)
+            if attn_mask.shape != correct_2d_size:
+                raise RuntimeError(f"The shape of the 2D attn_mask is {attn_mask.shape}, but should be {correct_2d_size}.")
+            attn_mask = attn_mask.unsqueeze(0)
+        elif attn_mask.dim() == 3:
+            correct_3d_size = (bsz * num_heads, tgt_len, src_len)
+            if attn_mask.shape != correct_3d_size:
+                raise RuntimeError(f"The shape of the 3D attn_mask is {attn_mask.shape}, but should be {correct_3d_size}.")
+        else:
+            raise RuntimeError(f"attn_mask's dimension {attn_mask.dim()} is not supported")
+
+    # add bias along batch dimension (currently second)
+    if bias_k is not None and bias_v is not None:
+        assert static_k is None, "bias cannot be added to static key."
+        assert static_v is None, "bias cannot be added to static value."
+        k = torch.cat([k, bias_k.repeat(1, bsz, 1)])
+        v = torch.cat([v, bias_v.repeat(1, bsz, 1)])
+        if attn_mask is not None:
+            attn_mask = pad(attn_mask, (0, 1))
+        if key_padding_mask is not None:
+            key_padding_mask = pad(key_padding_mask, (0, 1))
+    else:
+        assert bias_k is None
+        assert bias_v is None
+
+    #
+    # reshape q, k, v for multihead attention and make em batch first
+    #
+    q = q.view(tgt_len, bsz * num_heads, head_dim).transpose(0, 1)
+    if static_k is None:
+        k = k.view(k.shape[0], bsz * num_heads, head_dim).transpose(0, 1)
+    else:
+        # TODO finish disentangling control flow so we don't do in-projections when statics are passed
+        assert static_k.size(0) == bsz * num_heads, \
+            f"expecting static_k.size(0) of {bsz * num_heads}, but got {static_k.size(0)}"
+        assert static_k.size(2) == head_dim, \
+            f"expecting static_k.size(2) of {head_dim}, but got {static_k.size(2)}"
+        k = static_k
+    if static_v is None:
+        v = v.view(v.shape[0], bsz * num_heads, head_dim).transpose(0, 1)
+    else:
+        # TODO finish disentangling control flow so we don't do in-projections when statics are passed
+        assert static_v.size(0) == bsz * num_heads, \
+            f"expecting static_v.size(0) of {bsz * num_heads}, but got {static_v.size(0)}"
+        assert static_v.size(2) == head_dim, \
+            f"expecting static_v.size(2) of {head_dim}, but got {static_v.size(2)}"
+        v = static_v
+
+    # add zero attention along batch dimension (now first)
+    if add_zero_attn:
+        zero_attn_shape = (bsz * num_heads, 1, head_dim)
+        k = torch.cat([k, torch.zeros(zero_attn_shape, dtype=k.dtype, device=k.device)], dim=1)
+        v = torch.cat([v, torch.zeros(zero_attn_shape, dtype=v.dtype, device=v.device)], dim=1)
+        if attn_mask is not None:
+            attn_mask = pad(attn_mask, (0, 1))
+        if key_padding_mask is not None:
+            key_padding_mask = pad(key_padding_mask, (0, 1))
+
+    # update source sequence length after adjustments
+    src_len = k.size(1)
+
+    # merge key padding and attention masks
+    if key_padding_mask is not None:
+        assert key_padding_mask.shape == (bsz, src_len), \
+            f"expecting key_padding_mask shape of {(bsz, src_len)}, but got {key_padding_mask.shape}"
+        key_padding_mask = key_padding_mask.view(bsz, 1, 1, src_len).   \
+            expand(-1, num_heads, -1, -1).reshape(bsz * num_heads, 1, src_len)
+        if attn_mask is None:
+            attn_mask = key_padding_mask
+        else:
+            attn_mask = attn_mask + key_padding_mask
+
+    # adjust dropout probability
+    if not training:
+        dropout_p = 0.0
+
+    #
+    # (deep breath) calculate attention and out projection
+    #
+
+    if need_weights:
+        B, Nt, E = q.shape
+        q_scaled = q / math.sqrt(E)
+
+        assert not (is_causal and attn_mask is None), "FIXME: is_causal not implemented for need_weights"
+
+        if attn_mask is not None:
+            attn_output_weights = torch.baddbmm(attn_mask, q_scaled, k.transpose(-2, -1))
+        else:
+            attn_output_weights = torch.bmm(q_scaled, k.transpose(-2, -1))
+        attn_output_weights = softmax(attn_output_weights, dim=-1)
+        if dropout_p > 0.0:
+            attn_output_weights = dropout(attn_output_weights, p=dropout_p)
+
+        attn_output = torch.bmm(attn_output_weights, v)
+
+        attn_output = attn_output.transpose(0, 1).contiguous().view(tgt_len * bsz, embed_dim)
+        attn_output = linear(attn_output, out_proj_weight, out_proj_bias)
+        attn_output = attn_output.view(tgt_len, bsz, attn_output.size(1))
+
+        # optionally average attention weights over heads
+        attn_output_weights = attn_output_weights.view(bsz, num_heads, tgt_len, src_len)
+        if average_attn_weights:
+            attn_output_weights = attn_output_weights.mean(dim=1)
+
+        if not is_batched:
+            # squeeze the output if input was unbatched
+            attn_output = attn_output.squeeze(1)
+            attn_output_weights = attn_output_weights.squeeze(0)
+        return attn_output, attn_output_weights
+    else:
+        # attn_mask can be either (L,S) or (N*num_heads, L, S)
+        # if attn_mask's shape is (1, L, S) we need to unsqueeze to (1, 1, L, S)
+        # in order to match the input for SDPA of (N, num_heads, L, S)
+        if attn_mask is not None:
+            if attn_mask.size(0) == 1 and attn_mask.dim() == 3:
+                attn_mask = attn_mask.unsqueeze(0)
+            else:
+                attn_mask = attn_mask.view(bsz, num_heads, -1, src_len)
+
+        q = q.view(bsz, num_heads, tgt_len, head_dim)
+        k = k.view(bsz, num_heads, src_len, head_dim)
+        v = v.view(bsz, num_heads, src_len, head_dim)
+
+        attn_output = scaled_dot_product_attention(q, k, v, attn_mask, dropout_p, is_causal)
+        attn_output = attn_output.permute(2, 0, 1, 3).contiguous().view(bsz * tgt_len, embed_dim)
+
+        attn_output = linear(attn_output, out_proj_weight, out_proj_bias)
+        attn_output = attn_output.view(tgt_len, bsz, attn_output.size(1))
+        if not is_batched:
+            # squeeze the output if input was unbatched
+            attn_output = attn_output.squeeze(1)
+        return attn_output, None
diff --git a/AR/modules/scaling.py b/AR/modules/scaling.py
new file mode 100644
index 0000000000000000000000000000000000000000..ec31d616b18dec97962fb55dbc5c264cc1c3c39a
--- /dev/null
+++ b/AR/modules/scaling.py
@@ -0,0 +1,319 @@
+# Copyright    2022  Xiaomi Corp.        (authors: Daniel Povey)
+#
+# See ../../../../LICENSE for clarification regarding multiple authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import logging
+import math
+import random
+from typing import Optional
+from typing import Tuple
+from typing import Union
+
+import torch
+import torch.nn as nn
+from torch import Tensor
+
+
+class DoubleSwishFunction(torch.autograd.Function):
+    """
+      double_swish(x) = x * torch.sigmoid(x-1)
+    This is a definition, originally motivated by its close numerical
+    similarity to swish(swish(x)), where swish(x) =  x * sigmoid(x).
+
+    Memory-efficient derivative computation:
+     double_swish(x) = x * s, where s(x) = torch.sigmoid(x-1)
+     double_swish'(x) = d/dx double_swish(x) =  x * s'(x) + x' * s(x) = x * s'(x) + s(x).
+     Now, s'(x) = s(x) * (1-s(x)).
+     double_swish'(x) =  x * s'(x) + s(x).
+                      =  x * s(x) * (1-s(x)) + s(x).
+                     = double_swish(x) * (1-s(x)) + s(x)
+     ... so we just need to remember s(x) but not x itself.
+    """
+
+    @staticmethod
+    def forward(ctx, x: Tensor) -> Tensor:
+        requires_grad = x.requires_grad
+        x_dtype = x.dtype
+        if x.dtype == torch.float16:
+            x = x.to(torch.float32)
+
+        s = torch.sigmoid(x - 1.0)
+        y = x * s
+
+        if requires_grad:
+            deriv = y * (1 - s) + s
+            # notes on derivative of x * sigmoid(x - 1):
+            # https://www.wolframalpha.com/input?i=d%2Fdx+%28x+*+sigmoid%28x-1%29%29
+            # min \simeq -0.043638.  Take floor as -0.043637 so it's a lower bund
+            # max \simeq 1.1990.   Take ceil to be 1.2 so it's an upper bound.
+            # the combination of "+ torch.rand_like(deriv)" and casting to torch.uint8 (which
+            # floors), should be expectation-preserving.
+            floor = -0.043637
+            ceil = 1.2
+            d_scaled = (deriv - floor) * (255.0 / (ceil - floor)
+                                          ) + torch.rand_like(deriv)
+            if __name__ == "__main__":
+                # for self-testing only.
+                assert d_scaled.min() >= 0.0
+                assert d_scaled.max() < 256.0
+            d_int = d_scaled.to(torch.uint8)
+            ctx.save_for_backward(d_int)
+        if x.dtype == torch.float16 or torch.is_autocast_enabled():
+            y = y.to(torch.float16)
+        return y
+
+    @staticmethod
+    def backward(ctx, y_grad: Tensor) -> Tensor:
+        (d, ) = ctx.saved_tensors
+        # the same constants as used in forward pass.
+        floor = -0.043637
+        ceil = 1.2
+        d = d * ((ceil - floor) / 255.0) + floor
+        return y_grad * d
+
+
+class DoubleSwish(torch.nn.Module):
+    def forward(self, x: Tensor) -> Tensor:
+        """Return double-swish activation function which is an approximation to Swish(Swish(x)),
+        that we approximate closely with x * sigmoid(x-1).
+        """
+        if torch.jit.is_scripting() or torch.jit.is_tracing():
+            return x * torch.sigmoid(x - 1.0)
+        return DoubleSwishFunction.apply(x)
+
+
+class ActivationBalancerFunction(torch.autograd.Function):
+    @staticmethod
+    def forward(
+            ctx,
+            x: Tensor,
+            scale_factor: Tensor,
+            sign_factor: Optional[Tensor],
+            channel_dim: int, ) -> Tensor:
+        if channel_dim < 0:
+            channel_dim += x.ndim
+        ctx.channel_dim = channel_dim
+        xgt0 = x > 0
+        if sign_factor is None:
+            ctx.save_for_backward(xgt0, scale_factor)
+        else:
+            ctx.save_for_backward(xgt0, scale_factor, sign_factor)
+        return x
+
+    @staticmethod
+    def backward(ctx, x_grad: Tensor) -> Tuple[Tensor, None, None, None]:
+        if len(ctx.saved_tensors) == 3:
+            xgt0, scale_factor, sign_factor = ctx.saved_tensors
+            for _ in range(ctx.channel_dim, x_grad.ndim - 1):
+                scale_factor = scale_factor.unsqueeze(-1)
+                sign_factor = sign_factor.unsqueeze(-1)
+            factor = sign_factor + scale_factor * (xgt0.to(x_grad.dtype) - 0.5)
+        else:
+            xgt0, scale_factor = ctx.saved_tensors
+            for _ in range(ctx.channel_dim, x_grad.ndim - 1):
+                scale_factor = scale_factor.unsqueeze(-1)
+            factor = scale_factor * (xgt0.to(x_grad.dtype) - 0.5)
+        neg_delta_grad = x_grad.abs() * factor
+        return (x_grad - neg_delta_grad, None, None, None, )
+
+
+def _compute_scale_factor(
+        x: Tensor,
+        channel_dim: int,
+        min_abs: float,
+        max_abs: float,
+        gain_factor: float,
+        max_factor: float, ) -> Tensor:
+    if channel_dim < 0:
+        channel_dim += x.ndim
+    sum_dims = [d for d in range(x.ndim) if d != channel_dim]
+    x_abs_mean = torch.mean(x.abs(), dim=sum_dims).to(torch.float32)
+
+    if min_abs == 0.0:
+        below_threshold = 0.0
+    else:
+        # below_threshold is 0 if x_abs_mean > min_abs, can be at most max_factor if
+        # x_abs)_mean , min_abs.
+        below_threshold = (
+            (min_abs - x_abs_mean) * (gain_factor / min_abs)).clamp(
+                min=0, max=max_factor)
+
+    above_threshold = ((x_abs_mean - max_abs) * (gain_factor / max_abs)).clamp(
+        min=0, max=max_factor)
+
+    return below_threshold - above_threshold
+
+
+def _compute_sign_factor(
+        x: Tensor,
+        channel_dim: int,
+        min_positive: float,
+        max_positive: float,
+        gain_factor: float,
+        max_factor: float, ) -> Tensor:
+    if channel_dim < 0:
+        channel_dim += x.ndim
+    sum_dims = [d for d in range(x.ndim) if d != channel_dim]
+    proportion_positive = torch.mean((x > 0).to(torch.float32), dim=sum_dims)
+    if min_positive == 0.0:
+        factor1 = 0.0
+    else:
+        # 0 if proportion_positive >= min_positive, else can be
+        # as large as max_factor.
+        factor1 = ((min_positive - proportion_positive) *
+                   (gain_factor / min_positive)).clamp_(
+                       min=0, max=max_factor)
+
+    if max_positive == 1.0:
+        factor2 = 0.0
+    else:
+        # 0 if self.proportion_positive <= max_positive, else can be
+        # as large as -max_factor.
+        factor2 = ((proportion_positive - max_positive) *
+                   (gain_factor / (1.0 - max_positive))).clamp_(
+                       min=0, max=max_factor)
+    sign_factor = factor1 - factor2
+    # require min_positive != 0 or max_positive != 1:
+    assert not isinstance(sign_factor, float)
+    return sign_factor
+
+
+class ActivationBalancer(torch.nn.Module):
+    """
+    Modifies the backpropped derivatives of a function to try to encourage, for
+    each channel, that it is positive at least a proportion `threshold` of the
+    time.  It does this by multiplying negative derivative values by up to
+    (1+max_factor), and positive derivative values by up to (1-max_factor),
+    interpolated from 1 at the threshold to those extremal values when none
+    of the inputs are positive.
+
+    Args:
+           num_channels: the number of channels
+           channel_dim: the dimension/axis corresponding to the channel, e.g.
+               -1, 0, 1, 2; will be interpreted as an offset from x.ndim if negative.
+           min_positive: the minimum, per channel, of the proportion of the time
+               that (x > 0), below which we start to modify the derivatives.
+           max_positive: the maximum, per channel, of the proportion of the time
+               that (x > 0), above which we start to modify the derivatives.
+           max_factor: the maximum factor by which we modify the derivatives for
+              either the sign constraint or the magnitude constraint;
+              e.g. with max_factor=0.02, the the derivatives would be multiplied by
+              values in the range [0.98..1.02].
+           sign_gain_factor: determines the 'gain' with which we increase the
+              change in gradient once the constraints on min_positive and max_positive
+              are violated.
+           scale_gain_factor: determines the 'gain' with which we increase the
+              change in gradient once the constraints on min_abs and max_abs
+              are violated.
+           min_abs:  the minimum average-absolute-value difference from the mean
+               value per channel, which we allow, before we start to modify
+               the derivatives to prevent this.
+           max_abs:  the maximum average-absolute-value difference from the mean
+               value per channel, which we allow, before we start to modify
+               the derivatives to prevent this.
+          min_prob: determines the minimum probability with which we modify the
+             gradients for the {min,max}_positive and {min,max}_abs constraints,
+             on each forward().  This is done randomly to prevent all layers
+             from doing it at the same time.  Early in training we may use
+             higher probabilities than this; it will decay to this value.
+    """
+
+    def __init__(
+            self,
+            num_channels: int,
+            channel_dim: int,
+            min_positive: float=0.05,
+            max_positive: float=0.95,
+            max_factor: float=0.04,
+            sign_gain_factor: float=0.01,
+            scale_gain_factor: float=0.02,
+            min_abs: float=0.2,
+            max_abs: float=100.0,
+            min_prob: float=0.1, ):
+        super(ActivationBalancer, self).__init__()
+        self.num_channels = num_channels
+        self.channel_dim = channel_dim
+        self.min_positive = min_positive
+        self.max_positive = max_positive
+        self.max_factor = max_factor
+        self.min_abs = min_abs
+        self.max_abs = max_abs
+        self.min_prob = min_prob
+        self.sign_gain_factor = sign_gain_factor
+        self.scale_gain_factor = scale_gain_factor
+
+        # count measures how many times the forward() function has been called.
+        # We occasionally sync this to a tensor called `count`, that exists to
+        # make sure it is synced to disk when we load and save the model.
+        self.cpu_count = 0
+        self.register_buffer("count", torch.tensor(0, dtype=torch.int64))
+
+    def forward(self, x: Tensor) -> Tensor:
+        if (torch.jit.is_scripting() or not x.requires_grad or
+                torch.jit.is_tracing()):
+            return _no_op(x)
+
+        count = self.cpu_count
+        self.cpu_count += 1
+
+        if random.random() < 0.01:
+            # Occasionally sync self.cpu_count with self.count.
+            # count affects the decay of 'prob'.  don't do this on every iter,
+            # because syncing with the GPU is slow.
+            self.cpu_count = max(self.cpu_count, self.count.item())
+            self.count.fill_(self.cpu_count)
+
+        # the prob of doing some work exponentially decreases from 0.5 till it hits
+        # a floor at min_prob (==0.1, by default)
+        prob = max(self.min_prob, 0.5**(1 + (count / 4000.0)))
+
+        if random.random() < prob:
+            sign_gain_factor = 0.5
+            if self.min_positive != 0.0 or self.max_positive != 1.0:
+                sign_factor = _compute_sign_factor(
+                    x,
+                    self.channel_dim,
+                    self.min_positive,
+                    self.max_positive,
+                    gain_factor=self.sign_gain_factor / prob,
+                    max_factor=self.max_factor, )
+            else:
+                sign_factor = None
+
+            scale_factor = _compute_scale_factor(
+                x.detach(),
+                self.channel_dim,
+                min_abs=self.min_abs,
+                max_abs=self.max_abs,
+                gain_factor=self.scale_gain_factor / prob,
+                max_factor=self.max_factor, )
+            return ActivationBalancerFunction.apply(
+                x,
+                scale_factor,
+                sign_factor,
+                self.channel_dim, )
+        else:
+            return _no_op(x)
+
+
+def BalancedDoubleSwish(d_model, channel_dim=-1, max_abs=10.0,
+                        min_prob=0.25) -> nn.Sequential:
+    """
+    ActivationBalancer -> DoubleSwish
+    """
+    balancer = ActivationBalancer(
+        d_model, channel_dim=channel_dim, max_abs=max_abs, min_prob=min_prob)
+    return nn.Sequential(
+        balancer,
+        DoubleSwish(), )
diff --git a/AR/modules/transformer.py b/AR/modules/transformer.py
new file mode 100644
index 0000000000000000000000000000000000000000..04f0b1bea152c8f6cd5c6fc0ea60058691e0947e
--- /dev/null
+++ b/AR/modules/transformer.py
@@ -0,0 +1,347 @@
+# modified from https://github.com/lifeiteng/vall-e/blob/main/valle/modules/transformer.py
+import copy
+import numbers
+from functools import partial
+from typing import Any
+from typing import Callable
+from typing import List
+from typing import Optional
+from typing import Tuple
+from typing import Union
+
+import torch
+from AR.modules.activation import MultiheadAttention
+from AR.modules.scaling import BalancedDoubleSwish
+from torch import nn
+from torch import Tensor
+from torch.nn import functional as F
+
+_shape_t = Union[int, List[int], torch.Size]
+
+
+class LayerNorm(nn.Module):
+    __constants__ = ["normalized_shape", "eps", "elementwise_affine"]
+    normalized_shape: Tuple[int, ...]
+    eps: float
+    elementwise_affine: bool
+
+    def __init__(
+            self,
+            normalized_shape: _shape_t,
+            eps: float=1e-5,
+            elementwise_affine: bool=True,
+            device=None,
+            dtype=None, ) -> None:
+        factory_kwargs = {"device": device, "dtype": dtype}
+        super(LayerNorm, self).__init__()
+        if isinstance(normalized_shape, numbers.Integral):
+            # mypy error: incompatible types in assignment
+            normalized_shape = (normalized_shape, )  # type: ignore[assignment]
+        self.normalized_shape = tuple(
+            normalized_shape)  # type: ignore[arg-type]
+        self.eps = eps
+        self.elementwise_affine = elementwise_affine
+        if self.elementwise_affine:
+            self.weight = nn.Parameter(
+                torch.empty(self.normalized_shape, **factory_kwargs))
+            self.bias = nn.Parameter(
+                torch.empty(self.normalized_shape, **factory_kwargs))
+        else:
+            self.register_parameter("weight", None)
+            self.register_parameter("bias", None)
+
+        self.reset_parameters()
+
+    def reset_parameters(self) -> None:
+        if self.elementwise_affine:
+            nn.init.ones_(self.weight)
+            nn.init.zeros_(self.bias)
+
+    def forward(self, input: Tensor, embedding: Any=None) -> Tensor:
+        if isinstance(input, tuple):
+            input, embedding = input
+            return (F.layer_norm(
+                input,
+                self.normalized_shape,
+                self.weight,
+                self.bias,
+                self.eps, ), embedding, )
+
+        assert embedding is None
+        return F.layer_norm(input, self.normalized_shape, self.weight,
+                            self.bias, self.eps)
+
+    def extra_repr(self) -> str:
+        return (
+            "{normalized_shape}, eps={eps}, "
+            "elementwise_affine={elementwise_affine}".format(**self.__dict__))
+
+
+class IdentityNorm(nn.Module):
+    def __init__(
+            self,
+            d_model: int,
+            eps: float=1e-5,
+            device=None,
+            dtype=None, ) -> None:
+        super(IdentityNorm, self).__init__()
+
+    def forward(self, input: Tensor, embedding: Any=None) -> Tensor:
+        if isinstance(input, tuple):
+            return input
+
+        assert embedding is None
+        return input
+
+
+class TransformerEncoder(nn.Module):
+    r"""TransformerEncoder is a stack of N encoder layers. Users can build the
+    BERT(https://arxiv.org/abs/1810.04805) model with corresponding parameters.
+
+    Args:
+        encoder_layer: an instance of the TransformerEncoderLayer() class (required).
+        num_layers: the number of sub-encoder-layers in the encoder (required).
+        norm: the layer normalization component (optional).
+        enable_nested_tensor: if True, input will automatically convert to nested tensor
+            (and convert back on output). This will improve the overall performance of
+            TransformerEncoder when padding rate is high. Default: ``True`` (enabled).
+
+    Examples::
+        >>> encoder_layer = TransformerEncoderLayer(d_model=512, nhead=8)
+        >>> transformer_encoder = TransformerEncoder(encoder_layer, num_layers=6)
+        >>> src = torch.rand(10, 32, 512)
+        >>> out = transformer_encoder(src)
+    """
+    __constants__ = ["norm"]
+
+    def __init__(self, encoder_layer, num_layers, norm=None):
+        super(TransformerEncoder, self).__init__()
+        self.layers = _get_clones(encoder_layer, num_layers)
+        self.num_layers = num_layers
+        self.norm = norm
+
+    def forward(
+            self,
+            src: Tensor,
+            mask: Optional[Tensor]=None,
+            src_key_padding_mask: Optional[Tensor]=None,
+            return_layer_states: bool=False,cache=None ) -> Tensor:
+        r"""Pass the input through the encoder layers in turn.
+
+        Args:
+            src: the sequence to the encoder (required).
+            mask: the mask for the src sequence (optional).
+            src_key_padding_mask: the mask for the src keys per batch (optional).
+            return_layer_states: return layers' state (optional).
+
+        Shape:
+            see the docs in Transformer class.
+        """
+        if return_layer_states:
+            layer_states = []  # layers' output
+            output = src
+            for mod in self.layers:
+                output = mod(
+                    output,
+                    src_mask=mask,
+                    src_key_padding_mask=src_key_padding_mask, cache=cache)
+                layer_states.append(output[0])
+
+            if self.norm is not None:
+                output = self.norm(output)
+
+            return layer_states, output
+
+        output = src
+        for mod in self.layers:
+            output = mod(output,
+                         src_mask=mask,
+                         src_key_padding_mask=src_key_padding_mask, cache=cache)
+
+        if self.norm is not None:
+            output = self.norm(output)
+
+        return output
+
+
+class TransformerEncoderLayer(nn.Module):
+    __constants__ = ["batch_first", "norm_first"]
+
+    def __init__(
+            self,
+            d_model: int,
+            nhead: int,
+            dim_feedforward: int=2048,
+            dropout: float=0.1,
+            activation: Union[str, Callable[[Tensor], Tensor]]=F.relu,
+            batch_first: bool=False,
+            norm_first: bool=False,
+            device=None,
+            dtype=None,
+            linear1_self_attention_cls: nn.Module=nn.Linear,
+            linear2_self_attention_cls: nn.Module=nn.Linear,
+            linear1_feedforward_cls: nn.Module=nn.Linear,
+            linear2_feedforward_cls: nn.Module=nn.Linear,
+            layer_norm_cls: nn.Module=LayerNorm,
+            layer_norm_eps: float=1e-5,
+            adaptive_layer_norm=False, ) -> None:
+        factory_kwargs = {"device": device, "dtype": dtype}
+        super(TransformerEncoderLayer, self).__init__()
+        # print(233333333333,d_model,nhead)
+        # import os
+        # os._exit(2333333)
+        self.self_attn = MultiheadAttention(
+            d_model,#512 16
+            nhead,
+            dropout=dropout,
+            batch_first=batch_first,
+            linear1_cls=linear1_self_attention_cls,
+            linear2_cls=linear2_self_attention_cls,
+            **factory_kwargs, )
+
+        # Implementation of Feedforward model
+        self.linear1 = linear1_feedforward_cls(d_model, dim_feedforward,
+                                               **factory_kwargs)
+        self.dropout = nn.Dropout(dropout)
+        self.linear2 = linear2_feedforward_cls(dim_feedforward, d_model,
+                                               **factory_kwargs)
+
+        self.norm_first = norm_first
+        self.dropout1 = nn.Dropout(dropout)
+        self.dropout2 = nn.Dropout(dropout)
+
+        # Legacy string support for activation function.
+        if isinstance(activation, str):
+            activation = _get_activation_fn(activation)
+        elif isinstance(activation, partial):
+            activation = activation(d_model)
+        elif activation == BalancedDoubleSwish:
+            activation = BalancedDoubleSwish(d_model)
+
+        # # We can't test self.activation in forward() in TorchScript,
+        # # so stash some information about it instead.
+        # if activation is F.relu or isinstance(activation, torch.nn.ReLU):
+        #     self.activation_relu_or_gelu = 1
+        # elif activation is F.gelu or isinstance(activation, torch.nn.GELU):
+        #     self.activation_relu_or_gelu = 2
+        # else:
+        #     self.activation_relu_or_gelu = 0
+        self.activation = activation
+
+        norm1 = layer_norm_cls(d_model, eps=layer_norm_eps, **factory_kwargs)
+        if layer_norm_cls == IdentityNorm:
+            norm2 = BalancedBasicNorm(
+                d_model, eps=layer_norm_eps, **factory_kwargs)
+        else:
+            norm2 = layer_norm_cls(
+                d_model, eps=layer_norm_eps, **factory_kwargs)
+
+        if adaptive_layer_norm:
+            self.norm1 = AdaptiveLayerNorm(d_model, norm1)
+            self.norm2 = AdaptiveLayerNorm(d_model, norm2)
+        else:
+            self.norm1 = norm1
+            self.norm2 = norm2
+
+    def __setstate__(self, state):
+        super(TransformerEncoderLayer, self).__setstate__(state)
+        if not hasattr(self, "activation"):
+            self.activation = F.relu
+
+    def forward(
+            self,
+            src: Tensor,
+            src_mask: Optional[Tensor]=None,
+            src_key_padding_mask: Optional[Tensor]=None,cache=None ) -> Tensor:
+        r"""Pass the input through the encoder layer.
+
+        Args:
+            src: the sequence to the encoder layer (required).
+            src_mask: the mask for the src sequence (optional).
+            src_key_padding_mask: the mask for the src keys per batch (optional).
+
+        Shape:
+            see the docs in Transformer class.
+        """
+        x, stage_embedding = src, None
+        is_src_tuple = False
+        if isinstance(src, tuple):
+            x, stage_embedding = src
+            is_src_tuple = True
+
+        if src_key_padding_mask is not None:
+            _skpm_dtype = src_key_padding_mask.dtype
+            if _skpm_dtype != torch.bool and not torch.is_floating_point(
+                    src_key_padding_mask):
+                raise AssertionError(
+                    "only bool and floating types of key_padding_mask are supported"
+                )
+
+        if self.norm_first:
+            x = x + self._sa_block(
+                self.norm1(x, stage_embedding),
+                src_mask,
+                src_key_padding_mask,cache=cache )
+            x = x + self._ff_block(self.norm2(x, stage_embedding))
+        else:
+            x = self.norm1(
+                x + self._sa_block(x, src_mask, src_key_padding_mask,cache=cache),
+                stage_embedding, )
+            x = self.norm2(x + self._ff_block(x), stage_embedding)
+
+        if is_src_tuple:
+            return (x, stage_embedding)
+        return x
+
+    # self-attention block
+    def _sa_block(
+            self,
+            x: Tensor,
+            attn_mask: Optional[Tensor],
+            key_padding_mask: Optional[Tensor],cache=None ) -> Tensor:
+        # print(x.shape,attn_mask.shape,key_padding_mask)
+        #torch.Size([1, 188, 512]) torch.Size([188, 188]) None
+        # import os
+        # os._exit(23333)
+        x = self.self_attn(
+            x,
+            x,
+            x,
+            attn_mask=attn_mask,
+            key_padding_mask=key_padding_mask,
+            need_weights=False,cache=cache )[0]
+        return self.dropout1(x)
+
+    # feed forward block
+    def _ff_block(self, x: Tensor) -> Tensor:
+        x = self.linear2(self.dropout(self.activation(self.linear1(x))))
+        return self.dropout2(x)
+
+
+class AdaptiveLayerNorm(nn.Module):
+    r"""Adaptive Layer Normalization"""
+
+    def __init__(self, d_model, norm) -> None:
+        super(AdaptiveLayerNorm, self).__init__()
+        self.project_layer = nn.Linear(d_model, 2 * d_model)
+        self.norm = norm
+        self.d_model = d_model
+        self.eps = self.norm.eps
+
+    def forward(self, input: Tensor, embedding: Tensor=None) -> Tensor:
+        if isinstance(input, tuple):
+            input, embedding = input
+            weight, bias = torch.split(
+                self.project_layer(embedding),
+                split_size_or_sections=self.d_model,
+                dim=-1, )
+            return (weight * self.norm(input) + bias, embedding)
+
+        weight, bias = torch.split(
+            self.project_layer(embedding),
+            split_size_or_sections=self.d_model,
+            dim=-1, )
+        return weight * self.norm(input) + bias
+
+def _get_clones(module, N):
+    return nn.ModuleList([copy.deepcopy(module) for i in range(N)])
diff --git a/AR/text_processing/__init__.py b/AR/text_processing/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/AR/text_processing/phonemizer.py b/AR/text_processing/phonemizer.py
new file mode 100644
index 0000000000000000000000000000000000000000..83ecfb76fa0fe1ab8a6e78380c0534eee165b4db
--- /dev/null
+++ b/AR/text_processing/phonemizer.py
@@ -0,0 +1,80 @@
+# modified from https://github.com/feng-yufei/shared_debugging_code/blob/main/text_processing/phonemizer.py
+import itertools
+import re
+from typing import Dict
+from typing import List
+
+import regex
+from gruut import sentences
+from gruut.const import Sentence
+from gruut.const import Word
+from AR.text_processing.symbols import SYMBOL_TO_ID
+
+
+class GruutPhonemizer:
+    def __init__(self, language: str):
+        self._phonemizer = sentences
+        self.lang = language
+        self.symbol_to_id = SYMBOL_TO_ID
+        self._special_cases_dict: Dict[str] = {
+            r"\.\.\.": "... ",
+            ";": "; ",
+            ":": ": ",
+            ",": ", ",
+            r"\.": ". ",
+            "!": "! ",
+            r"\?": "? ",
+            "—": "—",
+            "…": "… ",
+            "«": "«",
+            "»": "»"
+        }
+        self._punctuation_regexp: str = rf"([{''.join(self._special_cases_dict.keys())}])"
+
+    def _normalize_punctuation(self, text: str) -> str:
+        text = regex.sub(fr"\pZ+{self._punctuation_regexp}", r"\1", text)
+        text = regex.sub(fr"{self._punctuation_regexp}(\pL)", r"\1 \2", text)
+        text = regex.sub(r"\pZ+", r" ", text)
+        return text.strip()
+
+    def _convert_punctuation(self, word: Word) -> str:
+        if not word.phonemes:
+            return ''
+        if word.phonemes[0] in ['‖', '|']:
+            return word.text.strip()
+
+        phonemes = ''.join(word.phonemes)
+        # remove modifier characters ˈˌː with regex
+        phonemes = re.sub(r'[ˈˌː͡]', '', phonemes)
+        return phonemes.strip()
+
+    def phonemize(self, text: str, espeak: bool=False) -> str:
+        text_to_phonemize: str = self._normalize_punctuation(text)
+        sents: List[Sentence] = [
+            sent
+            for sent in self._phonemizer(
+                text_to_phonemize, lang="en-us", espeak=espeak)
+        ]
+        words: List[str] = [
+            self._convert_punctuation(word) for word in itertools.chain(*sents)
+        ]
+        return ' '.join(words)
+
+    def transform(self, phonemes):
+        # convert phonemes to ids
+        # dictionary is in symbols.py
+        return [
+            self.symbol_to_id[p] for p in phonemes
+            if p in self.symbol_to_id.keys()
+        ]
+
+
+if __name__ == "__main__":
+    phonemizer = GruutPhonemizer("en-us")
+    # text -> IPA
+    phonemes = phonemizer.phonemize("Hello, wor-ld ?")
+    print("phonemes:", phonemes)
+    print("len(phonemes):", len(phonemes))
+    phoneme_ids = phonemizer.transform(phonemes)
+    print("phoneme_ids:", phoneme_ids)
+    print("len(phoneme_ids):", len(phoneme_ids))
diff --git a/AR/text_processing/symbols.py b/AR/text_processing/symbols.py
new file mode 100644
index 0000000000000000000000000000000000000000..6bc9a0c3eb77594b10670eb8caca7016cbbe9fdf
--- /dev/null
+++ b/AR/text_processing/symbols.py
@@ -0,0 +1,9 @@
+# modified from https://github.com/feng-yufei/shared_debugging_code/blob/main/text_processing/symbols.py
+PAD = '_'
+PUNCTUATION = ';:,.!?¡¿—…"«»“” '
+LETTERS = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz'
+IPA_LETTERS = "ɑɐɒæɓʙβɔɕçɗɖðʤəɘɚɛɜɝɞɟʄɡɠɢʛɦɧħɥʜɨɪʝɭɬɫɮʟɱɯɰŋɳɲɴøɵɸθœɶʘɹɺɾɻʀʁɽʂʃʈʧʉʊʋⱱʌɣɤʍχʎʏʑʐʒʔʡʕʢǀǁǂǃˈˌːˑʼʴʰʱʲʷˠˤ˞↓↑→↗↘'̩'ᵻ"
+SYMBOLS = [PAD] + list(PUNCTUATION) + list(LETTERS) + list(IPA_LETTERS)
+SPACE_ID = SYMBOLS.index(" ")
+SYMBOL_TO_ID = {s: i for i, s in enumerate(SYMBOLS)}
+ID_TO_SYMBOL = {i: s for i, s in enumerate(SYMBOLS)}
diff --git a/AR/utils/__init__.py b/AR/utils/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..c2eaf61adcfee96d6e7ec8fd70a7603e18afb567
--- /dev/null
+++ b/AR/utils/__init__.py
@@ -0,0 +1,37 @@
+import re
+
+
+def str2bool(str):
+    return True if str.lower() == 'true' else False
+
+
+def get_newest_ckpt(string_list):
+    # 定义一个正则表达式模式，用于匹配字符串中的数字
+    pattern = r'epoch=(\d+)-step=(\d+)\.ckpt'
+
+    # 使用正则表达式提取每个字符串中的数字信息，并创建一个包含元组的列表
+    extracted_info = []
+    for string in string_list:
+        match = re.match(pattern, string)
+        if match:
+            epoch = int(match.group(1))
+            step = int(match.group(2))
+            extracted_info.append((epoch, step, string))
+    # 按照 epoch 后面的数字和 step 后面的数字进行排序
+    sorted_info = sorted(
+        extracted_info, key=lambda x: (x[0], x[1]), reverse=True)
+    # 获取最新的 ckpt 文件名
+    newest_ckpt = sorted_info[0][2]
+    return newest_ckpt
+
+
+# 文本存在且不为空时 return True
+def check_txt_file(file_path):
+    try:
+        with open(file_path, 'r') as file:
+            text = file.readline().strip()
+        assert text.strip() != ''
+        return text
+    except Exception:
+        return False
+    return False
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diff --git a/AR/utils/initialize.py b/AR/utils/initialize.py
new file mode 100644
index 0000000000000000000000000000000000000000..17ff9f92e51c8941973139d6e34d4a1c7cd8daaa
--- /dev/null
+++ b/AR/utils/initialize.py
@@ -0,0 +1,38 @@
+#!/usr/bin/env python3
+"""Initialize modules for espnet2 neural networks."""
+import torch
+from typeguard import check_argument_types
+
+
+def initialize(model: torch.nn.Module, init: str):
+    """Initialize weights of a neural network module.
+
+    Parameters are initialized using the given method or distribution.
+
+    Custom initialization routines can be implemented into submodules
+    as function `espnet_initialization_fn` within the custom module.
+
+    Args:
+        model: Target.
+        init: Method of initialization.
+    """
+    assert check_argument_types()
+    print("init with", init)
+
+    # weight init
+    for p in model.parameters():
+        if p.dim() > 1:
+            if init == "xavier_uniform":
+                torch.nn.init.xavier_uniform_(p.data)
+            elif init == "xavier_normal":
+                torch.nn.init.xavier_normal_(p.data)
+            elif init == "kaiming_uniform":
+                torch.nn.init.kaiming_uniform_(p.data, nonlinearity="relu")
+            elif init == "kaiming_normal":
+                torch.nn.init.kaiming_normal_(p.data, nonlinearity="relu")
+            else:
+                raise ValueError("Unknown initialization: " + init)
+    # bias init
+    for name, p in model.named_parameters():
+        if ".bias" in name and p.dim() == 1:
+            p.data.zero_()
diff --git a/AR/utils/io.py b/AR/utils/io.py
new file mode 100644
index 0000000000000000000000000000000000000000..24f1be625d1c767fe68c2f348b1d04011cd82699
--- /dev/null
+++ b/AR/utils/io.py
@@ -0,0 +1,32 @@
+import sys
+
+import torch
+import yaml
+
+
+def load_yaml_config(path):
+    with open(path) as f:
+        config = yaml.full_load(f)
+    return config
+
+
+def save_config_to_yaml(config, path):
+    assert path.endswith('.yaml')
+    with open(path, 'w') as f:
+        f.write(yaml.dump(config))
+        f.close()
+
+
+def write_args(args, path):
+    args_dict = dict((name, getattr(args, name)) for name in dir(args)
+                     if not name.startswith('_'))
+    with open(path, 'a') as args_file:
+        args_file.write('==> torch version: {}\n'.format(torch.__version__))
+        args_file.write(
+            '==> cudnn version: {}\n'.format(torch.backends.cudnn.version()))
+        args_file.write('==> Cmd:\n')
+        args_file.write(str(sys.argv))
+        args_file.write('\n==> args:\n')
+        for k, v in sorted(args_dict.items()):
+            args_file.write('  %s: %s\n' % (str(k), str(v)))
+        args_file.close()
diff --git a/feature_extractor/__init__.py b/feature_extractor/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..79aa9294fec8fd823afae7d1a18e3279533dd7cf
--- /dev/null
+++ b/feature_extractor/__init__.py
@@ -0,0 +1,6 @@
+from . import cnhubert, whisper_enc
+
+content_module_map = {
+    'cnhubert': cnhubert,
+    'whisper': whisper_enc
+}
\ No newline at end of file
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diff --git a/feature_extractor/cnhubert.py b/feature_extractor/cnhubert.py
new file mode 100644
index 0000000000000000000000000000000000000000..048dc85c8093cd849232b34c8b059cf6040a4cc0
--- /dev/null
+++ b/feature_extractor/cnhubert.py
@@ -0,0 +1,97 @@
+import time
+
+import librosa
+import torch
+import torch.nn.functional as F
+import soundfile as sf
+import logging
+
+logging.getLogger("numba").setLevel(logging.WARNING)
+
+from transformers import (
+    Wav2Vec2FeatureExtractor,
+    HubertModel,
+    Wav2Vec2Model,
+)
+
+import utils
+import torch.nn as nn
+
+cnhubert_base_path=None
+class CNHubert(nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.model = HubertModel.from_pretrained(cnhubert_base_path)
+        self.feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(cnhubert_base_path)
+    def forward(self, x):
+        input_values = self.feature_extractor(x, return_tensors="pt", sampling_rate=16000).input_values.to(x.device)
+        feats = self.model(input_values)["last_hidden_state"]
+        return feats
+
+# class CNHubertLarge(nn.Module):
+#     def __init__(self):
+#         super().__init__()
+#         self.model = HubertModel.from_pretrained("/data/docker/liujing04/gpt-vits/chinese-hubert-large")
+#         self.feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("/data/docker/liujing04/gpt-vits/chinese-hubert-large")
+#     def forward(self, x):
+#         input_values = self.feature_extractor(x, return_tensors="pt", sampling_rate=16000).input_values.to(x.device)
+#         feats = self.model(input_values)["last_hidden_state"]
+#         return feats
+#
+# class CVec(nn.Module):
+#     def __init__(self):
+#         super().__init__()
+#         self.model = HubertModel.from_pretrained("/data/docker/liujing04/vc-webui-big/hubert_base")
+#         self.feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("/data/docker/liujing04/vc-webui-big/hubert_base")
+#     def forward(self, x):
+#         input_values = self.feature_extractor(x, return_tensors="pt", sampling_rate=16000).input_values.to(x.device)
+#         feats = self.model(input_values)["last_hidden_state"]
+#         return feats
+#
+# class cnw2v2base(nn.Module):
+#     def __init__(self):
+#         super().__init__()
+#         self.model = Wav2Vec2Model.from_pretrained("/data/docker/liujing04/gpt-vits/chinese-wav2vec2-base")
+#         self.feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("/data/docker/liujing04/gpt-vits/chinese-wav2vec2-base")
+#     def forward(self, x):
+#         input_values = self.feature_extractor(x, return_tensors="pt", sampling_rate=16000).input_values.to(x.device)
+#         feats = self.model(input_values)["last_hidden_state"]
+#         return feats
+
+
+
+def get_model():
+    model = CNHubert()
+    model.eval()
+    return model
+
+# def get_large_model():
+#     model = CNHubertLarge()
+#     model.eval()
+#     return model
+#
+# def get_model_cvec():
+#     model = CVec()
+#     model.eval()
+#     return model
+#
+# def get_model_cnw2v2base():
+#     model = cnw2v2base()
+#     model.eval()
+#     return model
+
+def get_content(hmodel, wav_16k_tensor):
+    with torch.no_grad():
+        feats = hmodel(wav_16k_tensor)
+    return feats.transpose(1,2)
+
+
+if __name__ == '__main__':
+    model = get_model()
+    src_path = "/Users/Shared/原音频2.wav"
+    wav_16k_tensor = utils.load_wav_to_torch_and_resample(src_path, 16000)
+    model = model
+    wav_16k_tensor = wav_16k_tensor
+    feats = get_content(model,wav_16k_tensor)
+    print(feats.shape)
+
diff --git a/feature_extractor/whisper_enc.py b/feature_extractor/whisper_enc.py
new file mode 100644
index 0000000000000000000000000000000000000000..023f751275bbf9d498b76a4da7ccd302e437949f
--- /dev/null
+++ b/feature_extractor/whisper_enc.py
@@ -0,0 +1,22 @@
+import torch
+
+
+def get_model():
+    import whisper
+    model = whisper.load_model("small", device='cpu')
+
+    return model.encoder
+
+
+def get_content(model=None, wav_16k_tensor=None):
+    from whisper import log_mel_spectrogram, pad_or_trim
+    dev = next(model.parameters()).device
+    mel = log_mel_spectrogram(wav_16k_tensor).to(dev)[:, :3000]
+    # if torch.cuda.is_available():
+    #     mel = mel.to(torch.float16)
+    feature_len = mel.shape[-1] // 2
+    assert  mel.shape[-1] < 3000, "输入音频过长，只允许输入30以内音频"
+    with torch.no_grad():
+        feature = model(pad_or_trim(mel, 3000).unsqueeze(0))[:1, :feature_len, :].transpose(1,2)
+    return feature
+
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diff --git a/module/attentions.py b/module/attentions.py
new file mode 100644
index 0000000000000000000000000000000000000000..07672e248f62c18e98381b75d739dad566e5663f
--- /dev/null
+++ b/module/attentions.py
@@ -0,0 +1,514 @@
+import math
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+from module import commons
+from module. modules import LayerNorm
+   
+
+class Encoder(nn.Module):
+  def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., window_size=4,isflow=False, **kwargs):
+    super().__init__()
+    self.hidden_channels = hidden_channels
+    self.filter_channels = filter_channels
+    self.n_heads = n_heads
+    self.n_layers = n_layers
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.window_size = window_size
+
+    self.drop = nn.Dropout(p_dropout)
+    self.attn_layers = nn.ModuleList()
+    self.norm_layers_1 = nn.ModuleList()
+    self.ffn_layers = nn.ModuleList()
+    self.norm_layers_2 = nn.ModuleList()
+    for i in range(self.n_layers):
+      self.attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, window_size=window_size))
+      self.norm_layers_1.append(LayerNorm(hidden_channels))
+      self.ffn_layers.append(FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout))
+      self.norm_layers_2.append(LayerNorm(hidden_channels))
+    if isflow:
+      cond_layer = torch.nn.Conv1d(kwargs["gin_channels"], 2*hidden_channels*n_layers, 1)
+      self.cond_pre = torch.nn.Conv1d(hidden_channels, 2*hidden_channels, 1)
+      self.cond_layer = weight_norm_modules(cond_layer, name='weight')
+      self.gin_channels = kwargs["gin_channels"]
+  def forward(self, x, x_mask, g=None):
+    attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
+    x = x * x_mask
+    if g is not None:
+      g = self.cond_layer(g)
+
+    for i in range(self.n_layers):
+      if g is not None:
+        x = self.cond_pre(x)
+        cond_offset = i * 2 * self.hidden_channels
+        g_l = g[:,cond_offset:cond_offset+2*self.hidden_channels,:]
+        x = commons.fused_add_tanh_sigmoid_multiply(
+          x,
+          g_l,
+          torch.IntTensor([self.hidden_channels]))
+      y = self.attn_layers[i](x, x, attn_mask)
+      y = self.drop(y)
+      x = self.norm_layers_1[i](x + y)
+
+      y = self.ffn_layers[i](x, x_mask)
+      y = self.drop(y)
+      x = self.norm_layers_2[i](x + y)
+    x = x * x_mask
+    return x
+
+
+class Decoder(nn.Module):
+  def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., proximal_bias=False, proximal_init=True, **kwargs):
+    super().__init__()
+    self.hidden_channels = hidden_channels
+    self.filter_channels = filter_channels
+    self.n_heads = n_heads
+    self.n_layers = n_layers
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.proximal_bias = proximal_bias
+    self.proximal_init = proximal_init
+
+    self.drop = nn.Dropout(p_dropout)
+    self.self_attn_layers = nn.ModuleList()
+    self.norm_layers_0 = nn.ModuleList()
+    self.encdec_attn_layers = nn.ModuleList()
+    self.norm_layers_1 = nn.ModuleList()
+    self.ffn_layers = nn.ModuleList()
+    self.norm_layers_2 = nn.ModuleList()
+    for i in range(self.n_layers):
+      self.self_attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, proximal_bias=proximal_bias, proximal_init=proximal_init))
+      self.norm_layers_0.append(LayerNorm(hidden_channels))
+      self.encdec_attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout))
+      self.norm_layers_1.append(LayerNorm(hidden_channels))
+      self.ffn_layers.append(FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout, causal=True))
+      self.norm_layers_2.append(LayerNorm(hidden_channels))
+
+  def forward(self, x, x_mask, h, h_mask):
+    """
+    x: decoder input
+    h: encoder output
+    """
+    self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(device=x.device, dtype=x.dtype)
+    encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
+    x = x * x_mask
+    for i in range(self.n_layers):
+      y = self.self_attn_layers[i](x, x, self_attn_mask)
+      y = self.drop(y)
+      x = self.norm_layers_0[i](x + y)
+
+      y = self.encdec_attn_layers[i](x, h, encdec_attn_mask)
+      y = self.drop(y)
+      x = self.norm_layers_1[i](x + y)
+      
+      y = self.ffn_layers[i](x, x_mask)
+      y = self.drop(y)
+      x = self.norm_layers_2[i](x + y)
+    x = x * x_mask
+    return x
+
+
+class MultiHeadAttention(nn.Module):
+  def __init__(self, channels, out_channels, n_heads, p_dropout=0., window_size=None, heads_share=True, block_length=None, proximal_bias=False, proximal_init=False):
+    super().__init__()
+    assert channels % n_heads == 0
+
+    self.channels = channels
+    self.out_channels = out_channels
+    self.n_heads = n_heads
+    self.p_dropout = p_dropout
+    self.window_size = window_size
+    self.heads_share = heads_share
+    self.block_length = block_length
+    self.proximal_bias = proximal_bias
+    self.proximal_init = proximal_init
+    self.attn = None
+
+    self.k_channels = channels // n_heads
+    self.conv_q = nn.Conv1d(channels, channels, 1)
+    self.conv_k = nn.Conv1d(channels, channels, 1)
+    self.conv_v = nn.Conv1d(channels, channels, 1)
+    self.conv_o = nn.Conv1d(channels, out_channels, 1)
+    self.drop = nn.Dropout(p_dropout)
+
+    if window_size is not None:
+      n_heads_rel = 1 if heads_share else n_heads
+      rel_stddev = self.k_channels**-0.5
+      self.emb_rel_k = nn.Parameter(torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels) * rel_stddev)
+      self.emb_rel_v = nn.Parameter(torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels) * rel_stddev)
+
+    nn.init.xavier_uniform_(self.conv_q.weight)
+    nn.init.xavier_uniform_(self.conv_k.weight)
+    nn.init.xavier_uniform_(self.conv_v.weight)
+    if proximal_init:
+      with torch.no_grad():
+        self.conv_k.weight.copy_(self.conv_q.weight)
+        self.conv_k.bias.copy_(self.conv_q.bias)
+      
+  def forward(self, x, c, attn_mask=None):
+    q = self.conv_q(x)
+    k = self.conv_k(c)
+    v = self.conv_v(c)
+    
+    x, self.attn = self.attention(q, k, v, mask=attn_mask)
+
+    x = self.conv_o(x)
+    return x
+
+  def attention(self, query, key, value, mask=None):
+    # reshape [b, d, t] -> [b, n_h, t, d_k]
+    b, d, t_s, t_t = (*key.size(), query.size(2))
+    query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3)
+    key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
+    value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
+
+    scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1))
+    if self.window_size is not None:
+      assert t_s == t_t, "Relative attention is only available for self-attention."
+      key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s)
+      rel_logits = self._matmul_with_relative_keys(query /math.sqrt(self.k_channels), key_relative_embeddings)
+      scores_local = self._relative_position_to_absolute_position(rel_logits)
+      scores = scores + scores_local
+    if self.proximal_bias:
+      assert t_s == t_t, "Proximal bias is only available for self-attention."
+      scores = scores + self._attention_bias_proximal(t_s).to(device=scores.device, dtype=scores.dtype)
+    if mask is not None:
+      scores = scores.masked_fill(mask == 0, -1e4)
+      if self.block_length is not None:
+        assert t_s == t_t, "Local attention is only available for self-attention."
+        block_mask = torch.ones_like(scores).triu(-self.block_length).tril(self.block_length)
+        scores = scores.masked_fill(block_mask == 0, -1e4)
+    p_attn = F.softmax(scores, dim=-1) # [b, n_h, t_t, t_s]
+    p_attn = self.drop(p_attn)
+    output = torch.matmul(p_attn, value)
+    if self.window_size is not None:
+      relative_weights = self._absolute_position_to_relative_position(p_attn)
+      value_relative_embeddings = self._get_relative_embeddings(self.emb_rel_v, t_s)
+      output = output + self._matmul_with_relative_values(relative_weights, value_relative_embeddings)
+    output = output.transpose(2, 3).contiguous().view(b, d, t_t) # [b, n_h, t_t, d_k] -> [b, d, t_t]
+    return output, p_attn
+
+  def _matmul_with_relative_values(self, x, y):
+    """
+    x: [b, h, l, m]
+    y: [h or 1, m, d]
+    ret: [b, h, l, d]
+    """
+    ret = torch.matmul(x, y.unsqueeze(0))
+    return ret
+
+  def _matmul_with_relative_keys(self, x, y):
+    """
+    x: [b, h, l, d]
+    y: [h or 1, m, d]
+    ret: [b, h, l, m]
+    """
+    ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1))
+    return ret
+
+  def _get_relative_embeddings(self, relative_embeddings, length):
+    max_relative_position = 2 * self.window_size + 1
+    # Pad first before slice to avoid using cond ops.
+    pad_length = max(length - (self.window_size + 1), 0)
+    slice_start_position = max((self.window_size + 1) - length, 0)
+    slice_end_position = slice_start_position + 2 * length - 1
+    if pad_length > 0:
+      padded_relative_embeddings = F.pad(
+          relative_embeddings,
+          commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]]))
+    else:
+      padded_relative_embeddings = relative_embeddings
+    used_relative_embeddings = padded_relative_embeddings[:,slice_start_position:slice_end_position]
+    return used_relative_embeddings
+
+  def _relative_position_to_absolute_position(self, x):
+    """
+    x: [b, h, l, 2*l-1]
+    ret: [b, h, l, l]
+    """
+    batch, heads, length, _ = x.size()
+    # Concat columns of pad to shift from relative to absolute indexing.
+    x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, 1]]))
+
+    # Concat extra elements so to add up to shape (len+1, 2*len-1).
+    x_flat = x.view([batch, heads, length * 2 * length])
+    x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [0, length - 1]]))
+
+    # Reshape and slice out the padded elements.
+    x_final = x_flat.view([batch, heads, length+1, 2*length-1])[:, :, :length, length-1:]
+    return x_final
+
+  def _absolute_position_to_relative_position(self, x):
+    """
+    x: [b, h, l, l]
+    ret: [b, h, l, 2*l-1]
+    """
+    batch, heads, length, _ = x.size()
+    # padd along column
+    x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length - 1]]))
+    x_flat = x.view([batch, heads, length**2 + length*(length -1)])
+    # add 0's in the beginning that will skew the elements after reshape
+    x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]]))
+    x_final = x_flat.view([batch, heads, length, 2*length])[:,:,:,1:]
+    return x_final
+
+  def _attention_bias_proximal(self, length):
+    """Bias for self-attention to encourage attention to close positions.
+    Args:
+      length: an integer scalar.
+    Returns:
+      a Tensor with shape [1, 1, length, length]
+    """
+    r = torch.arange(length, dtype=torch.float32)
+    diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1)
+    return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0)
+
+
+class FFN(nn.Module):
+  def __init__(self, in_channels, out_channels, filter_channels, kernel_size, p_dropout=0., activation=None, causal=False):
+    super().__init__()
+    self.in_channels = in_channels
+    self.out_channels = out_channels
+    self.filter_channels = filter_channels
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.activation = activation
+    self.causal = causal
+
+    if causal:
+      self.padding = self._causal_padding
+    else:
+      self.padding = self._same_padding
+
+    self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size)
+    self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size)
+    self.drop = nn.Dropout(p_dropout)
+
+  def forward(self, x, x_mask):
+    x = self.conv_1(self.padding(x * x_mask))
+    if self.activation == "gelu":
+      x = x * torch.sigmoid(1.702 * x)
+    else:
+      x = torch.relu(x)
+    x = self.drop(x)
+    x = self.conv_2(self.padding(x * x_mask))
+    return x * x_mask
+  
+  def _causal_padding(self, x):
+    if self.kernel_size == 1:
+      return x
+    pad_l = self.kernel_size - 1
+    pad_r = 0
+    padding = [[0, 0], [0, 0], [pad_l, pad_r]]
+    x = F.pad(x, commons.convert_pad_shape(padding))
+    return x
+
+  def _same_padding(self, x):
+    if self.kernel_size == 1:
+      return x
+    pad_l = (self.kernel_size - 1) // 2
+    pad_r = self.kernel_size // 2
+    padding = [[0, 0], [0, 0], [pad_l, pad_r]]
+    x = F.pad(x, commons.convert_pad_shape(padding))
+    return x
+
+
+import torch.nn as nn
+from torch.nn.utils import remove_weight_norm, weight_norm
+
+
+class Depthwise_Separable_Conv1D(nn.Module):
+  def __init__(
+          self,
+          in_channels,
+          out_channels,
+          kernel_size,
+          stride=1,
+          padding=0,
+          dilation=1,
+          bias=True,
+          padding_mode='zeros',  # TODO: refine this type
+          device=None,
+          dtype=None
+  ):
+    super().__init__()
+    self.depth_conv = nn.Conv1d(in_channels=in_channels, out_channels=in_channels, kernel_size=kernel_size,
+                                groups=in_channels, stride=stride, padding=padding, dilation=dilation, bias=bias,
+                                padding_mode=padding_mode, device=device, dtype=dtype)
+    self.point_conv = nn.Conv1d(in_channels=in_channels, out_channels=out_channels, kernel_size=1, bias=bias,
+                                device=device, dtype=dtype)
+
+  def forward(self, input):
+    return self.point_conv(self.depth_conv(input))
+
+  def weight_norm(self):
+    self.depth_conv = weight_norm(self.depth_conv, name='weight')
+    self.point_conv = weight_norm(self.point_conv, name='weight')
+
+  def remove_weight_norm(self):
+    self.depth_conv = remove_weight_norm(self.depth_conv, name='weight')
+    self.point_conv = remove_weight_norm(self.point_conv, name='weight')
+
+
+class Depthwise_Separable_TransposeConv1D(nn.Module):
+  def __init__(
+          self,
+          in_channels,
+          out_channels,
+          kernel_size,
+          stride=1,
+          padding=0,
+          output_padding=0,
+          bias=True,
+          dilation=1,
+          padding_mode='zeros',  # TODO: refine this type
+          device=None,
+          dtype=None
+  ):
+    super().__init__()
+    self.depth_conv = nn.ConvTranspose1d(in_channels=in_channels, out_channels=in_channels, kernel_size=kernel_size,
+                                         groups=in_channels, stride=stride, output_padding=output_padding,
+                                         padding=padding, dilation=dilation, bias=bias, padding_mode=padding_mode,
+                                         device=device, dtype=dtype)
+    self.point_conv = nn.Conv1d(in_channels=in_channels, out_channels=out_channels, kernel_size=1, bias=bias,
+                                device=device, dtype=dtype)
+
+  def forward(self, input):
+    return self.point_conv(self.depth_conv(input))
+
+  def weight_norm(self):
+    self.depth_conv = weight_norm(self.depth_conv, name='weight')
+    self.point_conv = weight_norm(self.point_conv, name='weight')
+
+  def remove_weight_norm(self):
+    remove_weight_norm(self.depth_conv, name='weight')
+    remove_weight_norm(self.point_conv, name='weight')
+
+
+def weight_norm_modules(module, name='weight', dim=0):
+  if isinstance(module, Depthwise_Separable_Conv1D) or isinstance(module, Depthwise_Separable_TransposeConv1D):
+    module.weight_norm()
+    return module
+  else:
+    return weight_norm(module, name, dim)
+
+
+def remove_weight_norm_modules(module, name='weight'):
+  if isinstance(module, Depthwise_Separable_Conv1D) or isinstance(module, Depthwise_Separable_TransposeConv1D):
+    module.remove_weight_norm()
+  else:
+    remove_weight_norm(module, name)
+
+
+class FFT(nn.Module):
+  def __init__(self, hidden_channels, filter_channels, n_heads, n_layers=1, kernel_size=1, p_dropout=0.,
+               proximal_bias=False, proximal_init=True, isflow = False, **kwargs):
+    super().__init__()
+    self.hidden_channels = hidden_channels
+    self.filter_channels = filter_channels
+    self.n_heads = n_heads
+    self.n_layers = n_layers
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.proximal_bias = proximal_bias
+    self.proximal_init = proximal_init
+    if isflow:
+      cond_layer = torch.nn.Conv1d(kwargs["gin_channels"], 2*hidden_channels*n_layers, 1)
+      self.cond_pre = torch.nn.Conv1d(hidden_channels, 2*hidden_channels, 1)
+      self.cond_layer = weight_norm_modules(cond_layer, name='weight')
+      self.gin_channels = kwargs["gin_channels"]
+    self.drop = nn.Dropout(p_dropout)
+    self.self_attn_layers = nn.ModuleList()
+    self.norm_layers_0 = nn.ModuleList()
+    self.ffn_layers = nn.ModuleList()
+    self.norm_layers_1 = nn.ModuleList()
+    for i in range(self.n_layers):
+      self.self_attn_layers.append(
+        MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, proximal_bias=proximal_bias,
+                           proximal_init=proximal_init))
+      self.norm_layers_0.append(LayerNorm(hidden_channels))
+      self.ffn_layers.append(
+        FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout, causal=True))
+      self.norm_layers_1.append(LayerNorm(hidden_channels))
+
+  def forward(self, x, x_mask, g = None):
+    """
+    x: decoder input
+    h: encoder output
+    """
+    if g is not None:
+      g = self.cond_layer(g)
+
+    self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(device=x.device, dtype=x.dtype)
+    x = x * x_mask
+    for i in range(self.n_layers):
+      if g is not None:
+        x = self.cond_pre(x)
+        cond_offset = i * 2 * self.hidden_channels
+        g_l = g[:,cond_offset:cond_offset+2*self.hidden_channels,:]
+        x = commons.fused_add_tanh_sigmoid_multiply(
+          x,
+          g_l,
+          torch.IntTensor([self.hidden_channels]))
+      y = self.self_attn_layers[i](x, x, self_attn_mask)
+      y = self.drop(y)
+      x = self.norm_layers_0[i](x + y)
+
+      y = self.ffn_layers[i](x, x_mask)
+      y = self.drop(y)
+      x = self.norm_layers_1[i](x + y)
+    x = x * x_mask
+    return x
+
+
+
+class TransformerCouplingLayer(nn.Module):
+  def __init__(self,
+      channels,
+      hidden_channels,
+      kernel_size,
+      n_layers,
+      n_heads,
+      p_dropout=0,
+      filter_channels=0,
+      mean_only=False,
+      wn_sharing_parameter=None,
+      gin_channels = 0
+      ):
+    assert channels % 2 == 0, "channels should be divisible by 2"
+    super().__init__()
+    self.channels = channels
+    self.hidden_channels = hidden_channels
+    self.kernel_size = kernel_size
+    self.n_layers = n_layers
+    self.half_channels = channels // 2
+    self.mean_only = mean_only
+
+    self.pre = nn.Conv1d(self.half_channels, hidden_channels, 1)
+    self.enc = Encoder(hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout, isflow = True, gin_channels = gin_channels) if wn_sharing_parameter is None else wn_sharing_parameter
+    self.post = nn.Conv1d(hidden_channels, self.half_channels * (2 - mean_only), 1)
+    self.post.weight.data.zero_()
+    self.post.bias.data.zero_()
+
+  def forward(self, x, x_mask, g=None, reverse=False):
+    x0, x1 = torch.split(x, [self.half_channels]*2, 1)
+    h = self.pre(x0) * x_mask
+    h = self.enc(h, x_mask, g=g)
+    stats = self.post(h) * x_mask
+    if not self.mean_only:
+      m, logs = torch.split(stats, [self.half_channels]*2, 1)
+    else:
+      m = stats
+      logs = torch.zeros_like(m)
+
+    if not reverse:
+      x1 = m + x1 * torch.exp(logs) * x_mask
+      x = torch.cat([x0, x1], 1)
+      logdet = torch.sum(logs, [1,2])
+      return x, logdet
+    else:
+      x1 = (x1 - m) * torch.exp(-logs) * x_mask
+      x = torch.cat([x0, x1], 1)
+      return x
\ No newline at end of file
diff --git a/module/commons.py b/module/commons.py
new file mode 100644
index 0000000000000000000000000000000000000000..7c9b028f1b3a6da4e5a90f35af6560666af466e9
--- /dev/null
+++ b/module/commons.py
@@ -0,0 +1,189 @@
+import math
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+
+def init_weights(m, mean=0.0, std=0.01):
+  classname = m.__class__.__name__
+  if classname.find("Conv") != -1:
+    m.weight.data.normal_(mean, std)
+
+
+def get_padding(kernel_size, dilation=1):
+  return int((kernel_size*dilation - dilation)/2)
+
+
+def convert_pad_shape(pad_shape):
+  l = pad_shape[::-1]
+  pad_shape = [item for sublist in l for item in sublist]
+  return pad_shape
+
+
+def intersperse(lst, item):
+  result = [item] * (len(lst) * 2 + 1)
+  result[1::2] = lst
+  return result
+
+
+def kl_divergence(m_p, logs_p, m_q, logs_q):
+  """KL(P||Q)"""
+  kl = (logs_q - logs_p) - 0.5
+  kl += 0.5 * (torch.exp(2. * logs_p) + ((m_p - m_q)**2)) * torch.exp(-2. * logs_q)
+  return kl
+
+
+def rand_gumbel(shape):
+  """Sample from the Gumbel distribution, protect from overflows."""
+  uniform_samples = torch.rand(shape) * 0.99998 + 0.00001
+  return -torch.log(-torch.log(uniform_samples))
+
+
+def rand_gumbel_like(x):
+  g = rand_gumbel(x.size()).to(dtype=x.dtype, device=x.device)
+  return g
+
+
+def slice_segments(x, ids_str, segment_size=4):
+  ret = torch.zeros_like(x[:, :, :segment_size])
+  for i in range(x.size(0)):
+    idx_str = ids_str[i]
+    idx_end = idx_str + segment_size
+    ret[i] = x[i, :, idx_str:idx_end]
+  return ret
+
+
+def rand_slice_segments(x, x_lengths=None, segment_size=4):
+  b, d, t = x.size()
+  if x_lengths is None:
+    x_lengths = t
+  ids_str_max = x_lengths - segment_size + 1
+  ids_str = (torch.rand([b]).to(device=x.device) * ids_str_max).to(dtype=torch.long)
+  ret = slice_segments(x, ids_str, segment_size)
+  return ret, ids_str
+
+
+def get_timing_signal_1d(
+    length, channels, min_timescale=1.0, max_timescale=1.0e4):
+  position = torch.arange(length, dtype=torch.float)
+  num_timescales = channels // 2
+  log_timescale_increment = (
+      math.log(float(max_timescale) / float(min_timescale)) /
+      (num_timescales - 1))
+  inv_timescales = min_timescale * torch.exp(
+      torch.arange(num_timescales, dtype=torch.float) * -log_timescale_increment)
+  scaled_time = position.unsqueeze(0) * inv_timescales.unsqueeze(1)
+  signal = torch.cat([torch.sin(scaled_time), torch.cos(scaled_time)], 0)
+  signal = F.pad(signal, [0, 0, 0, channels % 2])
+  signal = signal.view(1, channels, length)
+  return signal
+
+
+def add_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4):
+  b, channels, length = x.size()
+  signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
+  return x + signal.to(dtype=x.dtype, device=x.device)
+
+
+def cat_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4, axis=1):
+  b, channels, length = x.size()
+  signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
+  return torch.cat([x, signal.to(dtype=x.dtype, device=x.device)], axis)
+
+
+def subsequent_mask(length):
+  mask = torch.tril(torch.ones(length, length)).unsqueeze(0).unsqueeze(0)
+  return mask
+
+
+@torch.jit.script
+def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
+  n_channels_int = n_channels[0]
+  in_act = input_a + input_b
+  t_act = torch.tanh(in_act[:, :n_channels_int, :])
+  s_act = torch.sigmoid(in_act[:, n_channels_int:, :])
+  acts = t_act * s_act
+  return acts
+
+
+def convert_pad_shape(pad_shape):
+  l = pad_shape[::-1]
+  pad_shape = [item for sublist in l for item in sublist]
+  return pad_shape
+
+
+def shift_1d(x):
+  x = F.pad(x, convert_pad_shape([[0, 0], [0, 0], [1, 0]]))[:, :, :-1]
+  return x
+
+
+def sequence_mask(length, max_length=None):
+  if max_length is None:
+    max_length = length.max()
+  x = torch.arange(max_length, dtype=length.dtype, device=length.device)
+  return x.unsqueeze(0) < length.unsqueeze(1)
+
+
+def generate_path(duration, mask):
+  """
+  duration: [b, 1, t_x]
+  mask: [b, 1, t_y, t_x]
+  """
+  device = duration.device
+  
+  b, _, t_y, t_x = mask.shape
+  cum_duration = torch.cumsum(duration, -1)
+  
+  cum_duration_flat = cum_duration.view(b * t_x)
+  path = sequence_mask(cum_duration_flat, t_y).to(mask.dtype)
+  path = path.view(b, t_x, t_y)
+  path = path - F.pad(path, convert_pad_shape([[0, 0], [1, 0], [0, 0]]))[:, :-1]
+  path = path.unsqueeze(1).transpose(2,3) * mask
+  return path
+
+
+def clip_grad_value_(parameters, clip_value, norm_type=2):
+  if isinstance(parameters, torch.Tensor):
+    parameters = [parameters]
+  parameters = list(filter(lambda p: p.grad is not None, parameters))
+  norm_type = float(norm_type)
+  if clip_value is not None:
+    clip_value = float(clip_value)
+
+  total_norm = 0
+  for p in parameters:
+    param_norm = p.grad.data.norm(norm_type)
+    total_norm += param_norm.item() ** norm_type
+    if clip_value is not None:
+      p.grad.data.clamp_(min=-clip_value, max=clip_value)
+  total_norm = total_norm ** (1. / norm_type)
+  return total_norm
+
+
+def squeeze(x, x_mask=None, n_sqz=2):
+  b, c, t = x.size()
+
+  t = (t // n_sqz) * n_sqz
+  x = x[:, :, :t]
+  x_sqz = x.view(b, c, t // n_sqz, n_sqz)
+  x_sqz = x_sqz.permute(0, 3, 1, 2).contiguous().view(b, c * n_sqz, t // n_sqz)
+
+  if x_mask is not None:
+    x_mask = x_mask[:, :, n_sqz - 1::n_sqz]
+  else:
+    x_mask = torch.ones(b, 1, t // n_sqz).to(device=x.device, dtype=x.dtype)
+  return x_sqz * x_mask, x_mask
+
+
+def unsqueeze(x, x_mask=None, n_sqz=2):
+  b, c, t = x.size()
+
+  x_unsqz = x.view(b, n_sqz, c // n_sqz, t)
+  x_unsqz = x_unsqz.permute(0, 2, 3, 1).contiguous().view(b, c // n_sqz, t * n_sqz)
+
+  if x_mask is not None:
+    x_mask = x_mask.unsqueeze(-1).repeat(1, 1, 1, n_sqz).view(b, 1, t * n_sqz)
+  else:
+    x_mask = torch.ones(b, 1, t * n_sqz).to(device=x.device, dtype=x.dtype)
+  return x_unsqz * x_mask, x_mask
diff --git a/module/core_vq.py b/module/core_vq.py
new file mode 100644
index 0000000000000000000000000000000000000000..9121f3aaecdef7e72575ad6520c29fd31894e1fa
--- /dev/null
+++ b/module/core_vq.py
@@ -0,0 +1,367 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+#
+# This implementation is inspired from
+# https://github.com/lucidrains/vector-quantize-pytorch
+# which is released under MIT License. Hereafter, the original license:
+# MIT License
+#
+# Copyright (c) 2020 Phil Wang
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in all
+# copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+# SOFTWARE.
+
+"""Core vector quantization implementation."""
+import typing as tp
+
+from einops import rearrange, repeat
+import torch
+from torch import nn
+import torch.nn.functional as F
+from tqdm import tqdm
+
+
+def default(val: tp.Any, d: tp.Any) -> tp.Any:
+    return val if val is not None else d
+
+
+def ema_inplace(moving_avg, new, decay: float):
+    moving_avg.data.mul_(decay).add_(new, alpha=(1 - decay))
+
+
+def laplace_smoothing(x, n_categories: int, epsilon: float = 1e-5):
+    return (x + epsilon) / (x.sum() + n_categories * epsilon)
+
+
+def uniform_init(*shape: int):
+    t = torch.empty(shape)
+    nn.init.kaiming_uniform_(t)
+    return t
+
+
+def sample_vectors(samples, num: int):
+    num_samples, device = samples.shape[0], samples.device
+
+    if num_samples >= num:
+        indices = torch.randperm(num_samples, device=device)[:num]
+    else:
+        indices = torch.randint(0, num_samples, (num,), device=device)
+
+    return samples[indices]
+
+
+def kmeans(samples, num_clusters: int, num_iters: int = 10):
+    dim, dtype = samples.shape[-1], samples.dtype
+    max_kmeans_samples = 500
+    samples = samples[:max_kmeans_samples, :]
+    means = sample_vectors(samples, num_clusters)
+
+    print("kmeans start ... ")
+    for _ in tqdm(range(num_iters)):
+        diffs = rearrange(samples, "n d -> n () d") - rearrange(
+            means, "c d -> () c d"
+        )
+        dists = -(diffs ** 2).sum(dim=-1)
+
+        buckets = dists.max(dim=-1).indices
+        bins = torch.bincount(buckets, minlength=num_clusters)
+        zero_mask = bins == 0
+        bins_min_clamped = bins.masked_fill(zero_mask, 1)
+
+        new_means = buckets.new_zeros(num_clusters, dim, dtype=dtype)
+        new_means.scatter_add_(0, repeat(buckets, "n -> n d", d=dim), samples)
+        new_means = new_means / bins_min_clamped[..., None]
+
+        means = torch.where(zero_mask[..., None], means, new_means)
+
+    return means, bins
+
+
+class EuclideanCodebook(nn.Module):
+    """Codebook with Euclidean distance.
+    Args:
+        dim (int): Dimension.
+        codebook_size (int): Codebook size.
+        kmeans_init (bool): Whether to use k-means to initialize the codebooks.
+            If set to true, run the k-means algorithm on the first training batch and use
+            the learned centroids as initialization.
+        kmeans_iters (int): Number of iterations used for k-means algorithm at initialization.
+        decay (float): Decay for exponential moving average over the codebooks.
+        epsilon (float): Epsilon value for numerical stability.
+        threshold_ema_dead_code (int): Threshold for dead code expiration. Replace any codes
+            that have an exponential moving average cluster size less than the specified threshold with
+            randomly selected vector from the current batch.
+    """
+    def __init__(
+        self,
+        dim: int,
+        codebook_size: int,
+        kmeans_init: int = False,
+        kmeans_iters: int = 10,
+        decay: float = 0.99,
+        epsilon: float = 1e-5,
+        threshold_ema_dead_code: int = 2,
+    ):
+        super().__init__()
+        self.decay = decay
+        init_fn: tp.Union[tp.Callable[..., torch.Tensor], tp.Any] = uniform_init if not kmeans_init else torch.zeros
+        embed = init_fn(codebook_size, dim)
+
+        self.codebook_size = codebook_size
+
+        self.kmeans_iters = kmeans_iters
+        self.epsilon = epsilon
+        self.threshold_ema_dead_code = threshold_ema_dead_code
+
+        self.register_buffer("inited", torch.Tensor([not kmeans_init]))
+        self.register_buffer("cluster_size", torch.zeros(codebook_size))
+        self.register_buffer("embed", embed)
+        self.register_buffer("embed_avg", embed.clone())
+
+    @torch.jit.ignore
+    def init_embed_(self, data):
+        if self.inited:
+            return
+
+        embed, cluster_size = kmeans(data, self.codebook_size, self.kmeans_iters)
+        self.embed.data.copy_(embed)
+        self.embed_avg.data.copy_(embed.clone())
+        self.cluster_size.data.copy_(cluster_size)
+        self.inited.data.copy_(torch.Tensor([True]))
+        # Make sure all buffers across workers are in sync after initialization
+        #broadcast_tensors(self.buffers())
+
+    def replace_(self, samples, mask):
+        modified_codebook = torch.where(
+            mask[..., None], sample_vectors(samples, self.codebook_size), self.embed
+        )
+        self.embed.data.copy_(modified_codebook)
+
+    def expire_codes_(self, batch_samples):
+        if self.threshold_ema_dead_code == 0:
+            return
+
+        expired_codes = self.cluster_size < self.threshold_ema_dead_code
+        if not torch.any(expired_codes):
+            return
+
+        batch_samples = rearrange(batch_samples, "... d -> (...) d")
+        self.replace_(batch_samples, mask=expired_codes)
+        #broadcast_tensors(self.buffers())
+
+    def preprocess(self, x):
+        x = rearrange(x, "... d -> (...) d")
+        return x
+
+    def quantize(self, x):
+        embed = self.embed.t()
+        dist = -(
+            x.pow(2).sum(1, keepdim=True)
+            - 2 * x @ embed
+            + embed.pow(2).sum(0, keepdim=True)
+        )
+        embed_ind = dist.max(dim=-1).indices
+        return embed_ind
+
+    def postprocess_emb(self, embed_ind, shape):
+        return embed_ind.view(*shape[:-1])
+
+    def dequantize(self, embed_ind):
+        quantize = F.embedding(embed_ind, self.embed)
+        return quantize
+
+    def encode(self, x):
+        shape = x.shape
+        # pre-process
+        x = self.preprocess(x)
+        # quantize
+        embed_ind = self.quantize(x)
+        # post-process
+        embed_ind = self.postprocess_emb(embed_ind, shape)
+        return embed_ind
+
+    def decode(self, embed_ind):
+        quantize = self.dequantize(embed_ind)
+        return quantize
+
+    def forward(self, x):
+        shape, dtype = x.shape, x.dtype
+        x = self.preprocess(x)
+
+        self.init_embed_(x)
+
+        embed_ind = self.quantize(x)
+        embed_onehot = F.one_hot(embed_ind, self.codebook_size).type(dtype)
+        embed_ind = self.postprocess_emb(embed_ind, shape)
+        quantize = self.dequantize(embed_ind)
+
+        if self.training:
+            # We do the expiry of code at that point as buffers are in sync
+            # and all the workers will take the same decision.
+            self.expire_codes_(x)
+            ema_inplace(self.cluster_size, embed_onehot.sum(0), self.decay)
+            embed_sum = x.t() @ embed_onehot
+            ema_inplace(self.embed_avg, embed_sum.t(), self.decay)
+            cluster_size = (
+                laplace_smoothing(self.cluster_size, self.codebook_size, self.epsilon)
+                * self.cluster_size.sum()
+            )
+            embed_normalized = self.embed_avg / cluster_size.unsqueeze(1)
+            self.embed.data.copy_(embed_normalized)
+
+        return quantize, embed_ind
+
+
+class VectorQuantization(nn.Module):
+    """Vector quantization implementation.
+    Currently supports only euclidean distance.
+    Args:
+        dim (int): Dimension
+        codebook_size (int): Codebook size
+        codebook_dim (int): Codebook dimension. If not defined, uses the specified dimension in dim.
+        decay (float): Decay for exponential moving average over the codebooks.
+        epsilon (float): Epsilon value for numerical stability.
+        kmeans_init (bool): Whether to use kmeans to initialize the codebooks.
+        kmeans_iters (int): Number of iterations used for kmeans initialization.
+        threshold_ema_dead_code (int): Threshold for dead code expiration. Replace any codes
+            that have an exponential moving average cluster size less than the specified threshold with
+            randomly selected vector from the current batch.
+        commitment_weight (float): Weight for commitment loss.
+    """
+    def __init__(
+        self,
+        dim: int,
+        codebook_size: int,
+        codebook_dim: tp.Optional[int] = None,
+        decay: float = 0.99,
+        epsilon: float = 1e-5,
+        kmeans_init: bool = True,
+        kmeans_iters: int = 50,
+        threshold_ema_dead_code: int = 2,
+        commitment_weight: float = 1.,
+    ):
+        super().__init__()
+        _codebook_dim: int = default(codebook_dim, dim)
+
+        requires_projection = _codebook_dim != dim
+        self.project_in = (nn.Linear(dim, _codebook_dim) if requires_projection else nn.Identity())
+        self.project_out = (nn.Linear(_codebook_dim, dim) if requires_projection else nn.Identity())
+
+        self.epsilon = epsilon
+        self.commitment_weight = commitment_weight
+
+        self._codebook = EuclideanCodebook(dim=_codebook_dim, codebook_size=codebook_size,
+                                           kmeans_init=kmeans_init, kmeans_iters=kmeans_iters,
+                                           decay=decay, epsilon=epsilon,
+                                           threshold_ema_dead_code=threshold_ema_dead_code)
+        self.codebook_size = codebook_size
+
+    @property
+    def codebook(self):
+        return self._codebook.embed
+
+    def encode(self, x):
+        x = rearrange(x, "b d n -> b n d")
+        x = self.project_in(x)
+        embed_in = self._codebook.encode(x)
+        return embed_in
+
+    def decode(self, embed_ind):
+        quantize = self._codebook.decode(embed_ind)
+        quantize = self.project_out(quantize)
+        quantize = rearrange(quantize, "b n d -> b d n")
+        return quantize
+
+    def forward(self, x):
+        device = x.device
+        x = rearrange(x, "b d n -> b n d")
+        x = self.project_in(x)
+
+        quantize, embed_ind = self._codebook(x)
+
+        if self.training:
+            quantize = x + (quantize - x).detach()
+
+        loss = torch.tensor([0.0], device=device, requires_grad=self.training)
+
+        if self.training:
+            if self.commitment_weight > 0:
+                commit_loss = F.mse_loss(quantize.detach(), x)
+                loss = loss + commit_loss * self.commitment_weight
+
+        quantize = self.project_out(quantize)
+        quantize = rearrange(quantize, "b n d -> b d n")
+        return quantize, embed_ind, loss
+
+
+class ResidualVectorQuantization(nn.Module):
+    """Residual vector quantization implementation.
+    Follows Algorithm 1. in https://arxiv.org/pdf/2107.03312.pdf
+    """
+    def __init__(self, *, num_quantizers, **kwargs):
+        super().__init__()
+        self.layers = nn.ModuleList(
+            [VectorQuantization(**kwargs) for _ in range(num_quantizers)]
+        )
+
+    def forward(self, x, n_q: tp.Optional[int] = None, layers: tp.Optional[list] = None):
+        quantized_out = 0.0
+        residual = x
+
+        all_losses = []
+        all_indices = []
+        out_quantized = []
+
+        n_q = n_q or len(self.layers)
+
+        for i, layer in enumerate(self.layers[:n_q]):
+            quantized, indices, loss = layer(residual)
+            residual = residual - quantized
+            quantized_out = quantized_out + quantized
+
+            all_indices.append(indices)
+            all_losses.append(loss)
+            if layers and i in layers:
+                out_quantized.append(quantized)
+
+        out_losses, out_indices = map(torch.stack, (all_losses, all_indices))
+        return quantized_out, out_indices, out_losses, out_quantized
+
+    def encode(self, x: torch.Tensor, n_q: tp.Optional[int] = None, st: tp.Optional[int]= None) -> torch.Tensor:
+        residual = x
+        all_indices = []
+        n_q = n_q or len(self.layers)
+        st = st or 0
+        for layer in self.layers[st:n_q]:
+            indices = layer.encode(residual)
+            quantized = layer.decode(indices)
+            residual = residual - quantized
+            all_indices.append(indices)
+        out_indices = torch.stack(all_indices)
+        return out_indices
+
+    def decode(self, q_indices: torch.Tensor, st: int=0) -> torch.Tensor:
+        quantized_out = torch.tensor(0.0, device=q_indices.device)
+        for i, indices in enumerate(q_indices):
+            layer = self.layers[st + i]
+            quantized = layer.decode(indices)
+            quantized_out = quantized_out + quantized
+        return quantized_out
\ No newline at end of file
diff --git a/module/data_utils.py b/module/data_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..ea3fe779882886c61373a1bff0261af41cbd0373
--- /dev/null
+++ b/module/data_utils.py
@@ -0,0 +1,326 @@
+import time,logging
+import os
+import random,traceback
+import numpy as np
+import torch
+import torch.utils.data
+from tqdm import tqdm
+
+from module import commons
+from module.mel_processing import spectrogram_torch
+from text import cleaned_text_to_sequence
+from utils import load_wav_to_torch, load_filepaths_and_text
+import torch.nn.functional as F
+from functools import lru_cache
+import torch
+import requests
+from scipy.io import wavfile
+from io import BytesIO
+# from config import exp_dir
+from my_utils import load_audio
+
+class TextAudioSpeakerLoader(torch.utils.data.Dataset):
+    """
+        1) loads audio, speaker_id, text pairs
+        2) normalizes text and converts them to sequences of integers
+        3) computes spectrograms from audio files.
+    """
+
+    def __init__(self, hparams, val=False):
+        exp_dir=hparams.exp_dir
+        self.path2="%s/2-name2text.txt"%exp_dir
+        self.path4="%s/4-cnhubert"%exp_dir
+        self.path5="%s/5-wav32k"%exp_dir
+        assert os.path.exists(self.path2)
+        assert os.path.exists(self.path4)
+        assert os.path.exists(self.path5)
+        names4=set([name[:-3]for name in list(os.listdir(self.path4))])#去除.pt后缀
+        names5=set(os.listdir(self.path5))
+        self.phoneme_data={}
+        with open(self.path2,"r",encoding="utf8")as f:
+            lines=f.read().strip("\n").split("\n")
+
+        for line in lines:
+            tmp=line.split("\t")
+            if(len(tmp)!=4):continue
+            self.phoneme_data[tmp[0]]=[tmp[1]]
+
+        self.audiopaths_sid_text=list(set(self.phoneme_data)&names4&names5)
+        tmp=self.audiopaths_sid_text
+        leng=len(tmp)
+        min_num=100
+        if(leng<min_num):
+            self.audiopaths_sid_text=[]
+            for _ in range(max(2, int(min_num / leng))):
+                self.audiopaths_sid_text += tmp
+        self.max_wav_value = hparams.max_wav_value
+        self.sampling_rate = hparams.sampling_rate
+        self.filter_length = hparams.filter_length
+        self.hop_length = hparams.hop_length
+        self.win_length = hparams.win_length
+        self.sampling_rate = hparams.sampling_rate
+        self.val = val
+
+        random.seed(1234)
+        random.shuffle(self.audiopaths_sid_text)
+
+        print("phoneme_data_len:", len(self.phoneme_data.keys()))
+        print("wav_data_len:", len(self.audiopaths_sid_text))
+
+        audiopaths_sid_text_new = []
+        lengths = []
+        skipped_phone  = 0
+        skipped_dur   = 0
+        for audiopath in tqdm(self.audiopaths_sid_text):
+            try:
+                phoneme = self.phoneme_data[audiopath][0]
+                phoneme = phoneme.split(' ')
+                phoneme_ids = cleaned_text_to_sequence(phoneme)
+            except Exception:
+                print(f"{audiopath} not in self.phoneme_data !")
+                skipped_phone  += 1
+                continue
+            size=os.path.getsize("%s/%s"%(self.path5,audiopath))
+            duration = size / self.sampling_rate / 2
+            if (54 > duration > 0.6 or self.val):
+                audiopaths_sid_text_new.append([audiopath, phoneme_ids])
+                lengths.append(size // (2 * self.hop_length))
+            else:
+                skipped_dur += 1
+                continue
+        print("skipped_phone: ", skipped_phone, ", skipped_dur: ", skipped_dur)
+        print("total left: ", len(audiopaths_sid_text_new))
+        assert len(audiopaths_sid_text_new)>1#至少能凑够batch size，这里todo
+        self.audiopaths_sid_text = audiopaths_sid_text_new
+        self.lengths = lengths
+
+    def get_audio_text_speaker_pair(self, audiopath_sid_text):
+        audiopath, phoneme_ids = audiopath_sid_text
+        text = torch.FloatTensor(phoneme_ids)
+        try:
+            spec, wav = self.get_audio("%s/%s"%(self.path5,audiopath))
+            with torch.no_grad():
+                ssl = torch.load("%s/%s.pt"%(self.path4,audiopath),map_location="cpu")
+                if(ssl.shape[-1]!=spec.shape[-1]):
+                    typee=ssl.dtype
+                    ssl=F.pad(ssl.float(),(0,1),mode="replicate").to(typee)
+                ssl.requires_grad=False
+        except:
+            traceback.print_exc()
+            spec = torch.zeros(1025, 100)
+            wav = torch.zeros(1, 100*self.hop_length)
+            ssl=torch.zeros(1,768,100)
+            text=text[-1:]
+            print("load audio or ssl error!!!!!!", audiopath)
+        # print(ssl.requires_grad,spec.requires_grad,wav.requires_grad,text.requires_grad)
+        return (ssl, spec, wav, text)
+
+    def get_audio(self, filename):
+        audio_array = load_audio(filename,self.sampling_rate)#load_audio的方法是已经归一化到-1~1之间的，不用再/32768
+        # print(filename,audio_array.max(),audio_array.min(),audio_array.mean())
+        audio=torch.FloatTensor(audio_array)#/32768
+        audio_norm = audio
+        audio_norm = audio_norm.unsqueeze(0)
+        spec = spectrogram_torch(audio_norm, self.filter_length,self.sampling_rate, self.hop_length, self.win_length,center=False)
+        spec = torch.squeeze(spec, 0)
+        return spec, audio_norm
+
+    def get_sid(self, sid):
+        sid = torch.LongTensor([int(sid)])
+        return sid
+
+    def __getitem__(self, index):
+        # with torch.no_grad():
+            return self.get_audio_text_speaker_pair(self.audiopaths_sid_text[index])
+
+    def __len__(self):
+        return len(self.audiopaths_sid_text)
+
+    def random_slice(self, ssl, wav, mel):
+        assert abs(ssl.shape[-1]- wav.shape[-1]//self.hop_length) < 3, ("first", ssl.shape, wav.shape)
+
+        len_mel = mel.shape[1]
+        if self.val:
+            reference_mel = mel[:, :len_mel//3]
+            return reference_mel, ssl, wav, mel
+        dir = random.randint(0, 1)
+        sep_point = random.randint(int(len_mel//3), int(len_mel//3*2))
+
+        if dir == 0:
+            reference_mel = mel[:, :sep_point]
+            ssl = ssl[:, :, sep_point:]
+            wav2 = wav[:, sep_point*self.hop_length:]
+            mel = mel[:, sep_point:]
+        else:
+            reference_mel = mel[:, sep_point:]
+            ssl = ssl[:, :, :sep_point]
+            wav2 = wav[:, :sep_point*self.hop_length]
+            mel = mel[:, :sep_point]
+
+        assert abs(ssl.shape[-1]- wav2.shape[-1]//self.hop_length) < 3, (ssl.shape, wav.shape,wav2.shape, mel.shape, sep_point,self.hop_length, sep_point*self.hop_length, dir)
+        return reference_mel, ssl, wav2, mel
+
+
+class TextAudioSpeakerCollate():
+    """ Zero-pads model inputs and targets
+    """
+
+    def __init__(self, return_ids=False):
+        self.return_ids = return_ids
+
+    def __call__(self, batch):
+        """Collate's training batch from normalized text, audio and speaker identities
+        PARAMS
+        ------
+        batch: [text_normalized, spec_normalized, wav_normalized, sid]
+        """
+        # Right zero-pad all one-hot text sequences to max input length
+        _, ids_sorted_decreasing = torch.sort(
+            torch.LongTensor([x[1].size(1) for x in batch]),
+            dim=0, descending=True)
+
+        max_ssl_len = max([x[0].size(2) for x in batch])
+        max_ssl_len = int(2 * ((max_ssl_len // 2) + 1))
+        max_spec_len = max([x[1].size(1) for x in batch])
+        max_spec_len = int(2 * ((max_spec_len // 2) + 1))
+        max_wav_len = max([x[2].size(1) for x in batch])
+        max_text_len = max([x[3].size(0) for x in batch])
+
+        ssl_lengths = torch.LongTensor(len(batch))
+        spec_lengths = torch.LongTensor(len(batch))
+        wav_lengths = torch.LongTensor(len(batch))
+        text_lengths = torch.LongTensor(len(batch))
+
+        spec_padded = torch.FloatTensor(len(batch), batch[0][1].size(0), max_spec_len)
+        wav_padded = torch.FloatTensor(len(batch), 1, max_wav_len)
+        ssl_padded = torch.FloatTensor(len(batch), batch[0][0].size(1), max_ssl_len)
+        text_padded = torch.LongTensor(len(batch),  max_text_len)
+
+        spec_padded.zero_()
+        wav_padded.zero_()
+        ssl_padded.zero_()
+        text_padded.zero_()
+
+        for i in range(len(ids_sorted_decreasing)):
+            row = batch[ids_sorted_decreasing[i]]
+
+            ssl = row[0]
+            ssl_padded[i, :, :ssl.size(2)] = ssl[0, :, :]
+            ssl_lengths[i] = ssl.size(2)
+
+            spec = row[1]
+            spec_padded[i, :, :spec.size(1)] = spec
+            spec_lengths[i] = spec.size(1)
+
+            wav = row[2]
+            wav_padded[i, :, :wav.size(1)] = wav
+            wav_lengths[i] = wav.size(1)
+
+            text = row[3]
+            text_padded[i, :text.size(0)] = text
+            text_lengths[i] = text.size(0)
+
+
+        return ssl_padded, ssl_lengths, spec_padded, spec_lengths, wav_padded, wav_lengths, text_padded, text_lengths
+
+
+class DistributedBucketSampler(torch.utils.data.distributed.DistributedSampler):
+    """
+    Maintain similar input lengths in a batch.
+    Length groups are specified by boundaries.
+    Ex) boundaries = [b1, b2, b3] -> any batch is included either {x | b1 < length(x) <=b2} or {x | b2 < length(x) <= b3}.
+
+    It removes samples which are not included in the boundaries.
+    Ex) boundaries = [b1, b2, b3] -> any x s.t. length(x) <= b1 or length(x) > b3 are discarded.
+    """
+
+    def __init__(self, dataset, batch_size, boundaries, num_replicas=None, rank=None, shuffle=True):
+        super().__init__(dataset, num_replicas=num_replicas, rank=rank, shuffle=shuffle)
+        self.lengths = dataset.lengths
+        # print(233333333333333,self.lengths,dir(dataset))
+        self.batch_size = batch_size
+        self.boundaries = boundaries
+
+        self.buckets, self.num_samples_per_bucket = self._create_buckets()
+        self.total_size = sum(self.num_samples_per_bucket)
+        self.num_samples = self.total_size // self.num_replicas
+
+    def _create_buckets(self):
+        buckets = [[] for _ in range(len(self.boundaries) - 1)]
+        for i in range(len(self.lengths)):
+            length = self.lengths[i]
+            idx_bucket = self._bisect(length)
+            if idx_bucket != -1:
+                buckets[idx_bucket].append(i)
+
+        for i in range(len(buckets) - 1, 0, -1):
+        # for i in range(len(buckets) - 1, -1, -1):
+            if len(buckets[i]) == 0:
+                buckets.pop(i)
+                self.boundaries.pop(i + 1)
+
+        num_samples_per_bucket = []
+        for i in range(len(buckets)):
+            len_bucket = len(buckets[i])
+            total_batch_size = self.num_replicas * self.batch_size
+            rem = (total_batch_size - (len_bucket % total_batch_size)) % total_batch_size
+            num_samples_per_bucket.append(len_bucket + rem)
+        return buckets, num_samples_per_bucket
+
+    def __iter__(self):
+        # deterministically shuffle based on epoch
+        g = torch.Generator()
+        g.manual_seed(self.epoch)
+
+        indices = []
+        if self.shuffle:
+            for bucket in self.buckets:
+                indices.append(torch.randperm(len(bucket), generator=g).tolist())
+        else:
+            for bucket in self.buckets:
+                indices.append(list(range(len(bucket))))
+
+        batches = []
+        for i in range(len(self.buckets)):
+            bucket = self.buckets[i]
+            len_bucket = len(bucket)
+            ids_bucket = indices[i]
+            num_samples_bucket = self.num_samples_per_bucket[i]
+
+            # add extra samples to make it evenly divisible
+            rem = num_samples_bucket - len_bucket
+            ids_bucket = ids_bucket + ids_bucket * (rem // len_bucket) + ids_bucket[:(rem % len_bucket)]
+
+            # subsample
+            ids_bucket = ids_bucket[self.rank::self.num_replicas]
+
+            # batching
+            for j in range(len(ids_bucket) // self.batch_size):
+                batch = [bucket[idx] for idx in ids_bucket[j * self.batch_size:(j + 1) * self.batch_size]]
+                batches.append(batch)
+
+        if self.shuffle:
+            batch_ids = torch.randperm(len(batches), generator=g).tolist()
+            batches = [batches[i] for i in batch_ids]
+        self.batches = batches
+
+        assert len(self.batches) * self.batch_size == self.num_samples
+        return iter(self.batches)
+
+    def _bisect(self, x, lo=0, hi=None):
+        if hi is None:
+            hi = len(self.boundaries) - 1
+
+        if hi > lo:
+            mid = (hi + lo) // 2
+            if self.boundaries[mid] < x and x <= self.boundaries[mid + 1]:
+                return mid
+            elif x <= self.boundaries[mid]:
+                return self._bisect(x, lo, mid)
+            else:
+                return self._bisect(x, mid + 1, hi)
+        else:
+            return -1
+
+    def __len__(self):
+        return self.num_samples // self.batch_size
diff --git a/module/losses.py b/module/losses.py
new file mode 100644
index 0000000000000000000000000000000000000000..50fdf854a1826513cb9cbe99522494a1d41c7cc3
--- /dev/null
+++ b/module/losses.py
@@ -0,0 +1,68 @@
+import math
+
+import torch
+from torch.nn import functional as F
+
+
+def feature_loss(fmap_r, fmap_g):
+  loss = 0
+  for dr, dg in zip(fmap_r, fmap_g):
+    for rl, gl in zip(dr, dg):
+      rl = rl.float().detach()
+      gl = gl.float()
+      loss += torch.mean(torch.abs(rl - gl))
+
+  return loss * 2 
+
+
+def discriminator_loss(disc_real_outputs, disc_generated_outputs):
+  loss = 0
+  r_losses = []
+  g_losses = []
+  for dr, dg in zip(disc_real_outputs, disc_generated_outputs):
+    dr = dr.float()
+    dg = dg.float()
+    r_loss = torch.mean((1-dr)**2)
+    g_loss = torch.mean(dg**2)
+    loss += (r_loss + g_loss)
+    r_losses.append(r_loss.item())
+    g_losses.append(g_loss.item())
+
+  return loss, r_losses, g_losses
+
+
+def generator_loss(disc_outputs):
+  loss = 0
+  gen_losses = []
+  for dg in disc_outputs:
+    dg = dg.float()
+    l = torch.mean((1-dg)**2)
+    gen_losses.append(l)
+    loss += l
+
+  return loss, gen_losses
+
+
+def kl_loss(z_p, logs_q, m_p, logs_p, z_mask):
+  """
+  z_p, logs_q: [b, h, t_t]
+  m_p, logs_p: [b, h, t_t]
+  """
+  z_p = z_p.float()
+  logs_q = logs_q.float()
+  m_p = m_p.float()
+  logs_p = logs_p.float()
+  z_mask = z_mask.float()
+
+  kl = logs_p - logs_q - 0.5
+  kl += 0.5 * ((z_p - m_p)**2) * torch.exp(-2. * logs_p)
+  kl = torch.sum(kl * z_mask)
+  l = kl / torch.sum(z_mask)
+  return l
+
+def mle_loss(z, m, logs, logdet, mask):
+  l = torch.sum(logs) + 0.5 * torch.sum(torch.exp(-2 * logs) * ((z - m)**2)) # neg normal likelihood w/o the constant term
+  l = l - torch.sum(logdet) # log jacobian determinant
+  l = l / torch.sum(torch.ones_like(z) * mask) # averaging across batch, channel and time axes
+  l = l + 0.5 * math.log(2 * math.pi) # add the remaining constant term
+  return l
\ No newline at end of file
diff --git a/module/mel_processing.py b/module/mel_processing.py
new file mode 100644
index 0000000000000000000000000000000000000000..0ef5608d8eaf14b442386384929f274ec7d61762
--- /dev/null
+++ b/module/mel_processing.py
@@ -0,0 +1,111 @@
+import math
+import os
+import random
+import torch
+from torch import nn
+import torch.nn.functional as F
+import torch.utils.data
+import numpy as np
+import librosa
+import librosa.util as librosa_util
+from librosa.util import normalize, pad_center, tiny
+from scipy.signal import get_window
+from scipy.io.wavfile import read
+from librosa.filters import mel as librosa_mel_fn
+
+MAX_WAV_VALUE = 32768.0
+
+
+def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
+    """
+    PARAMS
+    ------
+    C: compression factor
+    """
+    return torch.log(torch.clamp(x, min=clip_val) * C)
+
+
+def dynamic_range_decompression_torch(x, C=1):
+    """
+    PARAMS
+    ------
+    C: compression factor used to compress
+    """
+    return torch.exp(x) / C
+
+
+def spectral_normalize_torch(magnitudes):
+    output = dynamic_range_compression_torch(magnitudes)
+    return output
+
+
+def spectral_de_normalize_torch(magnitudes):
+    output = dynamic_range_decompression_torch(magnitudes)
+    return output
+
+
+mel_basis = {}
+hann_window = {}
+
+
+def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center=False):
+    if torch.min(y) < -1.:
+        print('min value is ', torch.min(y))
+    if torch.max(y) > 1.:
+        print('max value is ', torch.max(y))
+
+    global hann_window
+    dtype_device = str(y.dtype) + '_' + str(y.device)
+    wnsize_dtype_device = str(win_size) + '_' + dtype_device
+    if wnsize_dtype_device not in hann_window:
+        hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(dtype=y.dtype, device=y.device)
+
+    y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft-hop_size)/2), int((n_fft-hop_size)/2)), mode='reflect')
+    y = y.squeeze(1)
+    spec = torch.stft(y, n_fft, hop_length=hop_size, win_length=win_size, window=hann_window[wnsize_dtype_device],
+                      center=center, pad_mode='reflect', normalized=False, onesided=True, return_complex=False)
+
+    spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
+    return spec
+
+
+def spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax):
+    global mel_basis
+    dtype_device = str(spec.dtype) + '_' + str(spec.device)
+    fmax_dtype_device = str(fmax) + '_' + dtype_device
+    if fmax_dtype_device not in mel_basis:
+        mel = librosa_mel_fn(sr=sampling_rate, n_fft=n_fft, n_mels=num_mels, fmin=fmin, fmax=fmax)
+        mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(dtype=spec.dtype, device=spec.device)
+    spec = torch.matmul(mel_basis[fmax_dtype_device], spec)
+    spec = spectral_normalize_torch(spec)
+    return spec
+
+
+def mel_spectrogram_torch(y, n_fft, num_mels, sampling_rate, hop_size, win_size, fmin, fmax, center=False):
+    if torch.min(y) < -1.:
+        print('min value is ', torch.min(y))
+    if torch.max(y) > 1.:
+        print('max value is ', torch.max(y))
+
+    global mel_basis, hann_window
+    dtype_device = str(y.dtype) + '_' + str(y.device)
+    fmax_dtype_device = str(fmax) + '_' + dtype_device
+    wnsize_dtype_device = str(win_size) + '_' + dtype_device
+    if fmax_dtype_device not in mel_basis:
+        mel = librosa_mel_fn(sr=sampling_rate, n_fft=n_fft, n_mels=num_mels, fmin=fmin, fmax=fmax)
+        mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(dtype=y.dtype, device=y.device)
+    if wnsize_dtype_device not in hann_window:
+        hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(dtype=y.dtype, device=y.device)
+
+    y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft-hop_size)/2), int((n_fft-hop_size)/2)), mode='reflect')
+    y = y.squeeze(1)
+
+    spec = torch.stft(y, n_fft, hop_length=hop_size, win_length=win_size, window=hann_window[wnsize_dtype_device],
+                      center=center, pad_mode='reflect', normalized=False, onesided=True, return_complex=False)
+
+    spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
+
+    spec = torch.matmul(mel_basis[fmax_dtype_device], spec)
+    spec = spectral_normalize_torch(spec)
+
+    return spec
diff --git a/module/models.py b/module/models.py
new file mode 100644
index 0000000000000000000000000000000000000000..2361b6485355f72441ba945c93edb029c21c2782
--- /dev/null
+++ b/module/models.py
@@ -0,0 +1,784 @@
+import copy
+import math
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+from module import commons
+from module import modules
+from module import attentions
+
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
+from module.commons import init_weights, get_padding
+from module.mrte_model import MRTE
+from module.quantize import  ResidualVectorQuantizer
+from text import symbols
+from torch.cuda.amp import autocast
+
+class StochasticDurationPredictor(nn.Module):
+    def __init__(self, in_channels, filter_channels, kernel_size, p_dropout, n_flows=4, gin_channels=0):
+        super().__init__()
+        filter_channels = in_channels  # it needs to be removed from future version.
+        self.in_channels = in_channels
+        self.filter_channels = filter_channels
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.n_flows = n_flows
+        self.gin_channels = gin_channels
+
+        self.log_flow = modules.Log()
+        self.flows = nn.ModuleList()
+        self.flows.append(modules.ElementwiseAffine(2))
+        for i in range(n_flows):
+            self.flows.append(modules.ConvFlow(2, filter_channels, kernel_size, n_layers=3))
+            self.flows.append(modules.Flip())
+
+        self.post_pre = nn.Conv1d(1, filter_channels, 1)
+        self.post_proj = nn.Conv1d(filter_channels, filter_channels, 1)
+        self.post_convs = modules.DDSConv(filter_channels, kernel_size, n_layers=3, p_dropout=p_dropout)
+        self.post_flows = nn.ModuleList()
+        self.post_flows.append(modules.ElementwiseAffine(2))
+        for i in range(4):
+            self.post_flows.append(modules.ConvFlow(2, filter_channels, kernel_size, n_layers=3))
+            self.post_flows.append(modules.Flip())
+
+        self.pre = nn.Conv1d(in_channels, filter_channels, 1)
+        self.proj = nn.Conv1d(filter_channels, filter_channels, 1)
+        self.convs = modules.DDSConv(filter_channels, kernel_size, n_layers=3, p_dropout=p_dropout)
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, filter_channels, 1)
+
+    def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scale=1.0):
+        x = torch.detach(x)
+        x = self.pre(x)
+        if g is not None:
+            g = torch.detach(g)
+            x = x + self.cond(g)
+        x = self.convs(x, x_mask)
+        x = self.proj(x) * x_mask
+
+        if not reverse:
+            flows = self.flows
+            assert w is not None
+
+            logdet_tot_q = 0
+            h_w = self.post_pre(w)
+            h_w = self.post_convs(h_w, x_mask)
+            h_w = self.post_proj(h_w) * x_mask
+            e_q = torch.randn(w.size(0), 2, w.size(2)).to(device=x.device, dtype=x.dtype) * x_mask
+            z_q = e_q
+            for flow in self.post_flows:
+                z_q, logdet_q = flow(z_q, x_mask, g=(x + h_w))
+                logdet_tot_q += logdet_q
+            z_u, z1 = torch.split(z_q, [1, 1], 1)
+            u = torch.sigmoid(z_u) * x_mask
+            z0 = (w - u) * x_mask
+            logdet_tot_q += torch.sum((F.logsigmoid(z_u) + F.logsigmoid(-z_u)) * x_mask, [1, 2])
+            logq = torch.sum(-0.5 * (math.log(2 * math.pi) + (e_q ** 2)) * x_mask, [1, 2]) - logdet_tot_q
+
+            logdet_tot = 0
+            z0, logdet = self.log_flow(z0, x_mask)
+            logdet_tot += logdet
+            z = torch.cat([z0, z1], 1)
+            for flow in flows:
+                z, logdet = flow(z, x_mask, g=x, reverse=reverse)
+                logdet_tot = logdet_tot + logdet
+            nll = torch.sum(0.5 * (math.log(2 * math.pi) + (z ** 2)) * x_mask, [1, 2]) - logdet_tot
+            return nll + logq  # [b]
+        else:
+            flows = list(reversed(self.flows))
+            flows = flows[:-2] + [flows[-1]]  # remove a useless vflow
+            z = torch.randn(x.size(0), 2, x.size(2)).to(device=x.device, dtype=x.dtype) * noise_scale
+            for flow in flows:
+                z = flow(z, x_mask, g=x, reverse=reverse)
+            z0, z1 = torch.split(z, [1, 1], 1)
+            logw = z0
+            return logw
+
+
+class DurationPredictor(nn.Module):
+    def __init__(self, in_channels, filter_channels, kernel_size, p_dropout, gin_channels=0):
+        super().__init__()
+
+        self.in_channels = in_channels
+        self.filter_channels = filter_channels
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.gin_channels = gin_channels
+
+        self.drop = nn.Dropout(p_dropout)
+        self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size, padding=kernel_size // 2)
+        self.norm_1 = modules.LayerNorm(filter_channels)
+        self.conv_2 = nn.Conv1d(filter_channels, filter_channels, kernel_size, padding=kernel_size // 2)
+        self.norm_2 = modules.LayerNorm(filter_channels)
+        self.proj = nn.Conv1d(filter_channels, 1, 1)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, in_channels, 1)
+
+    def forward(self, x, x_mask, g=None):
+        x = torch.detach(x)
+        if g is not None:
+            g = torch.detach(g)
+            x = x + self.cond(g)
+        x = self.conv_1(x * x_mask)
+        x = torch.relu(x)
+        x = self.norm_1(x)
+        x = self.drop(x)
+        x = self.conv_2(x * x_mask)
+        x = torch.relu(x)
+        x = self.norm_2(x)
+        x = self.drop(x)
+        x = self.proj(x * x_mask)
+        return x * x_mask
+
+
+class TextEncoder(nn.Module):
+    def __init__(self,
+                 out_channels,
+                 hidden_channels,
+                 filter_channels,
+                 n_heads,
+                 n_layers,
+                 kernel_size,
+                 p_dropout,
+                 latent_channels=192):
+        super().__init__()
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.latent_channels = latent_channels
+
+        self.ssl_proj = nn.Conv1d(768, hidden_channels, 1)
+
+        self.encoder_ssl = attentions.Encoder(
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers//2,
+            kernel_size,
+            p_dropout)
+
+        self.encoder_text = attentions.Encoder(
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout)
+        self.text_embedding = nn.Embedding(len(symbols), hidden_channels)
+
+        self.mrte = MRTE()
+
+        self.encoder2 = attentions.Encoder(
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers//2,
+            kernel_size,
+            p_dropout)
+
+
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, y, y_lengths, text, text_lengths, ge, test=None):
+        y_mask = torch.unsqueeze(commons.sequence_mask(y_lengths, y.size(2)), 1).to(y.dtype)
+
+        y = self.ssl_proj(y * y_mask) * y_mask
+        y = self.encoder_ssl(y * y_mask, y_mask)
+
+        text_mask = torch.unsqueeze(commons.sequence_mask(text_lengths, text.size(1)), 1).to(y.dtype)
+        if test == 1 :
+            text[:, :] = 0
+        text = self.text_embedding(text).transpose(1, 2)
+        text = self.encoder_text(text * text_mask, text_mask)
+        y = self.mrte(y, y_mask, text, text_mask, ge)
+
+        y = self.encoder2(y * y_mask, y_mask)
+
+        stats = self.proj(y) * y_mask
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        return y, m, logs, y_mask
+
+    def extract_latent(self, x):
+        x = self.ssl_proj(x)
+        quantized, codes, commit_loss, quantized_list = self.quantizer(x)
+        return codes.transpose(0,1)
+    def decode_latent(self, codes, y_mask, refer,refer_mask, ge):
+
+        quantized = self.quantizer.decode(codes)
+
+        y = self.vq_proj(quantized) * y_mask
+        y = self.encoder_ssl(y * y_mask, y_mask)
+
+        y = self.mrte(y, y_mask, refer, refer_mask, ge)
+
+        y = self.encoder2(y * y_mask, y_mask)
+
+        stats = self.proj(y) * y_mask
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        return y, m, logs, y_mask, quantized
+
+class ResidualCouplingBlock(nn.Module):
+    def __init__(self,
+                 channels,
+                 hidden_channels,
+                 kernel_size,
+                 dilation_rate,
+                 n_layers,
+                 n_flows=4,
+                 gin_channels=0):
+        super().__init__()
+        self.channels = channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.n_flows = n_flows
+        self.gin_channels = gin_channels
+
+        self.flows = nn.ModuleList()
+        for i in range(n_flows):
+            self.flows.append(
+                modules.ResidualCouplingLayer(channels, hidden_channels, kernel_size, dilation_rate, n_layers,
+                                              gin_channels=gin_channels, mean_only=True))
+            self.flows.append(modules.Flip())
+
+    def forward(self, x, x_mask, g=None, reverse=False):
+        if not reverse:
+            for flow in self.flows:
+                x, _ = flow(x, x_mask, g=g, reverse=reverse)
+        else:
+            for flow in reversed(self.flows):
+                x = flow(x, x_mask, g=g, reverse=reverse)
+        return x
+
+
+class PosteriorEncoder(nn.Module):
+    def __init__(self,
+                 in_channels,
+                 out_channels,
+                 hidden_channels,
+                 kernel_size,
+                 dilation_rate,
+                 n_layers,
+                 gin_channels=0):
+        super().__init__()
+        self.in_channels = in_channels
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.gin_channels = gin_channels
+
+        self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+        self.enc = modules.WN(hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=gin_channels)
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, x, x_lengths, g=None):
+        if(g!=None):
+            g = g.detach()
+        x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(x.dtype)
+        x = self.pre(x) * x_mask
+        x = self.enc(x, x_mask, g=g)
+        stats = self.proj(x) * x_mask
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
+        return z, m, logs, x_mask
+
+
+class WNEncoder(nn.Module):
+    def __init__(self,
+                 in_channels,
+                 out_channels,
+                 hidden_channels,
+                 kernel_size,
+                 dilation_rate,
+                 n_layers,
+                 gin_channels=0):
+        super().__init__()
+        self.in_channels = in_channels
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.gin_channels = gin_channels
+
+        self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+        self.enc = modules.WN(hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=gin_channels)
+        self.proj = nn.Conv1d(hidden_channels, out_channels, 1)
+        self.norm = modules.LayerNorm(out_channels)
+    def forward(self, x, x_lengths, g=None):
+        x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(x.dtype)
+        x = self.pre(x) * x_mask
+        x = self.enc(x, x_mask, g=g)
+        out = self.proj(x) * x_mask
+        out = self.norm(out)
+        return out
+
+
+class Generator(torch.nn.Module):
+    def __init__(self, initial_channel, resblock, resblock_kernel_sizes, resblock_dilation_sizes, upsample_rates,
+                 upsample_initial_channel, upsample_kernel_sizes, gin_channels=0):
+        super(Generator, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+        self.conv_pre = Conv1d(initial_channel, upsample_initial_channel, 7, 1, padding=3)
+        resblock = modules.ResBlock1 if resblock == '1' else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            self.ups.append(weight_norm(
+                ConvTranspose1d(upsample_initial_channel // (2 ** i), upsample_initial_channel // (2 ** (i + 1)),
+                                k, u, padding=(k - u) // 2)))
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel // (2 ** (i + 1))
+            for j, (k, d) in enumerate(zip(resblock_kernel_sizes, resblock_dilation_sizes)):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+    def forward(self, x, g=None):
+        x = self.conv_pre(x)
+        if g is not None:
+            x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i * self.num_kernels + j](x)
+                else:
+                    xs += self.resblocks[i * self.num_kernels + j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+
+        return x
+
+    def remove_weight_norm(self):
+        print('Removing weight norm...')
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+class DiscriminatorP(torch.nn.Module):
+    def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
+        super(DiscriminatorP, self).__init__()
+        self.period = period
+        self.use_spectral_norm = use_spectral_norm
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList([
+            norm_f(Conv2d(1, 32, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
+            norm_f(Conv2d(32, 128, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
+            norm_f(Conv2d(128, 512, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
+            norm_f(Conv2d(512, 1024, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
+            norm_f(Conv2d(1024, 1024, (kernel_size, 1), 1, padding=(get_padding(kernel_size, 1), 0))),
+        ])
+        self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
+
+    def forward(self, x):
+        fmap = []
+
+        # 1d to 2d
+        b, c, t = x.shape
+        if t % self.period != 0:  # pad first
+            n_pad = self.period - (t % self.period)
+            x = F.pad(x, (0, n_pad), "reflect")
+            t = t + n_pad
+        x = x.view(b, c, t // self.period, self.period)
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
+
+
+class DiscriminatorS(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(DiscriminatorS, self).__init__()
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList([
+            norm_f(Conv1d(1, 16, 15, 1, padding=7)),
+            norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
+            norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
+            norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
+            norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
+            norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
+        ])
+        self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
+
+    def forward(self, x):
+        fmap = []
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
+
+
+class MultiPeriodDiscriminator(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminator, self).__init__()
+        periods = [2, 3, 5, 7, 11]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+class ReferenceEncoder(nn.Module):
+    '''
+    inputs --- [N, Ty/r, n_mels*r]  mels
+    outputs --- [N, ref_enc_gru_size]
+    '''
+
+    def __init__(self, spec_channels, gin_channels=0):
+
+        super().__init__()
+        self.spec_channels = spec_channels
+        ref_enc_filters = [32, 32, 64, 64, 128, 128]
+        K = len(ref_enc_filters)
+        filters = [1] + ref_enc_filters
+        convs = [weight_norm(nn.Conv2d(in_channels=filters[i],
+                                       out_channels=filters[i + 1],
+                                       kernel_size=(3, 3),
+                                       stride=(2, 2),
+                                       padding=(1, 1))) for i in range(K)]
+        self.convs = nn.ModuleList(convs)
+        # self.wns = nn.ModuleList([weight_norm(num_features=ref_enc_filters[i]) for i in range(K)])
+
+        out_channels = self.calculate_channels(spec_channels, 3, 2, 1, K)
+        self.gru = nn.GRU(input_size=ref_enc_filters[-1] * out_channels,
+                          hidden_size=256 // 2,
+                          batch_first=True)
+        self.proj = nn.Linear(128, gin_channels)
+
+    def forward(self, inputs):
+        N = inputs.size(0)
+        out = inputs.view(N, 1, -1, self.spec_channels)  # [N, 1, Ty, n_freqs]
+        for conv in self.convs:
+            out = conv(out)
+            # out = wn(out)
+            out = F.relu(out)  # [N, 128, Ty//2^K, n_mels//2^K]
+
+        out = out.transpose(1, 2)  # [N, Ty//2^K, 128, n_mels//2^K]
+        T = out.size(1)
+        N = out.size(0)
+        out = out.contiguous().view(N, T, -1)  # [N, Ty//2^K, 128*n_mels//2^K]
+
+        self.gru.flatten_parameters()
+        memory, out = self.gru(out)  # out --- [1, N, 128]
+
+        return self.proj(out.squeeze(0)).unsqueeze(-1)
+
+    def calculate_channels(self, L, kernel_size, stride, pad, n_convs):
+        for i in range(n_convs):
+            L = (L - kernel_size + 2 * pad) // stride + 1
+        return L
+
+
+class Quantizer_module(torch.nn.Module):
+    def __init__(self, n_e, e_dim):
+        super(Quantizer_module, self).__init__()
+        self.embedding = nn.Embedding(n_e, e_dim)
+        self.embedding.weight.data.uniform_(-1.0 / n_e, 1.0 / n_e)
+
+    def forward(self, x):
+        d = torch.sum(x ** 2, 1, keepdim=True) + torch.sum(self.embedding.weight ** 2, 1) - 2 * torch.matmul(x, self.embedding.weight.T)
+        min_indicies = torch.argmin(d, 1)
+        z_q = self.embedding(min_indicies)
+        return z_q, min_indicies
+
+class Quantizer(torch.nn.Module):
+    def __init__(self, embed_dim=512, n_code_groups=4, n_codes=160):
+        super(Quantizer, self).__init__()
+        assert embed_dim % n_code_groups == 0
+        self.quantizer_modules = nn.ModuleList([
+            Quantizer_module(n_codes, embed_dim // n_code_groups) for _ in range(n_code_groups)
+        ])
+        self.n_code_groups = n_code_groups
+        self.embed_dim = embed_dim
+
+    def forward(self, xin):
+        #B, C, T
+        B, C, T = xin.shape
+        xin = xin.transpose(1, 2)
+        x = xin.reshape(-1, self.embed_dim)
+        x = torch.split(x, self.embed_dim // self.n_code_groups, dim=-1)
+        min_indicies = []
+        z_q = []
+        for _x, m in zip(x, self.quantizer_modules):
+            _z_q, _min_indicies = m(_x)
+            z_q.append(_z_q)
+            min_indicies.append(_min_indicies) #B * T,
+        z_q = torch.cat(z_q, -1).reshape(xin.shape)
+        loss = 0.25 * torch.mean((z_q.detach() - xin) ** 2) + torch.mean((z_q - xin.detach()) ** 2)
+        z_q = xin + (z_q - xin).detach()
+        z_q = z_q.transpose(1, 2)
+        codes = torch.stack(min_indicies, -1).reshape(B, T, self.n_code_groups)
+        return z_q, loss, codes.transpose(1, 2)
+
+    def embed(self, x):
+        #idx: N, 4, T
+        x=x.transpose(1, 2)
+        x = torch.split(x, 1, 2)
+        ret = []
+        for q, embed in zip(x, self.quantizer_modules):
+            q = embed.embedding(q.squeeze(-1))
+            ret.append(q)
+        ret = torch.cat(ret, -1)
+        return ret.transpose(1, 2) #N, C, T
+
+
+class CodePredictor(nn.Module):
+    def __init__(self,
+                 hidden_channels,
+                 filter_channels,
+                 n_heads,
+                 n_layers,
+                 kernel_size,
+                 p_dropout,
+                 n_q=8,
+                 dims=1024,
+                 ssl_dim=768
+                 ):
+        super().__init__()
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+
+        self.vq_proj = nn.Conv1d(ssl_dim, hidden_channels, 1)
+        self.ref_enc = modules.MelStyleEncoder(ssl_dim, style_vector_dim=hidden_channels)
+
+        self.encoder = attentions.Encoder(
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout)
+
+        self.out_proj = nn.Conv1d(hidden_channels, (n_q-1) * dims, 1)
+        self.n_q = n_q
+        self.dims = dims
+    def forward(self, x, x_mask, refer, codes, infer=False):
+        x = x.detach()
+        x = self.vq_proj(x * x_mask) * x_mask
+        g = self.ref_enc(refer, x_mask)
+        x = x + g
+        x = self.encoder(x * x_mask, x_mask)
+        x = self.out_proj(x * x_mask) * x_mask
+        logits = x.reshape(x.shape[0], self.n_q - 1, self.dims, x.shape[-1]).transpose(2, 3)
+        target = codes[1:].transpose(0, 1)
+        if not infer:
+            logits = logits.reshape(-1, self.dims)
+            target = target.reshape(-1)
+            loss = torch.nn.functional.cross_entropy(logits, target)
+            return loss
+        else:
+            _, top10_preds = torch.topk(logits, 10, dim=-1)
+            correct_top10 = torch.any(top10_preds == target.unsqueeze(-1), dim=-1)
+            top3_acc = 100 * torch.mean(correct_top10.float()).detach().cpu().item()
+
+            print('Top-10 Accuracy:', top3_acc, "%")
+
+            pred_codes = torch.argmax(logits, dim=-1)
+            acc = 100 * torch.mean((pred_codes == target).float()).detach().cpu().item()
+            print('Top-1 Accuracy:', acc, "%")
+
+            return pred_codes.transpose(0, 1)
+
+
+
+class SynthesizerTrn(nn.Module):
+    """
+  Synthesizer for Training
+  """
+
+    def __init__(self,
+                 spec_channels,
+                 segment_size,
+                 inter_channels,
+                 hidden_channels,
+                 filter_channels,
+                 n_heads,
+                 n_layers,
+                 kernel_size,
+                 p_dropout,
+                 resblock,
+                 resblock_kernel_sizes,
+                 resblock_dilation_sizes,
+                 upsample_rates,
+                 upsample_initial_channel,
+                 upsample_kernel_sizes,
+                 n_speakers=0,
+                 gin_channels=0,
+                 use_sdp=True,
+                 semantic_frame_rate=None,
+                 freeze_quantizer=None,
+                 **kwargs):
+
+        super().__init__()
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.n_speakers = n_speakers
+        self.gin_channels = gin_channels
+
+        self.use_sdp = use_sdp
+        self.enc_p = TextEncoder(
+                                 inter_channels,
+                                 hidden_channels,
+                                 filter_channels,
+                                 n_heads,
+                                 n_layers,
+                                 kernel_size,
+                                 p_dropout)
+        self.dec = Generator(inter_channels, resblock, resblock_kernel_sizes, resblock_dilation_sizes, upsample_rates,
+                             upsample_initial_channel, upsample_kernel_sizes, gin_channels=gin_channels)
+        self.enc_q = PosteriorEncoder(spec_channels, inter_channels, hidden_channels, 5, 1, 16,
+                                      gin_channels=gin_channels)
+        self.flow = ResidualCouplingBlock(inter_channels, hidden_channels, 5, 1, 4, gin_channels=gin_channels)
+
+        self.ref_enc = modules.MelStyleEncoder(spec_channels, style_vector_dim=gin_channels)
+
+        ssl_dim = 768
+        assert semantic_frame_rate in ['25hz', "50hz"]
+        self.semantic_frame_rate = semantic_frame_rate
+        if semantic_frame_rate == '25hz':
+            self.ssl_proj = nn.Conv1d(ssl_dim, ssl_dim, 2, stride=2)
+        else:
+            self.ssl_proj = nn.Conv1d(ssl_dim, ssl_dim, 1, stride=1)
+
+        self.quantizer = ResidualVectorQuantizer(
+            dimension=ssl_dim,
+            n_q=1,
+            bins=1024
+        )
+        if freeze_quantizer:
+            self.ssl_proj.requires_grad_(False)
+            self.quantizer.requires_grad_(False)
+            # self.enc_p.text_embedding.requires_grad_(False)
+            # self.enc_p.encoder_text.requires_grad_(False)
+            # self.enc_p.mrte.requires_grad_(False)
+
+    def forward(self, ssl, y, y_lengths, text, text_lengths):
+        y_mask = torch.unsqueeze(commons.sequence_mask(y_lengths, y.size(2)), 1).to(y.dtype)
+        ge = self.ref_enc(y * y_mask, y_mask)
+
+        with autocast(enabled=False):
+            ssl = self.ssl_proj(ssl)
+            quantized, codes, commit_loss, quantized_list = self.quantizer(ssl, layers=[0])
+
+        if self.semantic_frame_rate == '25hz':
+            quantized = F.interpolate(quantized, size=int(quantized.shape[-1] * 2), mode="nearest")
+
+        x, m_p, logs_p, y_mask = self.enc_p(quantized, y_lengths, text, text_lengths, ge)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=ge)
+        z_p = self.flow(z, y_mask, g=ge)
+
+        z_slice, ids_slice = commons.rand_slice_segments(z, y_lengths, self.segment_size)
+        o = self.dec(z_slice, g=ge)
+        return o, commit_loss, ids_slice, y_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q), quantized
+
+    def infer(self, ssl, y, y_lengths, text, text_lengths, test=None, noise_scale=0.5):
+        y_mask = torch.unsqueeze(commons.sequence_mask(y_lengths, y.size(2)), 1).to(y.dtype)
+        ge = self.ref_enc(y * y_mask, y_mask)
+
+        ssl =  self.ssl_proj(ssl)
+        quantized, codes, commit_loss, _ = self.quantizer(ssl, layers=[0])
+        if self.semantic_frame_rate == '25hz':
+            quantized = F.interpolate(quantized, size=int(quantized.shape[-1] * 2), mode="nearest")
+
+        x, m_p, logs_p, y_mask = self.enc_p(quantized, y_lengths, text, text_lengths, ge, test=test)
+        z_p = m_p + torch.randn_like(m_p) * torch.exp(logs_p) * noise_scale
+
+        z = self.flow(z_p, y_mask, g=ge, reverse=True)
+
+        o = self.dec((z * y_mask)[:, :, :], g=ge)
+        return o,y_mask, (z, z_p, m_p, logs_p)
+
+
+    @torch.no_grad()
+    def decode(self, codes,text, refer, noise_scale=0.5):
+        refer_lengths = torch.LongTensor([refer.size(2)]).to(refer.device)
+        refer_mask = torch.unsqueeze(commons.sequence_mask(refer_lengths, refer.size(2)), 1).to(refer.dtype)
+        ge = self.ref_enc(refer * refer_mask, refer_mask)
+
+        y_lengths = torch.LongTensor([codes.size(2)*2]).to(codes.device)
+        text_lengths = torch.LongTensor([text.size(-1)]).to(text.device)
+
+        quantized = self.quantizer.decode(codes)
+        if self.semantic_frame_rate == '25hz':
+            quantized = F.interpolate(quantized, size=int(quantized.shape[-1] * 2), mode="nearest")
+
+        x, m_p, logs_p, y_mask = self.enc_p(quantized, y_lengths, text, text_lengths, ge)
+        z_p = m_p + torch.randn_like(m_p) * torch.exp(logs_p) * noise_scale
+
+        z = self.flow(z_p, y_mask, g=ge, reverse=True)
+
+        o = self.dec((z * y_mask)[:, :, :], g=ge)
+        return o
+
+    def extract_latent(self, x):
+        ssl =  self.ssl_proj(x)
+        quantized, codes, commit_loss, quantized_list = self.quantizer(ssl)
+        return codes.transpose(0,1)
diff --git a/module/modules.py b/module/modules.py
new file mode 100644
index 0000000000000000000000000000000000000000..711cc5ba43a7e37968895e97ef5ede5f531115d2
--- /dev/null
+++ b/module/modules.py
@@ -0,0 +1,769 @@
+import math
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+from torch.nn import Conv1d
+from torch.nn.utils import weight_norm, remove_weight_norm
+
+from module import commons
+from module.commons import init_weights, get_padding
+from module.transforms import piecewise_rational_quadratic_transform
+import torch.distributions as D
+
+
+LRELU_SLOPE = 0.1
+
+
+class LayerNorm(nn.Module):
+  def __init__(self, channels, eps=1e-5):
+    super().__init__()
+    self.channels = channels
+    self.eps = eps
+
+    self.gamma = nn.Parameter(torch.ones(channels))
+    self.beta = nn.Parameter(torch.zeros(channels))
+
+  def forward(self, x):
+    x = x.transpose(1, -1)
+    x = F.layer_norm(x, (self.channels,), self.gamma, self.beta, self.eps)
+    return x.transpose(1, -1)
+
+ 
+class ConvReluNorm(nn.Module):
+  def __init__(self, in_channels, hidden_channels, out_channels, kernel_size, n_layers, p_dropout):
+    super().__init__()
+    self.in_channels = in_channels
+    self.hidden_channels = hidden_channels
+    self.out_channels = out_channels
+    self.kernel_size = kernel_size
+    self.n_layers = n_layers
+    self.p_dropout = p_dropout
+    assert n_layers > 1, "Number of layers should be larger than 0."
+
+    self.conv_layers = nn.ModuleList()
+    self.norm_layers = nn.ModuleList()
+    self.conv_layers.append(nn.Conv1d(in_channels, hidden_channels, kernel_size, padding=kernel_size//2))
+    self.norm_layers.append(LayerNorm(hidden_channels))
+    self.relu_drop = nn.Sequential(
+        nn.ReLU(),
+        nn.Dropout(p_dropout))
+    for _ in range(n_layers-1):
+      self.conv_layers.append(nn.Conv1d(hidden_channels, hidden_channels, kernel_size, padding=kernel_size//2))
+      self.norm_layers.append(LayerNorm(hidden_channels))
+    self.proj = nn.Conv1d(hidden_channels, out_channels, 1)
+    self.proj.weight.data.zero_()
+    self.proj.bias.data.zero_()
+
+  def forward(self, x, x_mask):
+    x_org = x
+    for i in range(self.n_layers):
+      x = self.conv_layers[i](x * x_mask)
+      x = self.norm_layers[i](x)
+      x = self.relu_drop(x)
+    x = x_org + self.proj(x)
+    return x * x_mask
+
+
+class DDSConv(nn.Module):
+  """
+  Dialted and Depth-Separable Convolution
+  """
+  def __init__(self, channels, kernel_size, n_layers, p_dropout=0.):
+    super().__init__()
+    self.channels = channels
+    self.kernel_size = kernel_size
+    self.n_layers = n_layers
+    self.p_dropout = p_dropout
+
+    self.drop = nn.Dropout(p_dropout)
+    self.convs_sep = nn.ModuleList()
+    self.convs_1x1 = nn.ModuleList()
+    self.norms_1 = nn.ModuleList()
+    self.norms_2 = nn.ModuleList()
+    for i in range(n_layers):
+      dilation = kernel_size ** i
+      padding = (kernel_size * dilation - dilation) // 2
+      self.convs_sep.append(nn.Conv1d(channels, channels, kernel_size, 
+          groups=channels, dilation=dilation, padding=padding
+      ))
+      self.convs_1x1.append(nn.Conv1d(channels, channels, 1))
+      self.norms_1.append(LayerNorm(channels))
+      self.norms_2.append(LayerNorm(channels))
+
+  def forward(self, x, x_mask, g=None):
+    if g is not None:
+      x = x + g
+    for i in range(self.n_layers):
+      y = self.convs_sep[i](x * x_mask)
+      y = self.norms_1[i](y)
+      y = F.gelu(y)
+      y = self.convs_1x1[i](y)
+      y = self.norms_2[i](y)
+      y = F.gelu(y)
+      y = self.drop(y)
+      x = x + y
+    return x * x_mask
+
+
+class WN(torch.nn.Module):
+  def __init__(self, hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=0, p_dropout=0):
+    super(WN, self).__init__()
+    assert(kernel_size % 2 == 1)
+    self.hidden_channels =hidden_channels
+    self.kernel_size = kernel_size,
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+    self.gin_channels = gin_channels
+    self.p_dropout = p_dropout
+
+    self.in_layers = torch.nn.ModuleList()
+    self.res_skip_layers = torch.nn.ModuleList()
+    self.drop = nn.Dropout(p_dropout)
+
+    if gin_channels != 0:
+      cond_layer = torch.nn.Conv1d(gin_channels, 2*hidden_channels*n_layers, 1)
+      self.cond_layer = torch.nn.utils.weight_norm(cond_layer, name='weight')
+
+    for i in range(n_layers):
+      dilation = dilation_rate ** i
+      padding = int((kernel_size * dilation - dilation) / 2)
+      in_layer = torch.nn.Conv1d(hidden_channels, 2*hidden_channels, kernel_size,
+                                 dilation=dilation, padding=padding)
+      in_layer = torch.nn.utils.weight_norm(in_layer, name='weight')
+      self.in_layers.append(in_layer)
+
+      # last one is not necessary
+      if i < n_layers - 1:
+        res_skip_channels = 2 * hidden_channels
+      else:
+        res_skip_channels = hidden_channels
+
+      res_skip_layer = torch.nn.Conv1d(hidden_channels, res_skip_channels, 1)
+      res_skip_layer = torch.nn.utils.weight_norm(res_skip_layer, name='weight')
+      self.res_skip_layers.append(res_skip_layer)
+
+  def forward(self, x, x_mask, g=None, **kwargs):
+    output = torch.zeros_like(x)
+    n_channels_tensor = torch.IntTensor([self.hidden_channels])
+
+    if g is not None:
+      g = self.cond_layer(g)
+
+    for i in range(self.n_layers):
+      x_in = self.in_layers[i](x)
+      if g is not None:
+        cond_offset = i * 2 * self.hidden_channels
+        g_l = g[:,cond_offset:cond_offset+2*self.hidden_channels,:]
+      else:
+        g_l = torch.zeros_like(x_in)
+
+      acts = commons.fused_add_tanh_sigmoid_multiply(
+          x_in,
+          g_l,
+          n_channels_tensor)
+      acts = self.drop(acts)
+
+      res_skip_acts = self.res_skip_layers[i](acts)
+      if i < self.n_layers - 1:
+        res_acts = res_skip_acts[:,:self.hidden_channels,:]
+        x = (x + res_acts) * x_mask
+        output = output + res_skip_acts[:,self.hidden_channels:,:]
+      else:
+        output = output + res_skip_acts
+    return output * x_mask
+
+  def remove_weight_norm(self):
+    if self.gin_channels != 0:
+      torch.nn.utils.remove_weight_norm(self.cond_layer)
+    for l in self.in_layers:
+      torch.nn.utils.remove_weight_norm(l)
+    for l in self.res_skip_layers:
+     torch.nn.utils.remove_weight_norm(l)
+
+
+class ResBlock1(torch.nn.Module):
+    def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
+        super(ResBlock1, self).__init__()
+        self.convs1 = nn.ModuleList([
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[0],
+                               padding=get_padding(kernel_size, dilation[0]))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[1],
+                               padding=get_padding(kernel_size, dilation[1]))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[2],
+                               padding=get_padding(kernel_size, dilation[2])))
+        ])
+        self.convs1.apply(init_weights)
+
+        self.convs2 = nn.ModuleList([
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
+                               padding=get_padding(kernel_size, 1))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
+                               padding=get_padding(kernel_size, 1))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
+                               padding=get_padding(kernel_size, 1)))
+        ])
+        self.convs2.apply(init_weights)
+
+    def forward(self, x, x_mask=None):
+        for c1, c2 in zip(self.convs1, self.convs2):
+            xt = F.leaky_relu(x, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c1(xt)
+            xt = F.leaky_relu(xt, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c2(xt)
+            x = xt + x
+        if x_mask is not None:
+            x = x * x_mask
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.convs1:
+            remove_weight_norm(l)
+        for l in self.convs2:
+            remove_weight_norm(l)
+
+
+class ResBlock2(torch.nn.Module):
+    def __init__(self, channels, kernel_size=3, dilation=(1, 3)):
+        super(ResBlock2, self).__init__()
+        self.convs = nn.ModuleList([
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[0],
+                               padding=get_padding(kernel_size, dilation[0]))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[1],
+                               padding=get_padding(kernel_size, dilation[1])))
+        ])
+        self.convs.apply(init_weights)
+
+    def forward(self, x, x_mask=None):
+        for c in self.convs:
+            xt = F.leaky_relu(x, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c(xt)
+            x = xt + x
+        if x_mask is not None:
+            x = x * x_mask
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.convs:
+            remove_weight_norm(l)
+
+
+class Log(nn.Module):
+  def forward(self, x, x_mask, reverse=False, **kwargs):
+    if not reverse:
+      y = torch.log(torch.clamp_min(x, 1e-5)) * x_mask
+      logdet = torch.sum(-y, [1, 2])
+      return y, logdet
+    else:
+      x = torch.exp(x) * x_mask
+      return x
+    
+
+class Flip(nn.Module):
+  def forward(self, x, *args, reverse=False, **kwargs):
+    x = torch.flip(x, [1])
+    if not reverse:
+      logdet = torch.zeros(x.size(0)).to(dtype=x.dtype, device=x.device)
+      return x, logdet
+    else:
+      return x
+
+
+class ElementwiseAffine(nn.Module):
+  def __init__(self, channels):
+    super().__init__()
+    self.channels = channels
+    self.m = nn.Parameter(torch.zeros(channels,1))
+    self.logs = nn.Parameter(torch.zeros(channels,1))
+
+  def forward(self, x, x_mask, reverse=False, **kwargs):
+    if not reverse:
+      y = self.m + torch.exp(self.logs) * x
+      y = y * x_mask
+      logdet = torch.sum(self.logs * x_mask, [1,2])
+      return y, logdet
+    else:
+      x = (x - self.m) * torch.exp(-self.logs) * x_mask
+      return x
+
+
+class ResidualCouplingLayer(nn.Module):
+  def __init__(self,
+      channels,
+      hidden_channels,
+      kernel_size,
+      dilation_rate,
+      n_layers,
+      p_dropout=0,
+      gin_channels=0,
+      mean_only=False):
+    assert channels % 2 == 0, "channels should be divisible by 2"
+    super().__init__()
+    self.channels = channels
+    self.hidden_channels = hidden_channels
+    self.kernel_size = kernel_size
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+    self.half_channels = channels // 2
+    self.mean_only = mean_only
+
+    self.pre = nn.Conv1d(self.half_channels, hidden_channels, 1)
+    self.enc = WN(hidden_channels, kernel_size, dilation_rate, n_layers, p_dropout=p_dropout, gin_channels=gin_channels)
+    self.post = nn.Conv1d(hidden_channels, self.half_channels * (2 - mean_only), 1)
+    self.post.weight.data.zero_()
+    self.post.bias.data.zero_()
+
+  def forward(self, x, x_mask, g=None, reverse=False):
+    x0, x1 = torch.split(x, [self.half_channels]*2, 1)
+    h = self.pre(x0) * x_mask
+    h = self.enc(h, x_mask, g=g)
+    stats = self.post(h) * x_mask
+    if not self.mean_only:
+      m, logs = torch.split(stats, [self.half_channels]*2, 1)
+    else:
+      m = stats
+      logs = torch.zeros_like(m)
+
+    if not reverse:
+      x1 = m + x1 * torch.exp(logs) * x_mask
+      x = torch.cat([x0, x1], 1)
+      logdet = torch.sum(logs, [1,2])
+      return x, logdet
+    else:
+      x1 = (x1 - m) * torch.exp(-logs) * x_mask
+      x = torch.cat([x0, x1], 1)
+      return x
+
+
+class ConvFlow(nn.Module):
+  def __init__(self, in_channels, filter_channels, kernel_size, n_layers, num_bins=10, tail_bound=5.0):
+    super().__init__()
+    self.in_channels = in_channels
+    self.filter_channels = filter_channels
+    self.kernel_size = kernel_size
+    self.n_layers = n_layers
+    self.num_bins = num_bins
+    self.tail_bound = tail_bound
+    self.half_channels = in_channels // 2
+
+    self.pre = nn.Conv1d(self.half_channels, filter_channels, 1)
+    self.convs = DDSConv(filter_channels, kernel_size, n_layers, p_dropout=0.)
+    self.proj = nn.Conv1d(filter_channels, self.half_channels * (num_bins * 3 - 1), 1)
+    self.proj.weight.data.zero_()
+    self.proj.bias.data.zero_()
+
+  def forward(self, x, x_mask, g=None, reverse=False):
+    x0, x1 = torch.split(x, [self.half_channels]*2, 1)
+    h = self.pre(x0)
+    h = self.convs(h, x_mask, g=g)
+    h = self.proj(h) * x_mask
+
+    b, c, t = x0.shape
+    h = h.reshape(b, c, -1, t).permute(0, 1, 3, 2) # [b, cx?, t] -> [b, c, t, ?]
+
+    unnormalized_widths = h[..., :self.num_bins] / math.sqrt(self.filter_channels)
+    unnormalized_heights = h[..., self.num_bins:2*self.num_bins] / math.sqrt(self.filter_channels)
+    unnormalized_derivatives = h[..., 2 * self.num_bins:]
+
+    x1, logabsdet = piecewise_rational_quadratic_transform(x1,
+        unnormalized_widths,
+        unnormalized_heights,
+        unnormalized_derivatives,
+        inverse=reverse,
+        tails='linear',
+        tail_bound=self.tail_bound
+    )
+
+    x = torch.cat([x0, x1], 1) * x_mask
+    logdet = torch.sum(logabsdet * x_mask, [1,2])
+    if not reverse:
+        return x, logdet
+    else:
+        return x
+
+
+
+class LinearNorm(nn.Module):
+    def __init__(self,
+                 in_channels,
+                 out_channels,
+                 bias=True,
+                 spectral_norm=False,
+                 ):
+        super(LinearNorm, self).__init__()
+        self.fc = nn.Linear(in_channels, out_channels, bias)
+
+        if spectral_norm:
+            self.fc = nn.utils.spectral_norm(self.fc)
+
+    def forward(self, input):
+        out = self.fc(input)
+        return out
+
+
+class Mish(nn.Module):
+    def __init__(self):
+        super(Mish, self).__init__()
+
+    def forward(self, x):
+        return x * torch.tanh(F.softplus(x))
+
+
+class Conv1dGLU(nn.Module):
+    '''
+    Conv1d + GLU(Gated Linear Unit) with residual connection.
+    For GLU refer to https://arxiv.org/abs/1612.08083 paper.
+    '''
+
+    def __init__(self, in_channels, out_channels, kernel_size, dropout):
+        super(Conv1dGLU, self).__init__()
+        self.out_channels = out_channels
+        self.conv1 = ConvNorm(in_channels, 2 * out_channels, kernel_size=kernel_size)
+        self.dropout = nn.Dropout(dropout)
+
+    def forward(self, x):
+        residual = x
+        x = self.conv1(x)
+        x1, x2 = torch.split(x, split_size_or_sections=self.out_channels, dim=1)
+        x = x1 * torch.sigmoid(x2)
+        x = residual + self.dropout(x)
+        return x
+
+
+class ConvNorm(nn.Module):
+    def __init__(self,
+                 in_channels,
+                 out_channels,
+                 kernel_size=1,
+                 stride=1,
+                 padding=None,
+                 dilation=1,
+                 bias=True,
+                 spectral_norm=False,
+                 ):
+        super(ConvNorm, self).__init__()
+
+        if padding is None:
+            assert (kernel_size % 2 == 1)
+            padding = int(dilation * (kernel_size - 1) / 2)
+
+        self.conv = torch.nn.Conv1d(in_channels,
+                                    out_channels,
+                                    kernel_size=kernel_size,
+                                    stride=stride,
+                                    padding=padding,
+                                    dilation=dilation,
+                                    bias=bias)
+
+        if spectral_norm:
+            self.conv = nn.utils.spectral_norm(self.conv)
+
+    def forward(self, input):
+        out = self.conv(input)
+        return out
+
+
+class MultiHeadAttention(nn.Module):
+    ''' Multi-Head Attention module '''
+
+    def __init__(self, n_head, d_model, d_k, d_v, dropout=0., spectral_norm=False):
+        super().__init__()
+
+        self.n_head = n_head
+        self.d_k = d_k
+        self.d_v = d_v
+
+        self.w_qs = nn.Linear(d_model, n_head * d_k)
+        self.w_ks = nn.Linear(d_model, n_head * d_k)
+        self.w_vs = nn.Linear(d_model, n_head * d_v)
+
+        self.attention = ScaledDotProductAttention(temperature=np.power(d_model, 0.5), dropout=dropout)
+
+        self.fc = nn.Linear(n_head * d_v, d_model)
+        self.dropout = nn.Dropout(dropout)
+
+        if spectral_norm:
+            self.w_qs = nn.utils.spectral_norm(self.w_qs)
+            self.w_ks = nn.utils.spectral_norm(self.w_ks)
+            self.w_vs = nn.utils.spectral_norm(self.w_vs)
+            self.fc = nn.utils.spectral_norm(self.fc)
+
+    def forward(self, x, mask=None):
+        d_k, d_v, n_head = self.d_k, self.d_v, self.n_head
+        sz_b, len_x, _ = x.size()
+
+        residual = x
+
+        q = self.w_qs(x).view(sz_b, len_x, n_head, d_k)
+        k = self.w_ks(x).view(sz_b, len_x, n_head, d_k)
+        v = self.w_vs(x).view(sz_b, len_x, n_head, d_v)
+        q = q.permute(2, 0, 1, 3).contiguous().view(-1,
+                                                    len_x, d_k)  # (n*b) x lq x dk
+        k = k.permute(2, 0, 1, 3).contiguous().view(-1,
+                                                    len_x, d_k)  # (n*b) x lk x dk
+        v = v.permute(2, 0, 1, 3).contiguous().view(-1,
+                                                    len_x, d_v)  # (n*b) x lv x dv
+
+        if mask is not None:
+            slf_mask = mask.repeat(n_head, 1, 1)  # (n*b) x .. x ..
+        else:
+            slf_mask = None
+        output, attn = self.attention(q, k, v, mask=slf_mask)
+
+        output = output.view(n_head, sz_b, len_x, d_v)
+        output = output.permute(1, 2, 0, 3).contiguous().view(
+            sz_b, len_x, -1)  # b x lq x (n*dv)
+
+        output = self.fc(output)
+
+        output = self.dropout(output) + residual
+        return output, attn
+
+
+class ScaledDotProductAttention(nn.Module):
+    ''' Scaled Dot-Product Attention '''
+
+    def __init__(self, temperature, dropout):
+        super().__init__()
+        self.temperature = temperature
+        self.softmax = nn.Softmax(dim=2)
+        self.dropout = nn.Dropout(dropout)
+
+    def forward(self, q, k, v, mask=None):
+        attn = torch.bmm(q, k.transpose(1, 2))
+        attn = attn / self.temperature
+
+        if mask is not None:
+            attn = attn.masked_fill(mask, -np.inf)
+
+        attn = self.softmax(attn)
+        p_attn = self.dropout(attn)
+
+        output = torch.bmm(p_attn, v)
+        return output, attn
+
+
+class MelStyleEncoder(nn.Module):
+    ''' MelStyleEncoder '''
+
+    def __init__(self, n_mel_channels=80,
+                 style_hidden=128,
+                 style_vector_dim=256,
+                 style_kernel_size=5,
+                 style_head=2,
+                 dropout=0.1):
+        super(MelStyleEncoder, self).__init__()
+        self.in_dim = n_mel_channels
+        self.hidden_dim = style_hidden
+        self.out_dim = style_vector_dim
+        self.kernel_size = style_kernel_size
+        self.n_head = style_head
+        self.dropout = dropout
+
+        self.spectral = nn.Sequential(
+            LinearNorm(self.in_dim, self.hidden_dim),
+            Mish(),
+            nn.Dropout(self.dropout),
+            LinearNorm(self.hidden_dim, self.hidden_dim),
+            Mish(),
+            nn.Dropout(self.dropout)
+        )
+
+        self.temporal = nn.Sequential(
+            Conv1dGLU(self.hidden_dim, self.hidden_dim, self.kernel_size, self.dropout),
+            Conv1dGLU(self.hidden_dim, self.hidden_dim, self.kernel_size, self.dropout),
+        )
+
+        self.slf_attn = MultiHeadAttention(self.n_head, self.hidden_dim,
+                                                   self.hidden_dim // self.n_head, self.hidden_dim // self.n_head,
+                                                   self.dropout)
+
+        self.fc = LinearNorm(self.hidden_dim, self.out_dim)
+
+    def temporal_avg_pool(self, x, mask=None):
+        if mask is None:
+            out = torch.mean(x, dim=1)
+        else:
+            len_ = (~mask).sum(dim=1).unsqueeze(1)
+            x = x.masked_fill(mask.unsqueeze(-1), 0)
+            x = x.sum(dim=1)
+            out = torch.div(x, len_)
+        return out
+
+    def forward(self, x, mask=None):
+        x = x.transpose(1,2)
+        if mask is not None:
+            mask = (mask.int()==0).squeeze(1)
+        max_len = x.shape[1]
+        slf_attn_mask = mask.unsqueeze(1).expand(-1, max_len, -1) if mask is not None else None
+
+        # spectral
+        x = self.spectral(x)
+        # temporal
+        x = x.transpose(1, 2)
+        x = self.temporal(x)
+        x = x.transpose(1, 2)
+        # self-attention
+        if mask is not None:
+            x = x.masked_fill(mask.unsqueeze(-1), 0)
+        x, _ = self.slf_attn(x, mask=slf_attn_mask)
+        # fc
+        x = self.fc(x)
+        # temoral average pooling
+        w = self.temporal_avg_pool(x, mask=mask)
+
+        return w.unsqueeze(-1)
+
+
+class MelStyleEncoderVAE(nn.Module):
+    def __init__(self, spec_channels, z_latent_dim, emb_dim):
+        super().__init__()
+        self.ref_encoder = MelStyleEncoder(spec_channels, style_vector_dim=emb_dim)
+        self.fc1 = nn.Linear(emb_dim, z_latent_dim)
+        self.fc2 = nn.Linear(emb_dim, z_latent_dim)
+        self.fc3 = nn.Linear(z_latent_dim, emb_dim)
+        self.z_latent_dim = z_latent_dim
+
+    def reparameterize(self, mu, logvar):
+        if self.training:
+            std = torch.exp(0.5 * logvar)
+            eps = torch.randn_like(std)
+            return eps.mul(std).add_(mu)
+        else:
+            return mu
+
+    def forward(self, inputs, mask=None):
+        enc_out = self.ref_encoder(inputs.squeeze(-1), mask).squeeze(-1)
+        mu = self.fc1(enc_out)
+        logvar = self.fc2(enc_out)
+        posterior = D.Normal(mu, torch.exp(logvar))
+        kl_divergence = D.kl_divergence(posterior, D.Normal(torch.zeros_like(mu), torch.ones_like(logvar)))
+        loss_kl = kl_divergence.mean()
+
+        z = posterior.rsample()
+        style_embed = self.fc3(z)
+
+        return style_embed.unsqueeze(-1), loss_kl
+
+    def infer(self, inputs=None, random_sample=False, manual_latent=None):
+        if manual_latent is None:
+            if random_sample:
+                dev = next(self.parameters()).device
+                posterior = D.Normal(torch.zeros(1, self.z_latent_dim, device=dev),
+                                     torch.ones(1, self.z_latent_dim, device=dev))
+                z = posterior.rsample()
+            else:
+
+                enc_out = self.ref_encoder(inputs.transpose(1, 2))
+                mu = self.fc1(enc_out)
+                z = mu
+        else:
+            z = manual_latent
+        style_embed = self.fc3(z)
+        return style_embed.unsqueeze(-1), z
+
+
+class ActNorm(nn.Module):
+    def __init__(self, channels, ddi=False, **kwargs):
+        super().__init__()
+        self.channels = channels
+        self.initialized = not ddi
+
+        self.logs = nn.Parameter(torch.zeros(1, channels, 1))
+        self.bias = nn.Parameter(torch.zeros(1, channels, 1))
+
+    def forward(self, x, x_mask=None, g=None, reverse=False, **kwargs):
+        if x_mask is None:
+            x_mask = torch.ones(x.size(0), 1, x.size(2)).to(device=x.device, dtype=x.dtype)
+        x_len = torch.sum(x_mask, [1, 2])
+        if not self.initialized:
+            self.initialize(x, x_mask)
+            self.initialized = True
+
+        if reverse:
+            z = (x - self.bias) * torch.exp(-self.logs) * x_mask
+            logdet = None
+            return z
+        else:
+            z = (self.bias + torch.exp(self.logs) * x) * x_mask
+            logdet = torch.sum(self.logs) * x_len  # [b]
+            return z, logdet
+
+    def store_inverse(self):
+        pass
+
+    def set_ddi(self, ddi):
+        self.initialized = not ddi
+
+    def initialize(self, x, x_mask):
+        with torch.no_grad():
+            denom = torch.sum(x_mask, [0, 2])
+            m = torch.sum(x * x_mask, [0, 2]) / denom
+            m_sq = torch.sum(x * x * x_mask, [0, 2]) / denom
+            v = m_sq - (m ** 2)
+            logs = 0.5 * torch.log(torch.clamp_min(v, 1e-6))
+
+            bias_init = (-m * torch.exp(-logs)).view(*self.bias.shape).to(dtype=self.bias.dtype)
+            logs_init = (-logs).view(*self.logs.shape).to(dtype=self.logs.dtype)
+
+            self.bias.data.copy_(bias_init)
+            self.logs.data.copy_(logs_init)
+
+
+class InvConvNear(nn.Module):
+    def __init__(self, channels, n_split=4, no_jacobian=False, **kwargs):
+        super().__init__()
+        assert (n_split % 2 == 0)
+        self.channels = channels
+        self.n_split = n_split
+        self.no_jacobian = no_jacobian
+
+        w_init = torch.linalg.qr(torch.FloatTensor(self.n_split, self.n_split).normal_())[0]
+        if torch.det(w_init) < 0:
+            w_init[:, 0] = -1 * w_init[:, 0]
+        self.weight = nn.Parameter(w_init)
+
+    def forward(self, x, x_mask=None, g=None, reverse=False, **kwargs):
+        b, c, t = x.size()
+        assert (c % self.n_split == 0)
+        if x_mask is None:
+            x_mask = 1
+            x_len = torch.ones((b,), dtype=x.dtype, device=x.device) * t
+        else:
+            x_len = torch.sum(x_mask, [1, 2])
+
+        x = x.view(b, 2, c // self.n_split, self.n_split // 2, t)
+        x = x.permute(0, 1, 3, 2, 4).contiguous().view(b, self.n_split, c // self.n_split, t)
+
+        if reverse:
+            if hasattr(self, "weight_inv"):
+                weight = self.weight_inv
+            else:
+                weight = torch.inverse(self.weight.float()).to(dtype=self.weight.dtype)
+            logdet = None
+        else:
+            weight = self.weight
+            if self.no_jacobian:
+                logdet = 0
+            else:
+                logdet = torch.logdet(self.weight) * (c / self.n_split) * x_len  # [b]
+
+        weight = weight.view(self.n_split, self.n_split, 1, 1)
+        z = F.conv2d(x, weight)
+
+        z = z.view(b, 2, self.n_split // 2, c // self.n_split, t)
+        z = z.permute(0, 1, 3, 2, 4).contiguous().view(b, c, t) * x_mask
+        if reverse:
+            return z
+        else:
+            return z, logdet
+
+    def store_inverse(self):
+        self.weight_inv = torch.inverse(self.weight.float()).to(dtype=self.weight.dtype)
diff --git a/module/mrte_model.py b/module/mrte_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..e936c76790499b201b83b80fcbcaaa08b8cd0fb3
--- /dev/null
+++ b/module/mrte_model.py
@@ -0,0 +1,160 @@
+# This is Multi-reference timbre encoder
+
+import torch
+from torch import nn
+from torch.nn.utils import remove_weight_norm, weight_norm
+from module.attentions import MultiHeadAttention
+
+class MRTE(nn.Module):
+    def __init__(self, 
+                 content_enc_channels=192,
+                 hidden_size=512,
+                 out_channels=192,
+                 kernel_size=5,
+                 n_heads=4,
+                 ge_layer = 2
+                 ):
+        super(MRTE, self).__init__()
+        self.cross_attention = MultiHeadAttention(hidden_size,hidden_size,n_heads)
+        self.c_pre = nn.Conv1d(content_enc_channels,hidden_size, 1)
+        self.text_pre = nn.Conv1d(content_enc_channels,hidden_size, 1)
+        self.c_post = nn.Conv1d(hidden_size,out_channels, 1)
+
+    def forward(self, ssl_enc, ssl_mask, text, text_mask, ge, test=None):
+        if(ge==None):ge=0
+        attn_mask = text_mask.unsqueeze(2) * ssl_mask.unsqueeze(-1)
+
+        ssl_enc = self.c_pre(ssl_enc * ssl_mask)
+        text_enc = self.text_pre(text * text_mask)
+        if test != None:
+            if test == 0:
+                x = self.cross_attention(ssl_enc * ssl_mask, text_enc * text_mask, attn_mask) + ssl_enc + ge
+            elif test == 1:
+                x = ssl_enc + ge
+            elif test ==2:
+                x = self.cross_attention(ssl_enc*0 * ssl_mask, text_enc * text_mask, attn_mask) + ge
+            else:
+                raise ValueError("test should be 0,1,2")
+        else:
+            x = self.cross_attention(ssl_enc * ssl_mask, text_enc * text_mask, attn_mask) + ssl_enc + ge
+        x = self.c_post(x * ssl_mask)
+        return x
+        
+
+class SpeakerEncoder(torch.nn.Module):
+    def __init__(self, mel_n_channels=80, model_num_layers=2, model_hidden_size=256, model_embedding_size=256):
+        super(SpeakerEncoder, self).__init__()
+        self.lstm = nn.LSTM(mel_n_channels, model_hidden_size, model_num_layers, batch_first=True)
+        self.linear = nn.Linear(model_hidden_size, model_embedding_size)
+        self.relu = nn.ReLU()
+
+    def forward(self, mels):
+        self.lstm.flatten_parameters()
+        _, (hidden, _) = self.lstm(mels.transpose(-1, -2))
+        embeds_raw = self.relu(self.linear(hidden[-1]))
+        return embeds_raw / torch.norm(embeds_raw, dim=1, keepdim=True)
+
+
+class MELEncoder(nn.Module):
+    def __init__(self,
+                 in_channels,
+                 out_channels,
+                 hidden_channels,
+                 kernel_size,
+                 dilation_rate,
+                 n_layers):
+        super().__init__()
+        self.in_channels = in_channels
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+
+        self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+        self.enc = WN(hidden_channels, kernel_size, dilation_rate, n_layers)
+        self.proj = nn.Conv1d(hidden_channels, out_channels, 1)
+
+    def forward(self, x):
+        # print(x.shape,x_lengths.shape)
+        x = self.pre(x)
+        x = self.enc(x)
+        x = self.proj(x)
+        return x
+    
+
+class WN(torch.nn.Module):
+  def __init__(self, hidden_channels, kernel_size, dilation_rate, n_layers):
+    super(WN, self).__init__()
+    assert(kernel_size % 2 == 1)
+    self.hidden_channels =hidden_channels
+    self.kernel_size = kernel_size
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+
+    self.in_layers = torch.nn.ModuleList()
+    self.res_skip_layers = torch.nn.ModuleList()
+
+    for i in range(n_layers):
+      dilation = dilation_rate ** i
+      padding = int((kernel_size * dilation - dilation) / 2)
+      in_layer = nn.Conv1d(hidden_channels, 2*hidden_channels, kernel_size,
+                                 dilation=dilation, padding=padding)
+      in_layer = weight_norm(in_layer)
+      self.in_layers.append(in_layer)
+
+      # last one is not necessary
+      if i < n_layers - 1:
+        res_skip_channels = 2 * hidden_channels
+      else:
+        res_skip_channels = hidden_channels
+
+      res_skip_layer = torch.nn.Conv1d(hidden_channels, res_skip_channels, 1)
+      res_skip_layer = weight_norm(res_skip_layer, name='weight')
+      self.res_skip_layers.append(res_skip_layer)
+
+  def forward(self, x):
+    output = torch.zeros_like(x)
+    n_channels_tensor = torch.IntTensor([self.hidden_channels])
+
+    for i in range(self.n_layers):
+      x_in = self.in_layers[i](x)
+
+      acts = fused_add_tanh_sigmoid_multiply(
+          x_in,
+          n_channels_tensor)
+
+      res_skip_acts = self.res_skip_layers[i](acts)
+      if i < self.n_layers - 1:
+        res_acts = res_skip_acts[:,:self.hidden_channels,:]
+        x = (x + res_acts)
+        output = output + res_skip_acts[:,self.hidden_channels:,:]
+      else:
+        output = output + res_skip_acts
+    return output
+
+  def remove_weight_norm(self):
+    for l in self.in_layers:
+      remove_weight_norm(l)
+    for l in self.res_skip_layers:
+      remove_weight_norm(l)
+
+
+@torch.jit.script
+def fused_add_tanh_sigmoid_multiply(input, n_channels):
+  n_channels_int = n_channels[0]
+  t_act = torch.tanh(input[:, :n_channels_int, :])
+  s_act = torch.sigmoid(input[:, n_channels_int:, :])
+  acts = t_act * s_act
+  return acts
+
+
+
+if __name__ == '__main__':
+    content_enc = torch.randn(3,192,100)
+    content_mask = torch.ones(3,1,100)
+    ref_mel = torch.randn(3,128,30)
+    ref_mask = torch.ones(3,1,30)
+    model = MRTE()
+    out = model(content_enc,content_mask,ref_mel,ref_mask)
+    print(out.shape)
\ No newline at end of file
diff --git a/module/quantize.py b/module/quantize.py
new file mode 100644
index 0000000000000000000000000000000000000000..cdbdeea3fec22ed3004e3096b20d9f6230e9267b
--- /dev/null
+++ b/module/quantize.py
@@ -0,0 +1,108 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""Residual vector quantizer implementation."""
+
+from dataclasses import dataclass, field
+import math
+import typing as tp
+
+import torch
+from torch import nn
+
+from module.core_vq import ResidualVectorQuantization
+
+
+@dataclass
+class QuantizedResult:
+    quantized: torch.Tensor
+    codes: torch.Tensor
+    bandwidth: torch.Tensor  # bandwidth in kb/s used, per batch item.
+    penalty: tp.Optional[torch.Tensor] = None
+    metrics: dict = field(default_factory=dict)
+
+
+class ResidualVectorQuantizer(nn.Module):
+    """Residual Vector Quantizer.
+    Args:
+        dimension (int): Dimension of the codebooks.
+        n_q (int): Number of residual vector quantizers used.
+        bins (int): Codebook size.
+        decay (float): Decay for exponential moving average over the codebooks.
+        kmeans_init (bool): Whether to use kmeans to initialize the codebooks.
+        kmeans_iters (int): Number of iterations used for kmeans initialization.
+        threshold_ema_dead_code (int): Threshold for dead code expiration. Replace any codes
+            that have an exponential moving average cluster size less than the specified threshold with
+            randomly selected vector from the current batch.
+    """
+    def __init__(
+        self,
+        dimension: int = 256,
+        n_q: int = 8,
+        bins: int = 1024,
+        decay: float = 0.99,
+        kmeans_init: bool = True,
+        kmeans_iters: int = 50,
+        threshold_ema_dead_code: int = 2,
+    ):
+        super().__init__()
+        self.n_q = n_q
+        self.dimension = dimension
+        self.bins = bins
+        self.decay = decay
+        self.kmeans_init = kmeans_init
+        self.kmeans_iters = kmeans_iters
+        self.threshold_ema_dead_code = threshold_ema_dead_code
+        self.vq = ResidualVectorQuantization(
+            dim=self.dimension,
+            codebook_size=self.bins,
+            num_quantizers=self.n_q,
+            decay=self.decay,
+            kmeans_init=self.kmeans_init,
+            kmeans_iters=self.kmeans_iters,
+            threshold_ema_dead_code=self.threshold_ema_dead_code,
+        )
+
+    def forward(self, x: torch.Tensor, n_q: tp.Optional[int] = None, layers: tp.Optional[list] = None) -> QuantizedResult:
+        """Residual vector quantization on the given input tensor.
+        Args:
+            x (torch.Tensor): Input tensor.
+            n_q (int): Number of quantizer used to quantize. Default: All quantizers.
+            layers (list): Layer that need to return quantized. Defalt: None.
+        Returns:
+            QuantizedResult:
+                The quantized (or approximately quantized) representation with
+                the associated numbert quantizers and layer quantized required to return.
+        """
+        n_q = n_q if n_q else self.n_q
+        if layers and max(layers) >= n_q:
+            raise ValueError(f'Last layer index in layers: A {max(layers)}. Number of quantizers in RVQ: B {self.n_q}. A must less than B.')
+        quantized, codes, commit_loss, quantized_list = self.vq(x, n_q=n_q, layers=layers)
+        return quantized, codes, torch.mean(commit_loss), quantized_list
+
+
+    def encode(self, x: torch.Tensor, n_q: tp.Optional[int] = None, st: tp.Optional[int] = None) -> torch.Tensor:
+        """Encode a given input tensor with the specified sample rate at the given bandwidth.
+        The RVQ encode method sets the appropriate number of quantizer to use
+        and returns indices for each quantizer.
+        Args:
+            x (torch.Tensor): Input tensor.
+            n_q (int): Number of quantizer used to quantize. Default: All quantizers.
+            st (int): Start to encode input from which layers. Default: 0.
+        """
+        n_q = n_q if n_q else self.n_q
+        st = st or 0
+        codes = self.vq.encode(x, n_q=n_q, st=st)
+        return codes
+
+    def decode(self, codes: torch.Tensor, st: int = 0) -> torch.Tensor:
+        """Decode the given codes to the quantized representation.
+        Args:
+            codes (torch.Tensor): Input indices for each quantizer.
+            st (int): Start to decode input codes from which layers. Default: 0.
+        """
+        quantized = self.vq.decode(codes, st=st)
+        return quantized
\ No newline at end of file
diff --git a/module/transforms.py b/module/transforms.py
new file mode 100644
index 0000000000000000000000000000000000000000..4793d67ca5a5630e0ffe0f9fb29445c949e64dae
--- /dev/null
+++ b/module/transforms.py
@@ -0,0 +1,193 @@
+import torch
+from torch.nn import functional as F
+
+import numpy as np
+
+
+DEFAULT_MIN_BIN_WIDTH = 1e-3
+DEFAULT_MIN_BIN_HEIGHT = 1e-3
+DEFAULT_MIN_DERIVATIVE = 1e-3
+
+
+def piecewise_rational_quadratic_transform(inputs, 
+                                           unnormalized_widths,
+                                           unnormalized_heights,
+                                           unnormalized_derivatives,
+                                           inverse=False,
+                                           tails=None, 
+                                           tail_bound=1.,
+                                           min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+                                           min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+                                           min_derivative=DEFAULT_MIN_DERIVATIVE):
+
+    if tails is None:
+        spline_fn = rational_quadratic_spline
+        spline_kwargs = {}
+    else:
+        spline_fn = unconstrained_rational_quadratic_spline
+        spline_kwargs = {
+            'tails': tails,
+            'tail_bound': tail_bound
+        }
+
+    outputs, logabsdet = spline_fn(
+            inputs=inputs,
+            unnormalized_widths=unnormalized_widths,
+            unnormalized_heights=unnormalized_heights,
+            unnormalized_derivatives=unnormalized_derivatives,
+            inverse=inverse,
+            min_bin_width=min_bin_width,
+            min_bin_height=min_bin_height,
+            min_derivative=min_derivative,
+            **spline_kwargs
+    )
+    return outputs, logabsdet
+
+
+def searchsorted(bin_locations, inputs, eps=1e-6):
+    bin_locations[..., -1] += eps
+    return torch.sum(
+        inputs[..., None] >= bin_locations,
+        dim=-1
+    ) - 1
+
+
+def unconstrained_rational_quadratic_spline(inputs,
+                                            unnormalized_widths,
+                                            unnormalized_heights,
+                                            unnormalized_derivatives,
+                                            inverse=False,
+                                            tails='linear',
+                                            tail_bound=1.,
+                                            min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+                                            min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+                                            min_derivative=DEFAULT_MIN_DERIVATIVE):
+    inside_interval_mask = (inputs >= -tail_bound) & (inputs <= tail_bound)
+    outside_interval_mask = ~inside_interval_mask
+
+    outputs = torch.zeros_like(inputs)
+    logabsdet = torch.zeros_like(inputs)
+
+    if tails == 'linear':
+        unnormalized_derivatives = F.pad(unnormalized_derivatives, pad=(1, 1))
+        constant = np.log(np.exp(1 - min_derivative) - 1)
+        unnormalized_derivatives[..., 0] = constant
+        unnormalized_derivatives[..., -1] = constant
+
+        outputs[outside_interval_mask] = inputs[outside_interval_mask]
+        logabsdet[outside_interval_mask] = 0
+    else:
+        raise RuntimeError('{} tails are not implemented.'.format(tails))
+
+    outputs[inside_interval_mask], logabsdet[inside_interval_mask] = rational_quadratic_spline(
+        inputs=inputs[inside_interval_mask],
+        unnormalized_widths=unnormalized_widths[inside_interval_mask, :],
+        unnormalized_heights=unnormalized_heights[inside_interval_mask, :],
+        unnormalized_derivatives=unnormalized_derivatives[inside_interval_mask, :],
+        inverse=inverse,
+        left=-tail_bound, right=tail_bound, bottom=-tail_bound, top=tail_bound,
+        min_bin_width=min_bin_width,
+        min_bin_height=min_bin_height,
+        min_derivative=min_derivative
+    )
+
+    return outputs, logabsdet
+
+def rational_quadratic_spline(inputs,
+                              unnormalized_widths,
+                              unnormalized_heights,
+                              unnormalized_derivatives,
+                              inverse=False,
+                              left=0., right=1., bottom=0., top=1.,
+                              min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+                              min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+                              min_derivative=DEFAULT_MIN_DERIVATIVE):
+    if torch.min(inputs) < left or torch.max(inputs) > right:
+        raise ValueError('Input to a transform is not within its domain')
+
+    num_bins = unnormalized_widths.shape[-1]
+
+    if min_bin_width * num_bins > 1.0:
+        raise ValueError('Minimal bin width too large for the number of bins')
+    if min_bin_height * num_bins > 1.0:
+        raise ValueError('Minimal bin height too large for the number of bins')
+
+    widths = F.softmax(unnormalized_widths, dim=-1)
+    widths = min_bin_width + (1 - min_bin_width * num_bins) * widths
+    cumwidths = torch.cumsum(widths, dim=-1)
+    cumwidths = F.pad(cumwidths, pad=(1, 0), mode='constant', value=0.0)
+    cumwidths = (right - left) * cumwidths + left
+    cumwidths[..., 0] = left
+    cumwidths[..., -1] = right
+    widths = cumwidths[..., 1:] - cumwidths[..., :-1]
+
+    derivatives = min_derivative + F.softplus(unnormalized_derivatives)
+
+    heights = F.softmax(unnormalized_heights, dim=-1)
+    heights = min_bin_height + (1 - min_bin_height * num_bins) * heights
+    cumheights = torch.cumsum(heights, dim=-1)
+    cumheights = F.pad(cumheights, pad=(1, 0), mode='constant', value=0.0)
+    cumheights = (top - bottom) * cumheights + bottom
+    cumheights[..., 0] = bottom
+    cumheights[..., -1] = top
+    heights = cumheights[..., 1:] - cumheights[..., :-1]
+
+    if inverse:
+        bin_idx = searchsorted(cumheights, inputs)[..., None]
+    else:
+        bin_idx = searchsorted(cumwidths, inputs)[..., None]
+
+    input_cumwidths = cumwidths.gather(-1, bin_idx)[..., 0]
+    input_bin_widths = widths.gather(-1, bin_idx)[..., 0]
+
+    input_cumheights = cumheights.gather(-1, bin_idx)[..., 0]
+    delta = heights / widths
+    input_delta = delta.gather(-1, bin_idx)[..., 0]
+
+    input_derivatives = derivatives.gather(-1, bin_idx)[..., 0]
+    input_derivatives_plus_one = derivatives[..., 1:].gather(-1, bin_idx)[..., 0]
+
+    input_heights = heights.gather(-1, bin_idx)[..., 0]
+
+    if inverse:
+        a = (((inputs - input_cumheights) * (input_derivatives
+                                             + input_derivatives_plus_one
+                                             - 2 * input_delta)
+              + input_heights * (input_delta - input_derivatives)))
+        b = (input_heights * input_derivatives
+             - (inputs - input_cumheights) * (input_derivatives
+                                              + input_derivatives_plus_one
+                                              - 2 * input_delta))
+        c = - input_delta * (inputs - input_cumheights)
+
+        discriminant = b.pow(2) - 4 * a * c
+        assert (discriminant >= 0).all()
+
+        root = (2 * c) / (-b - torch.sqrt(discriminant))
+        outputs = root * input_bin_widths + input_cumwidths
+
+        theta_one_minus_theta = root * (1 - root)
+        denominator = input_delta + ((input_derivatives + input_derivatives_plus_one - 2 * input_delta)
+                                     * theta_one_minus_theta)
+        derivative_numerator = input_delta.pow(2) * (input_derivatives_plus_one * root.pow(2)
+                                                     + 2 * input_delta * theta_one_minus_theta
+                                                     + input_derivatives * (1 - root).pow(2))
+        logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
+
+        return outputs, -logabsdet
+    else:
+        theta = (inputs - input_cumwidths) / input_bin_widths
+        theta_one_minus_theta = theta * (1 - theta)
+
+        numerator = input_heights * (input_delta * theta.pow(2)
+                                     + input_derivatives * theta_one_minus_theta)
+        denominator = input_delta + ((input_derivatives + input_derivatives_plus_one - 2 * input_delta)
+                                     * theta_one_minus_theta)
+        outputs = input_cumheights + numerator / denominator
+
+        derivative_numerator = input_delta.pow(2) * (input_derivatives_plus_one * theta.pow(2)
+                                                     + 2 * input_delta * theta_one_minus_theta
+                                                     + input_derivatives * (1 - theta).pow(2))
+        logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
+
+        return outputs, logabsdet
diff --git a/my_utils.py b/my_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..776939dd29bbcd9c45e47665f545a3dddcb16478
--- /dev/null
+++ b/my_utils.py
@@ -0,0 +1,21 @@
+import ffmpeg
+import numpy as np
+
+
+def load_audio(file, sr):
+    try:
+        # https://github.com/openai/whisper/blob/main/whisper/audio.py#L26
+        # This launches a subprocess to decode audio while down-mixing and resampling as necessary.
+        # Requires the ffmpeg CLI and `ffmpeg-python` package to be installed.
+        file = (
+            file.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
+        )  # 防止小白拷路径头尾带了空格和"和回车
+        out, _ = (
+            ffmpeg.input(file, threads=0)
+            .output("-", format="f32le", acodec="pcm_f32le", ac=1, ar=sr)
+            .run(cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True)
+        )
+    except Exception as e:
+        raise RuntimeError(f"Failed to load audio: {e}")
+
+    return np.frombuffer(out, np.float32).flatten()
diff --git a/pretrained_models/chinese-hubert-base/config.json b/pretrained_models/chinese-hubert-base/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..0bb839d4b0cd2ad41cb13c6500fd660800aaefdf
--- /dev/null
+++ b/pretrained_models/chinese-hubert-base/config.json
@@ -0,0 +1,72 @@
+{
+  "_name_or_path": "/data/docker/liujing04/gpt-vits/chinese-hubert-base",
+  "activation_dropout": 0.1,
+  "apply_spec_augment": true,
+  "architectures": [
+    "HubertModel"
+  ],
+  "attention_dropout": 0.1,
+  "bos_token_id": 1,
+  "classifier_proj_size": 256,
+  "conv_bias": false,
+  "conv_dim": [
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512
+  ],
+  "conv_kernel": [
+    10,
+    3,
+    3,
+    3,
+    3,
+    2,
+    2
+  ],
+  "conv_stride": [
+    5,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2
+  ],
+  "ctc_loss_reduction": "sum",
+  "ctc_zero_infinity": false,
+  "do_stable_layer_norm": false,
+  "eos_token_id": 2,
+  "feat_extract_activation": "gelu",
+  "feat_extract_norm": "group",
+  "feat_proj_dropout": 0.0,
+  "feat_proj_layer_norm": true,
+  "final_dropout": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "layerdrop": 0.1,
+  "mask_feature_length": 10,
+  "mask_feature_min_masks": 0,
+  "mask_feature_prob": 0.0,
+  "mask_time_length": 10,
+  "mask_time_min_masks": 2,
+  "mask_time_prob": 0.05,
+  "model_type": "hubert",
+  "num_attention_heads": 12,
+  "num_conv_pos_embedding_groups": 16,
+  "num_conv_pos_embeddings": 128,
+  "num_feat_extract_layers": 7,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "torch_dtype": "float16",
+  "transformers_version": "4.30.2",
+  "use_weighted_layer_sum": false,
+  "vocab_size": 32
+}
diff --git a/pretrained_models/chinese-hubert-base/preprocessor_config.json b/pretrained_models/chinese-hubert-base/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..409547bbb99588f69a603019a707505610fa38d3
--- /dev/null
+++ b/pretrained_models/chinese-hubert-base/preprocessor_config.json
@@ -0,0 +1,9 @@
+{
+  "do_normalize": true,
+  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
+  "feature_size": 1,
+  "padding_side": "right",
+  "padding_value": 0,
+  "return_attention_mask": false,
+  "sampling_rate": 16000
+}
\ No newline at end of file
diff --git a/pretrained_models/chinese-roberta-wwm-ext-large/config.json b/pretrained_models/chinese-roberta-wwm-ext-large/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3ae58d7f0734373bb28d3b6b9d6858b34f600b4a
--- /dev/null
+++ b/pretrained_models/chinese-roberta-wwm-ext-large/config.json
@@ -0,0 +1,34 @@
+{
+  "_name_or_path": "/data/docker/liujing04/bert-vits2/Bert-VITS2-master20231106/bert/chinese-roberta-wwm-ext-large",
+  "architectures": [
+    "BertForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float16",
+  "transformers_version": "4.30.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 21128
+}
diff --git a/pretrained_models/chinese-roberta-wwm-ext-large/tokenizer.json b/pretrained_models/chinese-roberta-wwm-ext-large/tokenizer.json
new file mode 100644
index 0000000000000000000000000000000000000000..9e77beb20869ea3b7850166fbc8cc7734662a017
--- /dev/null
+++ b/pretrained_models/chinese-roberta-wwm-ext-large/tokenizer.json
@@ -0,0 +1 @@
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diff --git a/text/__init__.py b/text/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..a48b9a49a39bdae1801d94a15db645154d6a68d1
--- /dev/null
+++ b/text/__init__.py
@@ -0,0 +1,15 @@
+from text.symbols import *
+
+
+_symbol_to_id = {s: i for i, s in enumerate(symbols)}
+
+def cleaned_text_to_sequence(cleaned_text):
+  '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
+    Args:
+      text: string to convert to a sequence
+    Returns:
+      List of integers corresponding to the symbols in the text
+  '''
+  phones = [_symbol_to_id[symbol] for symbol in cleaned_text]
+  return phones
+
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diff --git a/text/chinese.py b/text/chinese.py
new file mode 100644
index 0000000000000000000000000000000000000000..03bdefb66af02bc0e77afd886c7380d846ba40bd
--- /dev/null
+++ b/text/chinese.py
@@ -0,0 +1,167 @@
+import os
+import pdb
+import re
+
+import cn2an
+from pypinyin import lazy_pinyin, Style
+
+import sys
+sys.path.append("/data/docker/liujing04/gpt-vits/gpt-vits-master")
+
+from text.symbols import punctuation
+from text.tone_sandhi import ToneSandhi
+
+current_file_path = os.path.dirname(__file__)
+pinyin_to_symbol_map = {line.split("\t")[0]: line.strip().split("\t")[1] for line in
+                        open(os.path.join(current_file_path, 'opencpop-strict.txt')).readlines()}
+
+import jieba.posseg as psg
+
+
+rep_map = {
+    '：': ',',
+    '；': ',',
+    '，': ',',
+    '。': '.',
+    '！': '!',
+    '？': '?',
+    '\n': '.',
+    "·": ",",
+    '、': ",",
+    '...': '…',
+    '$': '.',
+    '/': ',',
+    '—': "-"
+}
+
+tone_modifier = ToneSandhi()
+
+def replace_punctuation(text):
+    text = text.replace("嗯", "恩").replace("呣","母")
+    pattern = re.compile('|'.join(re.escape(p) for p in rep_map.keys()))
+
+    replaced_text = pattern.sub(lambda x: rep_map[x.group()], text)
+
+    replaced_text = re.sub(r'[^\u4e00-\u9fa5'+"".join(punctuation)+r']+', '', replaced_text)
+
+    return replaced_text
+
+def g2p(text):
+    pattern = r'(?<=[{0}])\s*'.format(''.join(punctuation))
+    sentences = [i for i in re.split(pattern, text) if i.strip()!='']
+    phones, word2ph = _g2p(sentences)
+    return phones, word2ph
+
+
+def _get_initials_finals(word):
+    initials = []
+    finals = []
+    orig_initials = lazy_pinyin(
+        word, neutral_tone_with_five=True, style=Style.INITIALS)
+    orig_finals = lazy_pinyin(
+        word, neutral_tone_with_five=True, style=Style.FINALS_TONE3)
+    for c, v in zip(orig_initials, orig_finals):
+        initials.append(c)
+        finals.append(v)
+    return initials, finals
+
+
+def _g2p(segments):
+    phones_list = []
+    word2ph = []
+    for seg in segments:
+        pinyins = []
+        # Replace all English words in the sentence
+        seg = re.sub('[a-zA-Z]+', '', seg)
+        seg_cut = psg.lcut(seg)
+        initials = []
+        finals = []
+        seg_cut = tone_modifier.pre_merge_for_modify(seg_cut)
+        for word, pos in seg_cut:
+            if pos == 'eng':
+                continue
+            sub_initials, sub_finals = _get_initials_finals(word)
+            sub_finals = tone_modifier.modified_tone(word, pos,
+                                                          sub_finals)
+            initials.append(sub_initials)
+            finals.append(sub_finals)
+
+            # assert len(sub_initials) == len(sub_finals) == len(word)
+        initials = sum(initials, [])
+        finals = sum(finals, [])
+        #
+        for c, v in zip(initials, finals):
+            raw_pinyin = c+v
+            # NOTE: post process for pypinyin outputs
+            # we discriminate i, ii and iii
+            if c == v:
+                assert c in punctuation
+                phone = [c]
+                word2ph.append(1)
+            else:
+                v_without_tone = v[:-1]
+                tone = v[-1]
+
+                pinyin = c+v_without_tone
+                assert tone in '12345'
+
+                if c:
+                    # 多音节
+                    v_rep_map = {
+                        "uei": 'ui',
+                        'iou': 'iu',
+                        'uen': 'un',
+                    }
+                    if v_without_tone in v_rep_map.keys():
+                        pinyin = c+v_rep_map[v_without_tone]
+                else:
+                    # 单音节
+                    pinyin_rep_map = {
+                        'ing': 'ying',
+                        'i': 'yi',
+                        'in': 'yin',
+                        'u': 'wu',
+                    }
+                    if pinyin in pinyin_rep_map.keys():
+                        pinyin = pinyin_rep_map[pinyin]
+                    else:
+                        single_rep_map = {
+                            'v': 'yu',
+                            'e': 'e',
+                            'i': 'y',
+                            'u': 'w',
+                        }
+                        if pinyin[0] in single_rep_map.keys():
+                            pinyin = single_rep_map[pinyin[0]]+pinyin[1:]
+
+                assert pinyin in pinyin_to_symbol_map.keys(), (pinyin, seg, raw_pinyin)
+                new_c, new_v = pinyin_to_symbol_map[pinyin].split(' ')
+                new_v = new_v + tone
+                phone = [new_c, new_v]
+                word2ph.append(len(phone))
+
+            phones_list += phone
+    return phones_list, word2ph
+
+
+
+def text_normalize(text):
+    numbers = re.findall(r'\d+(?:\.?\d+)?', text)
+    for number in numbers:
+        text = text.replace(number, cn2an.an2cn(number), 1)
+    text = replace_punctuation(text)
+
+    return text
+
+
+if __name__ == '__main__':
+    text = "啊——但是《原神》是由,米哈\游自主，研发的一款全.新开放世界.冒险游戏"
+    text = "呣呣呣～就是…大人的鼹鼠党吧？"
+    text = "你好"
+    text = text_normalize(text)
+    print(g2p(text))
+
+
+# # 示例用法
+# text = "这是一个示例文本：,你好！这是一个测试..."
+# print(g2p_paddle(text))  # 输出: 这是一个示例文本你好这是一个测试
diff --git a/text/cleaner.py b/text/cleaner.py
new file mode 100644
index 0000000000000000000000000000000000000000..dc4bd732cd7138dc1eff5bf189fd6816621658ab
--- /dev/null
+++ b/text/cleaner.py
@@ -0,0 +1,57 @@
+from text import chinese, japanese, cleaned_text_to_sequence, symbols, english
+
+language_module_map = {
+    'zh': chinese,
+    "ja": japanese,
+    'en': english
+}
+special = [
+    ('%', 'zh', "SP"),
+    ('￥', 'zh', "SP2"),
+    ('^', 'zh', "SP3"),
+    # ('@', 'zh', "SP4")#不搞鬼畜了，和第二版保持一致吧
+]
+def clean_text(text, language):
+    for special_s, special_l, target_symbol in special:
+        if special_s in text and language == special_l:
+            return clean_special(text, language, special_s, target_symbol)
+    language_module = language_module_map[language]
+    norm_text = language_module.text_normalize(text)
+    if(language=="zh"):
+        phones, word2ph = language_module.g2p(norm_text)
+        assert len(phones) == sum(word2ph)
+        assert len(norm_text) == len(word2ph)
+    else:
+        phones = language_module.g2p(norm_text)
+        word2ph=None
+
+    for ph in phones:
+        assert ph in symbols
+    return phones, word2ph, norm_text
+
+
+def clean_special(text, language, special_s, target_symbol):
+    """
+    特殊静音段sp符号处理
+    """
+    text = text.replace(special_s, ",")
+    language_module = language_module_map[language]
+    norm_text = language_module.text_normalize(text)
+    phones = language_module.g2p(norm_text)
+    new_ph = []
+    for ph in phones:
+        assert ph in symbols
+        if ph == ',':
+            new_ph.append(target_symbol)
+        else:
+            new_ph.append(ph)
+    return new_ph
+
+def text_to_sequence(text, language):
+    phones = clean_text(text)
+    return cleaned_text_to_sequence(phones)
+
+if __name__ == '__main__':
+    print(clean_text("你好%啊啊啊额、还是到付红四方。", 'zh'))
+
+
diff --git a/text/cmudict.rep b/text/cmudict.rep
new file mode 100644
index 0000000000000000000000000000000000000000..eb2199d15167088b38044939acd779dcf8e334c1
--- /dev/null
+++ b/text/cmudict.rep
@@ -0,0 +1,129530 @@
+## Date:  August 8, 1998
+##
+## The Carnegie Mellon Pronouncing Dictionary [cmudict.0.6] is Copyright 1998
+## by Carnegie Mellon University. Use of this dictionary, for any research or
+## commercial purpose, is completely unrestricted.  If you make use of or
+## redistribute this material, we would appreciate acknowlegement of its
+## origin.
+##
+## cmudict.0.6 is the fifth release of cmudict, first released as cmudict.0.1
+## in September of 1993.  There was no generally available public release 
+## of version 0.5.
+##
+## See the README in this directory before you use this dictionary.
+##
+## Thanks to Bill Huggins at BBN; Bill Fisher at NIST; Alex Hauptman,
+## Alex Rudnicky, Jack Mostow, Roni Rosenfeld, Richard Stern,
+## Matthew Siegler, Kevin Lenzo, Maxine Eskenazi, Mosur Ravishankar,
+## Eric Thayer, Kristie Seymore, and Raj Reddy at CMU; Lin Chase at
+## LIMSI; Doug Paul at MIT Lincoln Labs; Ben Serridge at MIT SLS; Murray 
+## Spiegel at Bellcore; Tony Robinson at Cambridge UK; David Bowness of 
+## CAE Electronics Ltd. and CRIM; Stephen Hocking; Jerry Quinn at BNR 
+## Canada, and Marshal Midden for bringing to our attention problems and 
+## inadequacies with the first releases. Most special thanks to Bob Weide 
+## for all his work on prior versions of the dictionary.
+##
+## We welcome input from users and will continue to acknowledge such input
+## in subsequent releases. If I failed to acknowledge your input in this
+## release, please remind me and I will update these comments. If I failed to
+## fix things that you brought to my attention, please remind me and have
+## patience. If I actually fixed things that you brought to my attention and
+## you appreciate it, I wouldn't mind a pat on the back.
+##
+## This version differs from previous releases of cmudict most significantly
+## in the addition of new words from the common ARPA tasks for 1996 and 1997.
+##
+## There are undoubtedly still errors and inconsistencies in this dictionary
+## so keep your eyes open for problems and mail them to me.
+##
+## We hope this dictionary is an improvement over cmudict.0.4.
+## 
+## email: cmudict@cs.cmu.edu
+## web:   http://www.speech.cs.cmu.edu/cgi-bin/cmudict
+## ftp:   ftp://ftp.cs.cmu.edu/project/speech/dict/
+##
+## Thank you for your continued interest in the CMU Pronouncing 
+## Dictionary.  Further addictions and improvements are planned
+## for forthcoming releases.
+##
+!EXCLAMATION-POINT  EH2 K - S K L AH0 - M EY1 - SH AH0 N - P OY2 N T
+"CLOSE-QUOTE  K L OW1 Z - K W OW1 T
+"DOUBLE-QUOTE  D AH1 - B AH0 L - K W OW1 T
+"END-OF-QUOTE  EH1 N - D AH0 V - K W OW1 T
+"END-QUOTE  EH1 N D - K W OW1 T
+"IN-QUOTES  IH1 N - K W OW1 T S
+"QUOTE  K W OW1 T
+"UNQUOTE  AH1 N - K W OW1 T
+#SHARP-SIGN  SH AA1 R P - S AY1 N
+%PERCENT  P ER0 - S EH1 N T
+&AMPERSAND  AE1 M - P ER0 - S AE2 N D
+'CAUSE  K AH0 Z
+'COURSE  K AO1 R S
+'EM  AH0 M
+'END-INNER-QUOTE  EH1 N - D IH1 - N ER0 - K W OW1 T
+'END-QUOTE  EH1 N D - K W OW1 T
+'INNER-QUOTE  IH1 - N ER0 - K W OW1 T
+'M  AH0 M
+'N  AH0 N
+'QUOTE  K W OW1 T
+'S  EH1 S
+'SINGLE-QUOTE  S IH1 NG - G AH0 L - K W OW1 T
+'TIL  T IH1 L
+'TIS  T IH1 Z
+'TWAS  T W AH1 Z
+(BEGIN-PARENS  B IH0 - G IH1 N - P ER0 - EH1 N Z
+(IN-PARENTHESES  IH1 N - P ER0 - EH1 N - TH AH0 - S IY2 Z
+(LEFT-PAREN  L EH1 F T - P ER0 - EH1 N
+(OPEN-PARENTHESES  OW1 - P AH0 N - P ER0 - EH1 N - TH AH0 - S IY2 Z
+(PAREN  P ER0 - EH1 N
+(PARENS  P ER0 - EH1 N Z
+(PARENTHESES  P ER0 - EH1 N - TH AH0 - S IY2 Z
+)CLOSE-PAREN  K L OW1 Z - P ER0 - EH1 N
+)CLOSE-PARENTHESES  K L OW1 Z - P ER0 - EH1 N - TH AH0 - S IY2 Z
+)END-PAREN  EH1 N D - P ER0 - EH1 N
+)END-PARENS  EH1 N D - P ER0 - EH1 N Z
+)END-PARENTHESES  EH1 N D - P ER0 - EH1 N - TH AH0 - S IY2 Z
+)END-THE-PAREN  EH1 N D - DH AH0 - P ER0 - EH1 N
+)PAREN  P ER0 - EH1 N
+)PARENS  P ER0 - EH1 N Z
+)RIGHT-PAREN  R AY1 T - P ER0 - EH1 N
+)RIGHT-PAREN(2)  R AY1 T - P EH1 - R AH0 N
+)UN-PARENTHESES  AH1 N - P ER0 - EH1 N - TH AH0 - S IY1 Z
+,COMMA  K AA1 - M AH0
+-DASH  D AE1 SH
+-HYPHEN  HH AY1 - F AH0 N
+...ELLIPSIS  IH0 - L IH1 P - S IH0 S
+.DECIMAL  D EH1 - S AH0 - M AH0 L
+.DOT  D AA1 T
+.FULL-STOP  F UH1 L - S T AA1 P
+.PERIOD  P IH1 - R IY0 - AH0 D
+.POINT  P OY1 N T
+/SLASH  S L AE1 SH
+0MALEFACTORS  M AE1 - L AH0 - F AE2 K - T ER0 Z
+:COLON  K OW1 - L AH0 N
+;SEMI-COLON  S EH1 - M IY0 - K OW1 - L AH0 N
+;SEMI-COLON(2)  S EH1 - M IH0 - K OW2 - L AH0 N
+?QUESTION-MARK  K W EH1 S - CH AH0 N - M AA1 R K
+A  AH0
+A'S  EY1 Z
+A(2)  EY1
+A.  EY1
+A.'S  EY1 Z
+A.S  EY1 Z
+A42128  EY1 - F AO1 R - T UW1 - W AH1 N - T UW1 - EY1 T
+AAA  T R IH2 - P AH0 - L EY1
+AABERG  AA1 - B ER0 G
+AACHEN  AA1 - K AH0 N
+AAKER  AA1 - K ER0
+AALSETH  AA1 L - S EH0 TH
+AAMODT  AA1 - M AH0 T
+AANCOR  AA1 N - K AO2 R
+AARDEMA  AA0 R - D EH1 - M AH0
+AARDVARK  AA1 R D - V AA2 R K
+AARON  EH1 - R AH0 N
+AARON'S  EH1 - R AH0 N Z
+AARONS  EH1 - R AH0 N Z
+AARONSON  EH1 - R AH0 N - S AH0 N
+AARONSON'S  EH1 - R AH0 N - S AH0 N Z
+AARONSON'S(2)  AA1 - R AH0 N - S AH0 N Z
+AARONSON(2)  AA1 - R AH0 N - S AH0 N
+AARTI  AA1 R - T IY2
+AASE  AA1 S
+AASEN  AA1 - S AH0 N
+AB  AE1 B
+AB(2)  EY1 - B IY1
+ABABA  AH0 - B AA1 - B AH0
+ABABA(2)  AA1 - B AH0 - B AH0
+ABACHA  AE1 - B AH0 - K AH0
+ABACK  AH0 - B AE1 K
+ABACO  AE1 - B AH0 - K OW2
+ABACUS  AE1 - B AH0 - K AH0 S
+ABAD  AH0 - B AA1 D
+ABADAKA  AH0 - B AE1 - D AH0 - K AH0
+ABADI  AH0 - B AE1 - D IY0
+ABADIE  AH0 - B AE1 - D IY0
+ABAIR  AH0 - B EH1 R
+ABALKIN  AH0 - B AA1 L - K IH0 N
+ABALONE  AE2 - B AH0 - L OW1 - N IY0
+ABALOS  AA0 - B AA1 - L OW0 Z
+ABANDON  AH0 - B AE1 N - D AH0 N
+ABANDONED  AH0 - B AE1 N - D AH0 N D
+ABANDONING  AH0 - B AE1 N - D AH0 - N IH0 NG
+ABANDONMENT  AH0 - B AE1 N - D AH0 N - M AH0 N T
+ABANDONMENTS  AH0 - B AE1 N - D AH0 N - M AH0 N T S
+ABANDONS  AH0 - B AE1 N - D AH0 N Z
+ABANTO  AH0 - B AE1 N - T OW0
+ABARCA  AH0 - B AA1 R - K AH0
+ABARE  AA0 - B AA1 - R IY0
+ABASCAL  AE1 - B AH0 S - K AH0 L
+ABASH  AH0 - B AE1 SH
+ABASHED  AH0 - B AE1 SH T
+ABATE  AH0 - B EY1 T
+ABATED  AH0 - B EY1 - T IH0 D
+ABATEMENT  AH0 - B EY1 T - M AH0 N T
+ABATEMENTS  AH0 - B EY1 T - M AH0 N T S
+ABATES  AH0 - B EY1 T S
+ABATING  AH0 - B EY1 - T IH0 NG
+ABBA  AE1 - B AH0
+ABBADO  AH0 - B AA1 - D OW0
+ABBAS  AH0 - B AA1 S
+ABBASI  AA0 - B AA1 - S IY0
+ABBATE  AA1 - B EY0 T
+ABBATIELLO  AA0 - B AA0 - T IY0 - EH1 - L OW0
+ABBE  AE1 - B IY0
+ABBE(2)  AE0 - B EY1
+ABBENHAUS  AE1 - B AH0 N - HH AW2 S
+ABBETT  AH0 - B EH1 T
+ABBEVILLE  AE1 B - V IH0 L
+ABBEY  AE1 - B IY0
+ABBEY'S  AE1 - B IY0 Z
+ABBIE  AE1 - B IY0
+ABBITT  AE1 - B IH0 T
+ABBOT  AE1 - B AH0 T
+ABBOTT  AE1 - B AH0 T
+ABBOTT'S  AE1 - B AH0 T S
+ABBOUD  AH0 - B UW1 D
+ABBOUD(2)  AH0 - B AW1 D
+ABBREVIATE  AH0 - B R IY1 - V IY0 - EY2 T
+ABBREVIATED  AH0 - B R IY1 - V IY0 - EY2 - T AH0 D
+ABBREVIATED(2)  AH0 - B R IY1 - V IY0 - EY2 - T IH0 D
+ABBREVIATES  AH0 - B R IY1 - V IY0 - EY2 T S
+ABBREVIATING  AH0 - B R IY1 - V IY0 - EY2 - T IH0 NG
+ABBREVIATION  AH0 - B R IY2 - V IY0 - EY1 - SH AH0 N
+ABBREVIATIONS  AH0 - B R IY2 - V IY0 - EY1 - SH AH0 N Z
+ABBRUZZESE  AA0 - B R UW0 T - S EY1 - Z IY0
+ABBS  AE1 B Z
+ABBY  AE1 - B IY0
+ABCO  AE1 B - K OW0
+ABCOTEK  AE1 B - K OW0 - T EH2 K
+ABDALLA  AE2 B - D AE1 - L AH0
+ABDALLAH  AE2 B - D AE1 - L AH0
+ABDEL  AE1 B - D EH2 L
+ABDELLA  AE2 B - D EH1 - L AH0
+ABDICATE  AE1 B - D AH0 - K EY2 T
+ABDICATED  AE1 B - D AH0 - K EY2 - T AH0 D
+ABDICATES  AE1 B - D AH0 - K EY2 T S
+ABDICATING  AE1 B - D IH0 - K EY2 - T IH0 NG
+ABDICATION  AE2 B - D IH0 - K EY1 - SH AH0 N
+ABDNOR  AE1 B D - N ER0
+ABDO  AE1 B - D OW0
+ABDOLLAH  AE2 B - D AA1 - L AH0
+ABDOMEN  AE0 B - D OW1 - M AH0 N
+ABDOMEN(2)  AE1 B - D AH0 - M AH0 N
+ABDOMINAL  AE0 B - D AA1 - M AH0 - N AH0 L
+ABDOMINAL(2)  AH0 B - D AA1 - M AH0 - N AH0 L
+ABDUCT  AE0 B - D AH1 K T
+ABDUCTED  AE0 B - D AH1 K - T IH0 D
+ABDUCTED(2)  AH0 B - D AH1 K - T IH0 D
+ABDUCTEE  AE0 B - D AH2 K - T IY1
+ABDUCTEES  AE0 B - D AH2 K - T IY1 Z
+ABDUCTING  AE0 B - D AH1 K - T IH0 NG
+ABDUCTING(2)  AH0 B - D AH1 K - T IH0 NG
+ABDUCTION  AE0 B - D AH1 K - SH AH0 N
+ABDUCTION(2)  AH0 B - D AH1 K - SH AH0 N
+ABDUCTIONS  AE0 B - D AH1 K - SH AH0 N Z
+ABDUCTIONS(2)  AH0 B - D AH1 K - SH AH0 N Z
+ABDUCTOR  AE0 B - D AH1 K - T ER0
+ABDUCTOR(2)  AH0 B - D AH1 K - T ER0
+ABDUCTORS  AE0 B - D AH1 K - T ER0 Z
+ABDUCTORS(2)  AH0 B - D AH1 K - T ER0 Z
+ABDUCTS  AE0 B - D AH1 K T S
+ABDUL  AE0 B - D UW1 L
+ABDULAZIZ  AE0 B - D UW2 - L AH0 - Z IY1 Z
+ABDULLA  AA0 B - D UW1 - L AH0
+ABDULLAH  AE2 B - D AH1 - L AH0
+ABE  EY1 B
+ABED  AH0 - B EH1 D
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+ANTI-FEDERALISTS(3)  AE2 N - T IY0 - F EH1 - D R AH0 - L AH0 S
+ANTI-INFECTIVE  AE1 N - T IY0 - IH0 N - F EH1 K - T IH0 V
+ANTIABORTION  AE1 N - T IY0 - AH0 - B AO1 R - SH AH0 N
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+ANTIAIRCRAFT  AE2 N - T AY0 - EH1 R - K R AE2 F T
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+ANTIBODIES  AE1 N - T IH0 - B AA2 - D IY0 Z
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+ANTIBODIES(3)  AE1 - N IH0 - B AA2 - D IY0 Z
+ANTIBODY  AE1 N - T IH0 - B AA2 - D IY0
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+ANTIC  AE1 N - T IH0 K
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+ANTICIPATE  AE0 N - T IH1 - S AH0 - P EY2 T
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+ANTICIPATING  AE0 N - T IH1 - S AH0 - P EY2 - T IH0 NG
+ANTICIPATION  AE0 N - T IH2 - S AH0 - P EY1 - SH AH0 N
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+ANTICORRUPTION  AE2 N - T AY2 - K ER0 - AH1 P - SH AH0 N
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+ANTICRIME  AE1 N - T IY0 - K R AY1 M
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+ANTIDISCRIMINATION  AE2 N - T IY0 - D IH0 - S K R IH2 - M AH0 - N EY1 - SH AH0 N
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+ANTIDRUG  AE2 N - T IH0 - D R AH1 G
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+ANTIFRAUD  AE1 N - T IY0 - F R AA2 D
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+ANTIFREEZE  AE1 N - T IY0 - F R IY2 Z
+ANTIFUNGAL  AE2 N - T AY2 - F AH1 NG - G AH0 L
+ANTIFUNGAL(2)  AE2 N - T IY2 - F AH1 NG - G AH0 L
+ANTIGAY  AE2 N - T AY2 - G EY1
+ANTIGAY(2)  AE2 N - T IY2 - G EY1
+ANTIGEN  AE1 N - T AH0 - JH AH0 N
+ANTIGENS  AE1 N - T IH0 - JH AH0 N Z
+ANTIGONE  AE0 - T IH1 - G AH0 - N IY0
+ANTIGONE'S  AE0 N - T IH1 - G AH0 - N IY2 Z
+ANTIGONES  AE0 N - T IH1 - G AH0 - N IY2 Z
+ANTIGOVERNMENT  AE2 N - T IY0 - G AH1 - V ER0 - M AH0 N T
+ANTIGOVERNMENT(2)  AE2 N - T AY0 - G AH1 - V ER0 - M AH0 N T
+ANTIGUA  AE0 N - T IY1 - G W AH0
+ANTIHISTAMINE  AE2 N - T IY0 - HH IH1 - S T AH0 - M AH0 N
+ANTIHISTAMINES  AE2 N - T IY0 - HH IH1 - S T AH0 - M AH0 N Z
+ANTIKNOCK  AE2 N - T IY0 - N AA1 K
+ANTILL  AE0 N - T IH1 L
+ANTILLA  AA0 N - T IH1 - L AH0
+ANTILLES  AE0 N - T IH1 - L IY0 Z
+ANTILOCK  AE1 N - T IY0 - L AA1 K
+ANTILOCK(2)  AE1 N - T AY0 - L AA1 K
+ANTIMISSILE  AE2 N - T AY2 - M IH1 - S AH0 L
+ANTIOCH  AE1 N - T IY0 - AA2 K
+ANTIOXIDANT  AE2 N - T IY0 - AA1 K - S AH0 - D AH0 N T
+ANTIOXIDANTS  AE2 N - T IY0 - AA1 K - S AH0 - D AH0 N T S
+ANTIPATHIES  AE0 N - T IH1 - P AH0 - TH IY0 Z
+ANTIPATHY  AE0 N - T IH1 - P AH0 - TH IY0
+ANTIPERSONELL  AE0 N - T AY2 - P ER0 - S AH0 - N EH1 L
+ANTIPHON  AE1 N - T AH0 - F AA2 N
+ANTIPHON(2)  AE1 N - T IH0 - F AA2 N
+ANTIPHONS  AE1 N - T AH0 - F AA2 N Z
+ANTIPHONS(2)  AE1 N - T IH0 - F AA2 N Z
+ANTIPODAL  AE0 N - T IH1 - P AH0 - D AH0 L
+ANTIPOVERTY  AE2 N - T AY0 - P AA1 - V ER0 - T IY0
+ANTIPOVERTY(2)  AE2 N - T IY0 - P AA1 - V ER0 - T IY0
+ANTIQUATE  AE1 N - T AH0 - K W EY2 T
+ANTIQUATED  AE1 N - T AH0 - K W EY2 - T AH0 D
+ANTIQUATED(2)  AE1 N - T AH0 - K W EY2 - T IH0 D
+ANTIQUE  AE0 N - T IY1 K
+ANTIQUES  AE0 N - T IY1 K S
+ANTIQUITIES  AE0 N - T IH1 - K W AH0 - T IY0 Z
+ANTIQUITY  AE0 N - T IH1 - K W AH0 - T IY0
+ANTIREFORMER  AE2 N - T IY0 - R IH0 - F AO1 R - M ER0
+ANTIREFORMER(2)  AE2 N - T AY0 - R IH0 - F AO1 R - M ER0
+ANTIREFORMERS  AE2 N - T IY0 - R IH0 - F AO1 R - M ER0 Z
+ANTIREFORMERS(2)  AE2 N - T AY0 - R IH0 - F AO1 R - M ER0 Z
+ANTIS  AE1 N - T AY0 Z
+ANTISENSE  AE1 N - T IY0 - S EH2 N S
+ANTISENSE(2)  AE1 N - T AY0 - S EH2 N S
+ANTISEPTIC  AE2 N - T AH0 - S EH1 P - T IH0 K
+ANTISMOKING  AE1 N - T IY0 S - M OW1 - K IH0 NG
+ANTISMOKING(2)  AE1 N - T AY0 S - M OW1 - K IH0 NG
+ANTISOCIAL  AE2 N - T IH0 - S OW1 - SH AH0 L
+ANTISOCIAL(2)  AE2 N - T AY0 - S OW1 - SH AH0 L
+ANTISUBMARINE  AE2 N - T IH0 - S AH1 B - M ER0 - IY2 N
+ANTISUBMARINE(2)  AE2 N - T AY0 - S AH1 B - M ER0 - IY2 N
+ANTITAKEOVER  AE2 N - T IY0 - T EY1 K - OW2 - V ER0
+ANTITANK  AE2 N - T IY0 - T AE1 NG K
+ANTITAX  AE2 N - T AY2 - T AE1 K S
+ANTITAX(2)  AE2 N - T IY2 - T AE1 K S
+ANTITHEFT  AE2 N - T AY2 - TH EH1 F T
+ANTITHEFT(2)  AE2 N - T IY2 - TH EH1 F T
+ANTITHESIS  AE0 N - T IH1 - TH AH0 - S AH0 S
+ANTITHETICAL  AE2 N - T AH0 - TH EH1 - T IH0 - K AH0 L
+ANTITOXIN  AE2 N - T IY0 - T AA1 K - S AH0 N
+ANTITOXINS  AE2 N - T IY0 - T AA1 K - S AH0 N Z
+ANTITRUST  AE2 N - T AY0 - T R AH1 S T
+ANTIVIRAL  AE2 N - T IY0 - V AY1 - R AH0 L
+ANTIWAR  AE2 N - T AY0 - W AO1 R
+ANTIWAR(2)  AE2 N - T IY0 - W AO1 R
+ANTKOWIAK  AH0 N T - K AW1 - IY0 - AE0 K
+ANTLE  AE1 N - T AH0 L
+ANTLER  AE1 N T - L ER0
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+ANTLERS  AE1 N T - L ER0 Z
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+ANTOINE  AA0 N T - W AA1 N
+ANTOINETTE  AE2 N - T W AH0 - N EH1 T
+ANTOL  AA0 N - T AO1 L
+ANTOLIK  AE1 N - T AH0 - L IH0 K
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+ANTON  AE1 N - T AO2 N
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+ANTONE  AA0 N - T OW1 - N IY0
+ANTONELLI  AA0 N - T OW0 - N EH1 - L IY0
+ANTONELLIS  AE0 N - T AH0 - N EH1 - L IH0 S
+ANTONETTI  AA0 N - T OW0 - N EH1 - T IY0
+ANTONI  AA0 N - T OW1 - N IY0
+ANTONIA  AE0 N - T OW1 - N IY0 - AH0
+ANTONIN  AE1 N - T AH0 - N IH0 N
+ANTONINI  AA0 N - T OW0 - N IY1 - N IY0
+ANTONINI'S  AA0 N - T OW0 - N IY1 - N IY0 Z
+ANTONIO  AE0 N - T OW1 - N IY0 - OW0
+ANTONIO'S  AE0 N - T OW1 - N IY0 - OW2 Z
+ANTONIOU  AA0 N - T OW0 - N IY1 - UW0
+ANTONIU  AE2 N - T OW1 - N IY0 - UW0
+ANTONIU'S  AE0 N - T OW1 - N IY0 - UW0 Z
+ANTONIUS  AE0 N - T OW1 - N IY0 - AH0 S
+ANTONOPOULOS  AE0 N - T AH0 - N AA1 - P AH0 - L IH0 S
+ANTONOVICH  AE2 N - T AA1 - N AH0 - V IH0 CH
+ANTONSEN  AH0 N - T AA1 N - S AH0 N
+ANTONSON  AE1 N - T AH0 N - S AH0 N
+ANTONUCCI  AA0 N - T OW0 - N UW1 - CH IY0
+ANTONY  AE1 N - T AH0 - N IY0
+ANTOON  AE2 N - T UW1 N
+ANTOS  AA1 N - T OW0 Z
+ANTOSH  AH0 N - T AA1 SH
+ANTRIL  AE1 N - T R IH0 L
+ANTRIM  AE1 N - T R IH0 M
+ANTROBUS  AE1 N - T R AH0 - B IH0 S
+ANTS  AE1 N T S
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+ANTUNA  AA0 N - T UW1 - N AH0
+ANTUNES  AA0 N - T UW1 - N EH0 S
+ANTUNEZ  AA0 N - T UW1 - N EH0 Z
+ANTWERP  AE1 N T - W ER0 P
+ANTWINE  AE1 N - T W AY2 N
+ANVIL  AE1 N - V AH0 L
+ANWAR  AE1 N - W AA0 R
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+ANWAY  AH0 N - W EY1
+ANWELL  AH0 N - W EH1 L
+ANWYL  AE1 N - W IH0 L
+ANWYLL  AE1 N - W IH0 L
+ANXIETIES  AE0 NG - Z AY1 - AH0 - T IY0 Z
+ANXIETY  AE0 NG - Z AY1 - AH0 - T IY0
+ANXIOUS  AE1 NG K - SH AH0 S
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+ANXIOUSLY  AE1 NG K - SH AH0 S - L IY0
+ANY  EH1 - N IY0
+ANYBODY  EH1 - N IY0 - B AH0 - D IY0
+ANYBODY'S  EH1 - N IY0 - B AH0 - D IY0 Z
+ANYHOW  EH1 - N IY0 - HH AW2
+ANYMORE  EH2 - N IY0 - M AO1 R
+ANYON  EH1 - N IY0 - AA0 N
+ANYONE  EH1 - N IY0 - W AH2 N
+ANYONE'S  EH1 - N IY0 - W AH2 N Z
+ANYONE(2)  EH1 - N IY0 - W AH0 N
+ANYPLACE  EH1 - N IY0 - P L EY2 S
+ANYTHING  EH1 - N IY0 - TH IH2 NG
+ANYTHING'S  EH1 - N IY0 - TH IH2 NG Z
+ANYTIME  EH1 - N IY0 - T AY2 M
+ANYWAY  EH1 - N IY0 - W EY2
+ANYWAYS  EH1 - N IY0 - W EY2 Z
+ANYWHERE  EH1 - N IY0 - W EH2 R
+ANYWHERE(2)  EH1 - N IY0 HH - W EH2 R
+ANZA  AE1 N - Z AH0
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+ANZELMO  AA0 N - Z EH1 L - M OW0
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+AOKI  EY0 - OW1 - K IY0
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+AOL(2)  AH0 - M ER1 - IH0 - K AH0 - AA1 N - L AY2 N
+AON  EY1 - OW0 N
+AORTA  EY0 - AO1 R - T AH0
+AORTIC  EY0 - AO1 R - T IH0 K
+AOSHIMA  AW2 - SH IY1 - M AH0
+AOSHIMA(2)  EY2 - OW0 - SH IY1 - M AH0
+AOUN  AW1 - AH0 N
+AOUN'S  AW1 - AH0 N Z
+AOUN'S(2)  AW2 - UW1 N Z
+AOUN(2)  AW2 - UW1 N
+AOUZOU  AW2 - Y UW1 - Z UW0
+AOYAMA  AW2 - Y AA1 - M AH0
+AOYAMA(2)  EY2 - OW0 - Y AA1 - M AH0
+APACE  AH0 - P EY1 S
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+APACHE'S  AH0 - P AE1 - CH IY0 Z
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+APALACHICOLA'S  AE2 - P AH0 - L AE2 - CH AH0 - K OW1 - L AH0 Z
+APARICIO  AE2 - P ER0 - IH1 - S IY0 - OW0
+APART  AH0 - P AA1 R T
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+APARTMENT  AH0 - P AA1 R T - M AH0 N T
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+APATHETIC  AE2 - P AH0 - TH EH1 - T IH0 K
+APATHY  AE1 - P AH0 - TH IY0
+APATITE  AE1 - P AH0 - T AY2 T
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+APC  EY1 - P IY1 - S IY1
+APC'S  EY1 - P IY1 - S IY1 Z
+APCAR  AE1 P - K AA0 R
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+APEL  AA0 - P EH1 L
+APELIKE  EY1 - P L AY2 K
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+APERTURE  AE1 - P ER0 - CH ER0
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+APFEL  AE1 P - F AH0 L
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+APGAR  AE1 P - G ER0
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+APHID(2)  EY1 - F AH0 D
+APHIDS  AE1 - F IH0 D Z
+APHIDS(2)  EY1 - F AH0 D Z
+APHORISM  AE1 - F ER0 - IH2 - Z AH0 M
+APHORISMS  AE1 - F ER0 - IH2 - Z AH0 M Z
+APHRODISIAC  AE2 - F R OW0 - D IY1 - Z IY0 - AE0 K
+APHRODITE  AE2 - F R AH0 - D AY1 - T IY0
+APHRODITE'S  AE2 - F R AH0 - D AY1 - T IY0 Z
+APHRODITES  AE2 - F R AH0 - D AY1 - T IY0 Z
+APICELLA  AE2 - P IH0 - S EH1 - L AH0
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+APLOMB  AH0 - P L AA1 M
+APNEA  AE1 P - N IY0 - AH0
+APOCALYPSE  AH0 - P AA1 - K AH0 - L IH2 P S
+APOCALYPTIC  AH0 - P AA2 - K AH0 - L IH1 P - T IH0 K
+APOCRYPHAL  AH0 - P AA1 - K R AH0 - F AH0 L
+APODACA  AA0 - P OW0 - D AA1 - K AH0
+APOGEE  AE1 - P AH0 - JH IY2
+APOLITICAL  EY2 - P AH0 - L IH1 - T IH0 - K AH0 L
+APOLLINE  AE1 - P AH0 - L AY2 N
+APOLLINIAN  AE2 - P AH0 - L IH1 - N IY0 - AH0 N
+APOLLO  AH0 - P AA1 - L OW0
+APOLLO'S  AH0 - P AA1 - L OW0 Z
+APOLLONIAN  AE2 - P AH0 - L OW1 - N IY0 - AH0 N
+APOLOGETIC  AH0 - P AA2 - L AH0 - JH EH1 - T IH0 K
+APOLOGETICALLY  AH0 - P AA2 - L AH0 - JH EH1 - T IH0 K - L IY0
+APOLOGIES  AH0 - P AA1 - L AH0 - JH IY0 Z
+APOLOGIST  AH0 - P AA1 - L AH0 - JH AH0 S T
+APOLOGISTS  AH0 - P AA1 - L AH0 - JH AH0 S T S
+APOLOGISTS(2)  AH0 - P AA1 - L AH0 - JH AH0 S S
+APOLOGISTS(3)  AH0 - P AA1 - L AH0 - JH AH0 S
+APOLOGIZE  AH0 - P AA1 - L AH0 - JH AY2 Z
+APOLOGIZED  AH0 - P AA1 - L AH0 - JH AY2 Z D
+APOLOGIZES  AH0 - P AA1 - L AH0 - JH AY2 - Z IH0 Z
+APOLOGIZING  AH0 - P AA1 - L AH0 - JH AY2 - Z IH0 NG
+APOLOGY  AH0 - P AA1 - L AH0 - JH IY0
+APONTE  AH0 - P AA1 N - T IY0
+APOPA  AH0 - P OW1 - P AH0
+APOPKA  AH0 - P AO1 P - K AH0
+APOPLECTIC  AE2 - P AH0 - P L EH1 K - T IH0 K
+APOPLEXY  AE1 - P AH0 - P L EH2 K - S IY0
+APOSTLE  AH0 - P AA1 - S AH0 L
+APOSTLES  AH0 - P AA1 - S AH0 L Z
+APOSTOL  AE1 - P AH0 - S T AH0 L
+APOSTOLOPOUL  AH0 - P AA2 - S T OW0 - L OW0 - P UW1 L
+APOSTROPHE  AH0 - P AA1 S - T R AH0 - F IY0
+APOTHECARY  AH0 - P AA1 - TH AH0 - K EH2 - R IY0
+APOTHEOSIS  AH0 - P AA2 - TH IY0 - OW1 - S AH0 S
+APP  AE1 P
+APPALACHIA  AE2 - P AH0 - L AE1 - CH IY0 - AH0
+APPALACHIAN  AE2 - P AH0 - L EY1 - CH AH0 N
+APPALACHIAN(2)  AE2 - P AH0 - L EY1 - SH AH0 N
+APPALACHIAN(3)  AE2 - P AH0 - L AE1 - CH AH0 N
+APPALACHIANS  AE2 - P AH0 - L EY1 - CH AH0 N Z
+APPALACHIANS(2)  AE2 - P AH0 - L EY1 - SH AH0 N Z
+APPALACHIANS(3)  AE1 - P AH0 - L AE1 - CH AH0 N Z
+APPALL  AH0 - P AO1 L
+APPALLED  AH0 - P AO1 L D
+APPALLING  AH0 - P AO1 - L IH0 NG
+APPALLINGLY  AH0 - P AO1 - L IH0 NG - L IY0
+APPALLS  AH0 - P AO1 L Z
+APPARATCHIK  AE2 - P ER0 - AE1 - CH IH0 K
+APPARATCHIKS  AE2 - P ER0 - AE1 - CH IH0 K S
+APPARATUS  AE2 - P ER0 - AE1 - T AH0 S
+APPARATUSES  AE2 - P ER0 - AE1 - T AH0 - S AH0 Z
+APPAREL  AH0 - P AE1 - R AH0 L
+APPAREL(2)  AH0 - P EH1 - R AH0 L
+APPARENT  AH0 - P EH1 - R AH0 N T
+APPARENTLY  AH0 - P EH1 - R AH0 N T - L IY0
+APPARITION  AE2 - P ER0 - IH1 - SH AH0 N
+APPARITIONS  AE2 - P ER0 - IH1 - SH AH0 N Z
+APPEAL  AH0 - P IY1 L
+APPEALABLE  AH0 - P IY1 - L AH0 - B AH0 L
+APPEALED  AH0 - P IY1 L D
+APPEALING  AH0 - P IY1 - L IH0 NG
+APPEALINGLY  AH0 - P IY1 - L IH0 NG - L IY0
+APPEALS  AH0 - P IY1 L Z
+APPEAR  AH0 - P IH1 R
+APPEARANCE  AH0 - P IH1 - R AH0 N S
+APPEARANCES  AH0 - P IH1 - R AH0 N - S AH0 Z
+APPEARED  AH0 - P IH1 R D
+APPEARING  AH0 - P IH1 - R IH0 NG
+APPEARS  AH0 - P IH1 R Z
+APPEASE  AH0 - P IY1 Z
+APPEASED  AH0 - P IY1 Z D
+APPEASEMENT  AH0 - P IY1 Z - M AH0 N T
+APPEASING  AH0 - P IY1 - Z IH0 NG
+APPEL  AE1 - P AH0 L
+APPELBAUM  AE1 - P AH0 L - B AW2 M
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+APPELLATION  AE2 - P AH0 - L EY1 - SH AH0 N
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+APPENDED  AH0 - P EH1 N - D IH0 D
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+APPENZELLER  AE1 - P IH0 N - Z AH0 L - ER0
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+APPETITES  AE1 - P AH0 - T AY2 T S
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+APPETIZER  AE1 - P AH0 - T AY2 - Z ER0
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+APPLAUDING  AH0 - P L AO1 - D IH0 NG
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+APPLEBEE  AE1 - P AH0 L - B IY2
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+APPLEBERRY  AE1 - P AH0 L - B EH2 - R IY0
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+APPLICABLE  AE1 - P L AH0 - K AH0 - B AH0 L
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+APPLICANTS  AE1 - P L IH0 - K AH0 N T S
+APPLICANTS'  AE1 - P L AH0 - K AH0 N T S
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+APPLICATIONS  AE2 - P L AH0 - K EY1 - SH AH0 N Z
+APPLICATOR  AE1 - P L AH0 - K EY2 - T ER0
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+APPLIED  AH0 - P L AY1 D
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+APPLIN  AE1 - P L IH0 N
+APPLING  AE1 - P AH0 L - IH0 NG
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+APPLY  AH0 - P L AY1
+APPLYING  AH0 - P L AY1 - IH0 NG
+APPOINT  AH0 - P OY1 N T
+APPOINTED  AH0 - P OY1 N - T AH0 D
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+APPOINTEE  AH0 - P OY0 N - T IY1
+APPOINTEE(2)  AH0 - P OY1 N - T IY0
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+APPOINTEES(2)  AH0 - P OY1 N - T IY0 Z
+APPOINTING  AH0 - P OY1 N - T IH0 NG
+APPOINTIVE  AH0 - P OY1 N - T IH0 V
+APPOINTMENT  AH0 - P OY1 N T - M AH0 N T
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+APPORTION  AH0 - P AO1 R - SH AH0 N
+APPORTIONED  AH0 - P AO1 R - SH AH0 N D
+APPORTIONING  AH0 - P AO1 R - SH AH0 N - IH0 NG
+APPORTIONMENT  AH0 - P AO1 R - SH AH0 N - M AH0 N T
+APPRAISAL  AH0 - P R EY1 - Z AH0 L
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+APPRAISE  AH0 - P R EY1 Z
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+APPREHEND  AE2 - P R IH0 - HH EH1 N D
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+APPREHENSION  AE2 - P R IH0 - HH EH1 N - SH AH0 N
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+APPRENTICE  AH0 - P R EH1 N - T AH0 S
+APPRENTICE(2)  AH0 - P R EH1 N - T IH0 S
+APPRENTICED  AH0 - P R EH1 N - T AH0 S T
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+APPRENTICESHIP  AH0 - P R EH1 N - T AH0 S - SH IH2 P
+APPRENTICESHIPS  AH0 - P R EH1 N - T AH0 S - SH IH2 P S
+APPRISE  AH0 - P R AY1 Z
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+APPROACH  AH0 - P R OW1 CH
+APPROACHABLE  AH0 - P R OW1 - CH AH0 - B AH0 L
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+APPROPRIATED  AH0 - P R OW1 - P R IY0 - EY2 - T IH0 D
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+BALKANIZED  B AO1 L - K AH0 - N AY2 Z D
+BALKANS  B AO1 L - K AH0 N Z
+BALKCOM  B AE1 L - K AH0 M
+BALKE  B EY1 L K
+BALKED  B AO1 K T
+BALKIN  B AE1 L - K IH0 N
+BALKING  B AO1 - K IH0 NG
+BALKO  B AE1 L - K OW0
+BALKS  B AO1 K S
+BALKY  B AO1 - K IY0
+BALL  B AO1 L
+BALL'S  B AO1 L Z
+BALLA  B AE1 - L AH0
+BALLAD  B AE1 - L AH0 D
+BALLADE  B AH0 - L AA1 D
+BALLADS  B AE1 - L AH0 D Z
+BALLADUR  B AE1 - L AH0 - D ER0
+BALLADUR'S  B AE1 - L AH0 - D ER0 Z
+BALLANCE  B AA1 - L AH0 N S
+BALLANTINE  B AE1 - L AH0 N - T AY2 N
+BALLANTRAE  B AE1 - L AH0 N - T R EY2
+BALLANTYNE  B AH0 - L AE1 N - T AY0 N
+BALLARD  B AE1 - L ER0 D
+BALLARD'S  B AE1 - L ER0 D Z
+BALLAS  B AE1 - L AH0 Z
+BALLAST  B AE1 - L AH0 S T
+BALLASTS  B AE1 - L AH0 S T S
+BALLASTS(2)  B AE1 - L AH0 S S
+BALLASTS(3)  B AE1 - L AH0 S
+BALLCLUB  B AO1 L - K L AH0 B
+BALLCOCK  B AO1 L - K AA1 K
+BALLCOCKS  B AO1 L - K AA1 K S
+BALLE  B EY1 L
+BALLED  B AO1 L D
+BALLENGEE  B AH0 - L EH1 NG - G IY0
+BALLENGER  B AE1 - L IH0 N - JH ER0
+BALLENTINE  B AA0 - L EH0 N - T IY1 - N IY0
+BALLER  B AO1 - L ER0
+BALLERINA  B AE2 - L ER0 - IY1 - N AH0
+BALLERINAS  B AE2 - L ER0 - IY1 - N AH0 Z
+BALLES  B EY1 L Z
+BALLESTER  B AE1 - L IH0 - S T ER0
+BALLESTEROS  B AE1 - L IH0 - S T ER0 - OW0 Z
+BALLESTEROS(2)  B AH0 - L EH1 - S T ER0 - OW0 S
+BALLET  B AE0 - L EY1
+BALLET'S  B AE0 - L EY1 Z
+BALLETS  B AE0 - L EY1 Z
+BALLETTO  B AE2 - L EH1 - T OW0
+BALLEW  B AE1 - L UW0
+BALLGAME  B AO0 L - G EY1 M
+BALLI  B AE1 - L IY0
+BALLIET  B AE1 - L IY0 - IH0 T
+BALLIETT  B AE1 - L IY2 T
+BALLIN  B AE1 - L IH0 N
+BALLING  B AO1 - L IH0 NG
+BALLINGER  B AO1 - L IH2 N - JH ER0
+BALLISTIC  B AH0 - L IH1 - S T IH0 K
+BALLISTICS  B AH0 - L IH1 - S T IH0 K S
+BALLMAN  B AO1 L - M AH0 N
+BALLMER  B AE1 L - M ER0
+BALLO  B AE1 - L OW0
+BALLON  B AE1 - L AH0 N
+BALLOON  B AH0 - L UW1 N
+BALLOONED  B AH0 - L UW1 N D
+BALLOONING  B AH0 - L UW1 - N IH0 NG
+BALLOONIST  B AH0 - L UW1 - N IH0 S T
+BALLOONISTS  B AH0 - L UW1 - N IH0 S T S
+BALLOONS  B AH0 - L UW1 N Z
+BALLOR  B AO1 - L ER0
+BALLOT  B AE1 - L AH0 T
+BALLOTING  B AE1 - L AH0 - T IH0 NG
+BALLOTS  B AE1 - L AH0 T S
+BALLOU  B AH0 - L UW1
+BALLOW  B AE1 - L OW0
+BALLOWE  B AE1 - L AW0
+BALLPARK  B AO1 L - P AA2 R K
+BALLPARKS  B AO1 L - P AA2 R K S
+BALLPLAYER  B AO1 L - P L EY2 - ER0
+BALLPLAYERS  B AO0 L - P L EY1 - ER0 Z
+BALLPOINT  B AO1 L - P OY0 N T
+BALLPOINTS  B AO1 L - P OY0 N T S
+BALLROOM  B AO1 L - R UW2 M
+BALLROOMS  B AO1 L - R UW2 M Z
+BALLS  B AO1 L Z
+BALLWEG  B AE1 L - W IH0 G
+BALLY  B AE1 - L IY0
+BALLY'S  B AE1 - L IY0 Z
+BALLY'S(2)  B EY1 - L IY0 Z
+BALLY(2)  B EY1 - L IY0
+BALLYHOO  B AE1 - L IY0 - HH UW1
+BALLYHOOED  B AE1 - L IY0 - HH UW1 D
+BALM  B AA1 M
+BALM(2)  B AA1 L M
+BALMER  B AA1 - M ER0
+BALMES  B AA1 L - M EH0 S
+BALMORAL  B AE0 L - M AO1 - R AH0 L
+BALMORALS  B AE0 L - M AO1 - R AH0 L Z
+BALMS  B AA1 M Z
+BALMS(2)  B AA1 L M Z
+BALMY  B AA1 - M IY0
+BALODIA  B AH0 - L OW1 - D IY0 - AH0
+BALOG  B AE1 - L AO0 G
+BALOGA  B AA0 - L OW1 - G AH0
+BALOGH  B AE1 - L OW0
+BALON  B AA0 - L AO1 N
+BALONEY  B AH0 - L OW1 - N IY0
+BALOW  B AE1 - L OW0
+BALSA  B AO1 L - S AH0
+BALSAM  B AO1 L - S AH0 M
+BALSAMO  B AA0 L - S AA1 - M OW0
+BALSBAUGH  B AO1 L Z - B AO2
+BALSER  B EY1 L - S ER0
+BALSIGER  B AE1 L - S IH0 - G ER0
+BALSLEY  B AE1 L S - L IY0
+BALSTER  B AE1 L - S T ER0
+BALT'S  B AO1 L T S
+BALTAZAR  B AA0 L - T AA0 - Z AA1 R
+BALTER  B AO1 L - T ER0
+BALTES  B EY1 L T S
+BALTHASAR  B AE1 L - TH AH0 - S ER0
+BALTHASER  B AE1 L - TH AH0 - S ER0
+BALTHAZAR  B AE1 L - TH AH0 - Z ER0
+BALTHAZOR  B AA0 L - TH AA0 - Z AO1 R
+BALTHROP  B AE1 L - TH R AH0 P
+BALTIC  B AO1 L - T IH0 K
+BALTICA  B AE1 L - T IH0 - K AH0
+BALTICS  B AO1 L - T IH0 K S
+BALTIERRA  B AA0 L - T IH1 - R AH0
+BALTIMORE  B AO1 L - T AH0 - M AO2 R
+BALTIMORE'S  B AO1 L - T AH0 - M AO2 R Z
+BALTO  B AA1 L - T OW0
+BALTODANO  B AO2 L - T OW0 - D AA1 - N OW0
+BALTSA  B AO1 L T - S AH0
+BALTZ  B AE1 L T S
+BALTZELL  B AE1 L T - Z AH0 L
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+BALUCHI  B AH0 - L UW1 - CH IY0
+BALUJA  B AH0 - L UW1 - JH AH0
+BALUKAS  B AH0 - L UW1 - K AH0 Z
+BALYEAT  B AE2 - L IY0 - AE1 T
+BALZ  B AO1 L Z
+BALZANO  B AA0 L - Z AA1 - N OW0
+BALZARINI  B AA0 L - Z AA0 - R IY1 - N IY0
+BALZER  B EY1 L - Z ER0
+BAM  B AE1 M
+BAMBA  B AE1 M - B AH0
+BAMBACH  B AE1 M - B AA2 K
+BAMBENEK  B AE0 M - B EH1 - N EH0 K
+BAMBER  B AE1 M - B ER0
+BAMBERG  B AE1 M - B ER0 G
+BAMBERGER  B AE1 M - B ER0 - G ER0
+BAMBI  B AE1 M - B IY0
+BAMBINO  B AE2 M - B IY1 - N OW0
+BAMBINOS  B AE2 M - B IY1 - N OW0 Z
+BAMBOO  B AE0 M - B UW1
+BAMBRICK  B AE1 M - B R IH0 K
+BAMBURG  B AE1 M - B ER0 G
+BAME  B EY1 M
+BAMFORD  B AE1 M - F ER0 D
+BAMUT  B AE1 - M AH0 T
+BAN  B AE1 N
+BANACCI  B AH0 - N AA1 - CH IY0
+BANACH  B AE1 - N AH0 K
+BANAL  B AH0 - N AA1 L
+BANALITIES  B AH0 - N AE1 - L IH0 - T IY0 Z
+BANALITY  B AH0 - N AE1 - L IH0 - T IY0
+BANAMEX  B AE1 - N AH0 - M EH2 K S
+BANANA  B AH0 - N AE1 - N AH0
+BANANAS  B AH0 - N AE1 - N AH0 Z
+BANAS  B AE1 - N AH0 Z
+BANASIAK  B AH0 - N AA1 - S IY0 - AE0 K
+BANASZAK  B AH0 - N AA1 - SH AH0 K
+BANBURY  B AE1 N - B EH2 - R IY0
+BANC  B AE1 NG K
+BANCA  B AE1 NG - K AH0
+BANCA(2)  B AA1 NG - K AH0
+BANCAIRE  B AE0 N - K EH1 R
+BANCARIO  B AE0 N - K EH1 - R IY0 - OW0
+BANCO  B AE1 NG - K OW0
+BANCOKLAHOMA  B AE0 NG - K AA2 K - L AH0 - HH OW1 - M AH0
+BANCOMER  B AE1 NG - K AH0 - M ER0
+BANCOR  B AE1 N - K AO2 R
+BANCORP  B AE1 NG - K AO0 R P
+BANCORP'S  B AE1 NG - K AO0 R P S
+BANCORP'S(2)  B AE1 N - K AO0 R P S
+BANCORP(2)  B AE1 N - K AO0 R P
+BANCORPORATION  B AE1 N - K AO2 R - P ER0 - EY0 - SH AH0 N
+BANCROFT  B AE1 NG - K R AO0 F T
+BANCROFT'S  B AE1 N - K R AO2 F T S
+BANCSERVE  B AE1 N K - S ER0 V
+BANCSHARES  B AE1 NG K - SH EH0 R Z
+BANCSHARES'  B AE0 NG K - SH EH1 R Z
+BANCTEC  B AE1 NG K - T EH2 K
+BANCTEXAS  B AE0 NG K - T EH1 K - S AH0 S
+BAND  B AE1 N D
+BAND'S  B AE1 N D Z
+BANDA  B AE1 N - D AH0
+BANDAG  B AE1 N - D AE2 G
+BANDAGE  B AE1 N - D IH0 JH
+BANDAGED  B AE1 N - D AH0 JH D
+BANDAGES  B AE1 N - D AH0 - JH AH0 Z
+BANDAGES(2)  B AE1 N - D IH0 - JH IH0 Z
+BANDAI  B AE2 N - D AY1
+BANDAID  B AE1 N - D EY0 D
+BANDANA  B AE2 N - D AE1 - N AH0
+BANDANAS  B AE2 N - D AE1 - N AH0 Z
+BANDAR  B AE1 N - D AA0 R
+BANDED  B AE1 N - D IH0 D
+BANDEL  B AE1 N - D AH0 L
+BANDEMER  B AE1 N - D IY0 - M ER0
+BANDER  B AE1 N - D ER0
+BANDERAS  B AE0 N - D ER1 - AH0 S
+BANDERAS(2)  B AA0 N - D ER0 - AH1 S
+BANDICOOTS  B AE1 N - D IH0 - K UW2 T S
+BANDICOOTS(2)  B AE1 N - D IY0 - K UW2 T S
+BANDIED  B AE1 N - D IY0 D
+BANDING  B AE1 N - D IH0 NG
+BANDIT  B AE1 N - D AH0 T
+BANDITRY  B AE1 N - D AH0 - T R IY0
+BANDITS  B AE1 N - D AH0 T S
+BANDLEADER  B AE1 N D - L IY0 - D ER0
+BANDLEADERS  B AE1 N D - L IY0 - D ER0 Z
+BANDOLIER  B AE2 N - D AH0 - L IH1 R
+BANDOLIERS  B AE2 N - D AH0 - L IH1 R Z
+BANDOW  B AE1 N - D AW2
+BANDOW'S  B AE1 N - D AW2 Z
+BANDS  B AE1 N D Z
+BANDSHELL  B AE0 N D - SH EH1 L
+BANDSTAND  B AE1 N D - S T AE2 N D
+BANDT  B AE1 N T
+BANDUCCI  B AA0 N - D UW1 - CH IY0
+BANDWAGON  B AE1 N D - W AE2 - G AH0 N
+BANDWIDTH  B AE1 N D - W IH0 D TH
+BANDY  B AE1 N - D IY0
+BANE  B EY1 N
+BANEGAS  B AE1 - N IH0 - G AH0 Z
+BANERJEE  B AH0 - N ER1 - JH IY0
+BANES  B EY1 N Z
+BANESTO  B AH0 - N EH1 - S T OW0
+BANESTO'S  B AH0 - N EH1 - S T OW0 Z
+BANET  B AE1 - N IH0 T
+BANEY  B EY1 - N IY0
+BANFF  B AE1 N F
+BANFIELD  B AE1 N - F IY2 L D
+BANFORD  B AE1 N - F ER0 D
+BANG  B AE1 NG
+BANGALORE  B AE1 NG - G AH0 - L AO2 R
+BANGALORE'S  B AE1 NG - G AH0 - L AO2 R Z
+BANGE  B AE1 N JH
+BANGED  B AE1 NG D
+BANGEE  B AE1 N - JH IY0
+BANGEMANN  B AE1 NG - G AH0 - M AH0 N
+BANGER  B AE1 - NG ER0
+BANGERS  B AE1 - NG ER0 Z
+BANGERT  B EY1 NG - G ER0 T
+BANGERTER  B EY1 NG - G ER0 - T ER0
+BANGHART  B AE1 NG - HH AA2 R T
+BANGING  B AE1 - NG IH0 NG
+BANGISH  B AE1 - NG IH0 SH
+BANGKOK  B AE0 NG - K AA1 K
+BANGKOK'S  B AE1 NG - K AA0 K S
+BANGKOK(2)  B AE1 NG - K AA0 K
+BANGLADESH  B AE1 NG - L AH0 - D EH2 SH
+BANGLADESH'S  B AE1 NG - L AH0 - D EH2 - SH IH0 Z
+BANGLADESHI  B AE1 NG - L AH0 - D EH2 - SH IY0
+BANGLADESHI'S  B AE1 NG - L AH0 - D EH2 - SH IY0 Z
+BANGLADESHIS  B AE1 NG - L AH0 - D EH2 - SH IY0 Z
+BANGLE  B AE1 NG - G AH0 L
+BANGO  B AA1 NG - G OW0
+BANGOR  B AE1 NG - G ER0
+BANGOR(2)  B AE1 NG - G AO2 R
+BANGS  B AE1 NG Z
+BANH  B AE1 N
+BANIA  B AA1 - N IY0 - AH0
+BANICK  B AE1 - N IH0 K
+BANIK  B AE1 - N IH0 K
+BANIS  B AE1 - N IH0 S
+BANISH  B AE1 - N IH0 SH
+BANISHED  B AE1 - N IH0 SH T
+BANISHING  B AE1 - N IH0 - SH IH0 NG
+BANISHMENT  B AE1 - N IH0 SH - M AH0 N T
+BANISTER  B AE1 - N IH0 - S T ER0
+BANJA  B AA1 - N Y AH0
+BANJO  B AE1 N - JH OW2
+BANK  B AE1 NG K
+BANK'S  B AE1 NG K S
+BANKABLE  B AE1 NG - K AH0 - B AH0 L
+BANKAMERICA  B AE2 NG - K AH0 - M EH1 - R IH0 - K AH0
+BANKAMERICA'S  B AE2 NG - K AH0 - M EH1 - R IH0 - K AH0 Z
+BANKATLANTIC  B AE2 NG K - AH0 T - L AE1 N - T IH0 K
+BANKCARD  B AE1 NG - K AA2 R D
+BANKCORP  B AE1 NG - K AO2 R P
+BANKE  B AE1 NG K
+BANKEAST  B AE2 NG - K IY1 S T
+BANKED  B AE1 NG K T
+BANKEN  B AE1 NG - K AH0 N
+BANKER  B AE1 NG - K ER0
+BANKER'S  B AE1 NG - K ER0 Z
+BANKERS  B AE1 NG - K ER0 Z
+BANKERS'  B AE1 NG - K ER0 Z
+BANKERT  B AE1 NG - K ER0 T
+BANKES  B AE1 NG K S
+BANKEY  B AE1 N - K IY2
+BANKHEAD  B AE1 NG K - HH EH2 D
+BANKHOLDING  B AE1 NG K - HH OW2 L - D IH0 NG
+BANKING  B AE1 NG - K IH0 NG
+BANKING'S  B AE1 NG - K IH0 NG Z
+BANKNOTE  B AE1 NG K - N OW2 T
+BANKNOTES  B AE1 NG K - N OW2 T S
+BANKO  B AE1 NG - K OW0
+BANKOWSKI  B AH0 NG - K AO1 F S - K IY0
+BANKROLL  B AE1 NG K - R OW2 L
+BANKROLLED  B AE1 NG K - R OW2 L D
+BANKROLLING  B AE1 NG K - R OW2 - L IH0 NG
+BANKROLLS  B AE1 NG K - R OW2 L Z
+BANKRUPCTY  B AE1 NG - K R AH0 P T - S IY0
+BANKRUPT  B AE1 NG - K R AH0 P T
+BANKRUPTCIES  B AE1 NG - K R AH0 P T - S IY0 Z
+BANKRUPTCY  B AE1 NG - K R AH0 P - S IY0
+BANKRUPTCY'S  B AE1 NG - K R AH0 P - S IY0 Z
+BANKRUPTCY(2)  B AE1 NG - K R AH0 P T - S IY0
+BANKRUPTED  B AE1 NG - K R AH0 P - T IH0 D
+BANKRUPTING  B AE1 NG - K R AH2 P - T IH0 NG
+BANKS  B AE1 NG K S
+BANKS'  B AE1 NG K S
+BANKS'S  B AE1 NG K - S IH0 Z
+BANKSHARE  B AE1 NG K - SH EH2 R
+BANKSHARES  B AE1 NG K - SH EH2 R Z
+BANKSON  B AE1 NG K - S AH0 N
+BANKSTON  B AE1 NG K - S T AH0 N
+BANKVEREIN  B AE1 NG K - V ER0 - AY2 N
+BANKVERMONT  B AE1 NG K - V ER0 - M AA1 N T
+BANKWORCESTER  B AE1 NG K - W ER1 - CH EH2 - S T ER0
+BANKWORCESTER(2)  B AE1 NG - K W UW1 - S T ER0
+BANN  B AE1 N
+BANNAN  B AE1 - N AH0 N
+BANNED  B AE1 N D
+BANNER  B AE1 - N ER0
+BANNER'S  B AE1 - N ER0 Z
+BANNERMAN  B AE1 - N ER0 - M AH0 N
+BANNERS  B AE1 - N ER0 Z
+BANNICK  B AE1 - N IH0 K
+BANNING  B AE1 - N IH0 NG
+BANNINGS  B AE1 - N IH0 NG Z
+BANNISTER  B AE1 - N AH0 - S T ER0
+BANNISTER(2)  B AE1 - N IH0 - S T ER0
+BANNON  B AE1 - N AH0 N
+BANOS  B AA1 - N OW0 Z
+BANOUN  B AH0 - N UW1 N
+BANPAIS  B AE2 N - P EY1
+BANPONCE  B AE1 N - P AA0 N S
+BANQUE  B AE1 NG K
+BANQUET  B AE1 NG - K W AH0 T
+BANQUETS  B AE1 NG - K W AH0 T S
+BANQUO'S  B AE1 NG - K W OW0 Z
+BANS  B AE1 N Z
+BANSAL  B AA0 N - S AE1 L
+BANSHEE  B AE0 N - SH IY1
+BANSHEE(2)  B AE1 N - SH IY0
+BANTA  B AE1 N - T AH0
+BANTAM  B AE1 N - T AH0 M
+BANTAM'S  B AE1 N - T AH0 M Z
+BANTAMS  B AE1 N - T AH0 M Z
+BANTER  B AE1 N - T ER0
+BANTERED  B AE1 N - T ER0 D
+BANTERING  B AE1 N - T ER0 - IH0 NG
+BANTLE  B AE1 N - T AH0 L
+BANTON  B AE1 N - T AH0 N
+BANTU  B AE1 N - T UW0
+BANTZ  B AE1 N T S
+BANUELOS  B AA0 N - W EH1 - L OW0 Z
+BANVILLE  B AA1 N - V IH0 L
+BANWART  B AE1 N - W AO2 R T
+BANXQUOTE  B AE0 NG K - S K W OW1 T
+BANYA  B AA1 - N Y AH0
+BANYA(2)  B AE1 - N Y AH0
+BANYALUCA  B AE1 - N Y AH0 - L UW2 - K AH0
+BANYAN  B AE1 - N Y AH0 N
+BANYAS  B AA1 - N Y AH0 Z
+BANYAS(2)  B AE1 - N Y AH0 Z
+BANYU  B AA1 - N UW0
+BANZHAF  B AE1 N Z - HH AH0 F
+BAO  B AW1
+BAOGUANG  B EY1 - OW0 - G W AE2 NG
+BAPLEY  B AE1 P - L IY0
+BAPNA  B AA1 P - N AH0
+BAPTISM  B AE1 P - T IH0 - Z AH0 M
+BAPTISMAL  B AE0 P - T IH1 Z - M AH0 L
+BAPTISMS  B AE1 P - T IH2 - Z AH0 M Z
+BAPTIST  B AE1 P - T AH0 S T
+BAPTIST(2)  B AE1 P - T IH0 S T
+BAPTISTA  B AE2 P - T IH1 - S T AH0
+BAPTISTE  B AH0 P - T IH1 S T
+BAPTISTERY  B AE1 P - T AH0 S - T R IY0
+BAPTISTS  B AE1 P - T AH0 S T S
+BAPTISTS(2)  B AE1 P - T AH0 S S
+BAPTIZE  B AE0 P - T AY1 Z
+BAPTIZED  B AE0 P - T AY1 Z D
+BAPTIZED(2)  B AE1 P - T AY2 Z D
+BAR  B AA1 R
+BAR'S  B AA1 R Z
+BAR-MITZVAH  B AA1 R - M IH1 T - S V AH0
+BARA  B AA1 - R AH0
+BARABAR  B EH1 - R AH0 - B AA0 R
+BARACH  B AH0 - R AA1 K
+BARACH(2)  B ER0 - AA1 K
+BARAFF  B AA0 - R AA1 F
+BARAHONA  B AE2 - R AH0 - HH OW1 - N AH0
+BARAJAS  B AA0 - R AA1 - Y AA0 Z
+BARAK  B AA1 - R AH0 K
+BARAKAT  B AA1 - R AH0 - K AA2 T
+BARAM  B EH1 - R AE0 M
+BARAN  B AA0 - R AA1 N
+BARANEK  B AE1 - R AH0 - N IH0 K
+BARANOSKI  B ER0 - AH0 - N AW1 S - K IY0
+BARANOWSKI  B ER0 - AH0 - N AO1 F S - K IY0
+BARANSKI  B ER0 - AE1 N S - K IY0
+BARANY  B ER0 - AO1 - N IY0
+BARASCH  B AE1 - R AH0 SH
+BARASH  B AE1 - R AH0 SH
+BARATH  B AE1 - R AH0 TH
+BARATTA  B AA0 - R AA1 - T AH0
+BARB  B AA1 R B
+BARB'S  B AA1 R B Z
+BARBA  B AA1 R - B AH0
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+BARBAGALLO  B AA2 R - B AH0 - G AE1 - L OW0
+BARBAKOW  B AA1 R - B AH0 - K AW2
+BARBANEL  B AA1 R - B AH0 - N AH0 L
+BARBANO  B AA0 R - B AA1 - N OW0
+BARBARA  B AA1 R - B ER0 - AH0
+BARBARA'S  B AA1 R - B ER0 - AH0 Z
+BARBARA(2)  B AA1 R - B R AH0
+BARBAREE  B AA1 R - B ER0 - IY1
+BARBARIAN  B AA0 R - B EH1 - R IY0 - AH0 N
+BARBARIANS  B AA0 R - B EH1 - R IY0 - AH0 N Z
+BARBARIC  B AA0 R - B AE1 - R IH0 K
+BARBARIC(2)  B AA0 R - B EH1 - R IH0 K
+BARBARINO  B AA0 R - B AA0 - R IY1 - N OW0
+BARBARISM  B AA1 R - B ER0 - IH2 - Z AH0 M
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+BARIS  B AA1 - R IY0 Z
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+BRAXTON  B R AE1 K - S T AH0 N
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+BRAYBOY  B R EY1 - B OY2
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+BRAYMAN  B R EY1 - M AH0 N
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+BRAZ  B R AE1 Z
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+BRAZEAL  B R AH0 - Z IY1 L
+BRAZEAU  B R AH0 - Z OW1
+BRAZEE  B R AE1 - Z IY0
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+BRAZELL  B R AE1 - Z AH0 L
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+BRAZEN  B R EY1 - Z AH0 N
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+BRAZIEL  B R AH0 - Z IY1 L
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+BRAZIERS  B R EY1 - ZH ER0 Z
+BRAZIL  B R AH0 - Z IH1 L
+BRAZIL'S  B R AH0 - Z IH1 L Z
+BRAZILE  B R AA1 - Z AY0 L
+BRAZILIAN  B R AH0 - Z IH1 - L Y AH0 N
+BRAZILIANS  B R AH0 - Z IH1 - L Y AH0 N Z
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+BRAZZAVILLE  B R AE1 - Z AH0 - V IH0 L
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+BREACH  B R IY1 CH
+BREACHED  B R IY1 CH T
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+BREACHING  B R IY1 - CH IH0 NG
+BREAD  B R EH1 D
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+BREADING  B R EH1 - D IH0 NG
+BREADS  B R EH1 D Z
+BREADTH  B R EH1 D TH
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+BREAK  B R EY1 K
+BREAKABLE  B R EY1 - K AH0 - B AH0 L
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+BREAKTHROUGHS  B R EY1 K - TH R UW2 Z
+BREAKUP  B R EY1 K - AH2 P
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+BREAN  B R IY1 N
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+BREAST  B R EH1 S T
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+BREASTFED  B R EH1 S T - F EH2 D
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+BREASTFEEDING  B R EH1 S T - F IY0 - D IH0 NG
+BREASTFEEDING'S  B R EH1 S T - F IY0 - D IH0 NG Z
+BREASTFEEDS  B R EH1 S T - F IY0 D Z
+BREASTING  B R EH1 - S T IH0 NG
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+BREATHED  B R IY1 DH D
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+BREATHES  B R IY1 DH Z
+BREATHING  B R IY1 - DH IH0 NG
+BREATHLESS  B R EH1 TH - L AH0 S
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+BREATHS  B R EH1 TH S
+BREATHTAKING  B R EH1 TH - T EY2 - K IH0 NG
+BREATHTAKINGLY  B R EH1 TH - T EY2 - K IH0 NG - L IY0
+BREATHY  B R EH1 - TH IY0
+BREAU  B R OW1
+BREAULT  B R OW1
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+BREAZEALE  B R IY1 - Z IY2 L
+BREBACH  B R EH1 - B AH0 K
+BRECHBILL  B R EH1 K - B AH0 L
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+BRECHEISEN  B R EH1 - K AY0 - S AH0 N
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+BRECHT  B R EH1 K T
+BRECHTEL  B R EH1 K - T AH0 L
+BRECK  B R EH1 K
+BRECKENRIDGE  B R EH1 - K AH0 N - R IH2 JH
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+BRED  B R EH1 D
+BREDA  B R EY1 - D AH0
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+BREDEN  B R IY1 - D AH0 N
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+BREECE  B R IY1 S
+BREECH  B R IY1 CH
+BREED  B R IY1 D
+BREED'S  B R IY1 D Z
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+BREEDEN'S  B R IY1 - D AH0 N Z
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+BREEDERS  B R IY1 - D ER0 Z
+BREEDERS'  B R IY1 - D ER0 Z
+BREEDING  B R IY1 - D IH0 NG
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+BREEDS  B R IY1 D Z
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+BREESE  B R IY1 Z
+BREEZE  B R IY1 Z
+BREEZED  B R IY1 Z D
+BREEZES  B R IY1 - Z IH0 Z
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+BREEZY  B R IY1 - Z IY0
+BREGE  B R IY1 JH
+BREGER  B R IY1 - G ER0
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+BREGMAN  B R EH1 G - M AH0 N
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+BREISCH  B R AY1 SH
+BREIT  B R IY1 T
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+CHAMBERLAIN(2)  CH EY1 M - B ER0 - L IH0 N
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+CHAMBLEE  CH AE1 M - B L IY0
+CHAMBLESS  SH AH0 M - B L IY1 S
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+CHAMP  CH AE1 M P
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+CHAMPLAIN  SH AE0 M - P L EY1 N
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+CHANG-MING  CH AA1 NG - M IH1 NG
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+CHANGCHUN  CH AA1 NG - CH UH1 N
+CHANGE  CH EY1 N JH
+CHANGEABLE  CH EY1 N - JH AH0 - B AH0 L
+CHANGED  CH EY1 N JH D
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+CHANGER  CH EY1 N - JH ER0
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+CHANGSHO  CH AE1 NG - SH OW1
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+CHANNEL  CH AE1 - N AH0 L
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+CHANNELING  CH AE1 - N AH0 L - IH0 NG
+CHANNELING(2)  CH AE1 N - L IH0 NG
+CHANNELL  CH AE1 - N AH0 L
+CHANNELL'S  SH AH0 - N EH1 L Z
+CHANNELS  CH AE1 - N AH0 L Z
+CHANNING  CH AE1 - N IH0 NG
+CHANNON  CH AE1 - N AH0 N
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+CHANTILLY  SH AE2 N - T IH1 - L IY0
+CHANTING  CH AE1 N - T IH0 NG
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+CHANUKAH  HH AA1 - N AH0 - K AH0
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+CHAOS  K EY1 - AA0 S
+CHAOTIC  K EY0 - AA1 - T IH0 K
+CHAP  CH AE1 P
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+CHAPARRAL  SH AE2 - P ER0 - AE1 L
+CHAPARRO  K AA0 - P AA1 - R OW0
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+CHAPDELAINE  SH AE1 P - D IH0 - L EY0 N
+CHAPEK  CH AE1 - P IH0 K
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+CHAPERONE  SH AE1 - P ER0 - OW2 N
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+CHAPIN  SH AH0 - P AE1 N
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+CHAPMAN  CH AE1 P - M AH0 N
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+CHAPNICK  CH AE1 P - N IH0 K
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+CHAPPAQUIDDICK  CH AE2 - P AH0 - K W IH1 - D IH0 K
+CHAPPEL  CH AE1 - P AH0 L
+CHAPPELEAR  SH AE1 - P IH0 - L ER0
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+CHAPS  CH AE1 P S
+CHAPTER  CH AE1 P - T ER0
+CHAPTERS  CH AE1 P - T ER0 Z
+CHAPUT  CH AE1 - P AH0 T
+CHAR  CH AA1 R
+CHARACTER  K EH1 - R IH0 K - T ER0
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+CHARACTERISTIC  K EH2 - R AH0 K - T ER0 - IH1 - S T IH0 K
+CHARACTERISTICALLY  K EH2 - R AH0 K - T ER0 - IH1 - S T IH0 K - L IY0
+CHARACTERISTICS  K EH2 - R AH0 K - T ER0 - IH1 - S T IH0 K S
+CHARACTERIZATION  K EH2 - R AH0 K - T ER0 - IH0 - Z EY1 - SH AH0 N
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+CHARACTERS  K AE1 - R IH0 K - T ER0 Z
+CHARACTERS'  CH EH1 - R AH0 K - T ER0 Z
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+CHARADE  SH ER0 - EY1 D
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+CHARCOAL  CH AA1 R - K OW2 L
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+CHARISMA  K ER0 - IH1 Z - M AH0
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+CHARITABLE  CH AE1 - R AH0 - T AH0 - B AH0 L
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+CHARITABLY  CH EH1 - R IH0 - T AH0 - B L IY0
+CHARITIES  CH EH1 - R AH0 - T IY0 Z
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+CHARITIES(2)  CH EH1 - R IH0 - T IY0 Z
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+CHARLEBOIS  SH AA1 R - L IH0 - B W AA0
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+CHARLENE  SH AA0 R - L IY1 N
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+CHARLESTON  CH AA1 R L - S T AH0 N
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+CHARLESTON'S(2)  CH AA1 - R AH0 L - S T AH0 N Z
+CHARLESTON(2)  CH AA1 - R AH0 L - S T AH0 N
+CHARLESTOWN  CH AA1 R L - S T AW2 N
+CHARLESTOWN(2)  CH AA1 - R AH0 L - S T AW2 N
+CHARLESWORTH  CH AA1 - R AH0 L - S W ER0 TH
+CHARLESWORTH(2)  CH AA1 - R AH0 L Z - W ER0 TH
+CHARLET  CH AA1 R - L IH0 T
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+CHARLIE'S  CH AA1 R - L IY0 Z
+CHARLIER  CH AA1 R - L IY0 - ER0
+CHARLINE  SH AA0 R - L IY1 N
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+CHARLOTTEVILLE  SH AA1 R - L AH0 T - V IH2 L
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+CHARMAIN  SH AA0 R - M EY1 N
+CHARMAINE  SH AA0 R - M EY1 N
+CHARMED  CH AA1 R M D
+CHARMER  CH AA1 R - M ER0
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+CHARMIAN  CH AA1 R - M IY0 - AH0 N
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+CHARMINGLY  CH AA1 R - M IH0 NG - L IY0
+CHARMION  CH AA1 R - M IY0 - AH0 N
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+CHARNLEY  CH AA1 R N - L IY0
+CHARNOCK  CH AA1 R - N AH0 K
+CHARON  K EH1 - R AH0 N
+CHARPENTIER  SH AA2 R - P AH0 N - T IH1 R
+CHARPIE  CH AA1 R - P IY0
+CHARRED  CH AA1 R D
+CHARREN  CH EH1 - R AH0 N
+CHARRIER  CH AE1 - R IY0 - ER0
+CHARRING  CH AA1 - R IH0 NG
+CHARRON  CH EH1 - R AH0 N
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+CHARRY  CH AE1 - R IY0
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+CHARTERHOUSE  CH AA1 R - T ER0 - HH AW2 S
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+CHARTIER  CH AA1 R - T IY0 - ER0
+CHARTING  CH AA1 R - T IH0 NG
+CHARTIST  CH AA1 R - T IH0 S T
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+CHATSWOOD  CH AE1 T S - W UH2 D
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+CHATTANOOGA  CH AE2 - T AH0 - N UW1 - G AH0
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+CHATTEL  CH AE1 - T AH0 L
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+CHATTERJEE  CH AH0 - T ER1 - JH IY0
+CHATTERTON  CH AE1 - T ER0 - T AH0 N
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+CHATTY  CH AE1 - T IY0
+CHATWAL  CH AE1 T - W AO2 L
+CHATWIN  CH AE1 T - W IH0 N
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+CHATZ'  CH AE1 T S
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+CHAU  SH OW1
+CHAUCER  CH AO1 - S ER0
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+CHAUDOIN  SH OW0 - D OY1 N
+CHAUFFEUR  SH OW0 - F ER1
+CHAUFFEUR'S  SH OW0 - F ER1 Z
+CHAUFFEUR'S(2)  SH OW1 - F ER0 Z
+CHAUFFEUR(2)  SH OW1 - F ER0
+CHAUFFEURED  SH OW0 - F ER1 D
+CHAUFFEURED(2)  SH OW1 - F ER0 D
+CHAUFFEURS  SH OW0 - F ER1 Z
+CHAUFFEURS(2)  SH OW1 - F ER0 Z
+CHAUMET  CH AO1 - M IH0 T
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+CHAUS  CH AW1 S
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+CHAUSSEE  CH AW1 - S IY0
+CHAUTAUQUA  SH AH0 - T AO1 - K W AH0
+CHAUTAUQUAN  SH AH0 - T AO1 - K W AH0 N
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+CHAUVIN  SH OW0 - V AE1 N
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+CHAUVINISTIC  CH OW2 - V AH0 - N IH1 - S T IH0 K
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+CHAVEZ  SH AA1 - V EH0 Z
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+CHAVEZ(3)  SH AH0 - V EH1 Z
+CHAVIN  CH EY1 - V IH0 N
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+CHAVIS(2)  CH EY1 - V IH0 S
+CHAVITZ  CH AE1 - V IH0 T S
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+CHAZEN  CH EY1 - Z AH0 N
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+CHE  CH EY1
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+CHEADLE  CH IY1 - D AH0 L
+CHEANE  CH IY1 N
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+CHEANEY  CH IY1 - N IY0
+CHEAP  CH IY1 P
+CHEAPEN  CH IY1 - P AH0 N
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+CHEAPENING  CH IY1 - P AH0 - N IH0 NG
+CHEAPER  CH IY1 - P ER0
+CHEAPEST  CH IY1 - P AH0 S T
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+CHEAPNESS  CH IY1 P - N AH0 S
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+CHEAPSKATE  CH IY1 P - S K EY2 T
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+CHEATED  CH IY1 - T AH0 D
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+CHEATER  CH IY1 - T ER0
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+CHEATHAM  CH IY1 - T AH0 M
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+CHEATUM  CH IY1 - T AH0 M
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+CHEBRIKOV  CH EH1 - B R IH0 - K AA2 V
+CHECCHI  CH EH1 - K IY0
+CHECHEN  CH EH1 - CH IH0 N
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+CHECHNYA  CH EH1 CH - N IY0 - AH0
+CHECHNYA'S  CH EH1 CH - N IY0 - AH0 Z
+CHECHNYAN  CH EH1 CH - N IY0 - AH0 N
+CHECHNYAN'S  CH EH1 CH - N IY0 - AH0 N Z
+CHECHNYANS  CH EH1 CH - N IY0 - AH0 N Z
+CHECK  CH EH1 K
+CHECKBOOK  CH EH1 K - B UH2 K
+CHECKBOOKS  CH EH1 K - B UH2 K S
+CHECKED  CH EH1 K T
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+CHECKERBOARD  CH EH1 - K ER0 - B AO2 R D
+CHECKERBOARDING  CH EH1 - K ER0 - B AO2 R - D IH0 NG
+CHECKERBOARDS  CH EH1 - K ER0 - B AO2 R D Z
+CHECKERED  CH EH1 - K ER0 D
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+CHECKETTS  CH EH1 - K IH0 T S
+CHECKING  CH EH1 - K IH0 NG
+CHECKLIST  CH EH1 K - L IH2 S T
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+CHECKOFF  CH EH1 K - AO2 F
+CHECKOUT  CH EH1 K - AW2 T
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+CHECKPOINT  CH EH1 K - P OY2 N T
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+CHECKS  CH EH1 K S
+CHECKUP  CH EH1 K - AH2 P
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+CHEDDAR  CH EH1 - D ER0
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+CHEE  CH IY1
+CHEECH  CH IY1 CH
+CHEEK  CH IY1 K
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+CHEER  CH IH1 R
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+CHEERING  CH IH1 - R IH0 NG
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+CHEERLEADER  CH IH1 R - L IY2 - D ER0
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+CHENG  CH EH1 NG
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+CHEVY  CH EH1 - V IY0
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+CLARIDGES  K L EH1 - R IH0 - JH IH0 Z
+CLARIFICATION  K L EH2 - R AH0 - F AH0 - K EY1 - SH AH0 N
+CLARIFICATIONS  K L EH2 - R IH0 - F IH0 - K EY1 - SH AH0 N Z
+CLARIFIED  K L EH1 - R AH0 - F AY2 D
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+CLARIMOND  K L AE1 - R IH0 - M AH0 N D
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+CLARK  K L AA1 R K
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+COLUMBIANS(2)  K OW2 - L AH1 M - B IY0 - AH0 N Z
+COLUMBINE  K AA1 - L AH0 M - B AY2 N
+COLUMBINES  K AA1 - L AH0 M - B AY2 N Z
+COLUMBO  K OW2 - L AH1 M - B OW0
+COLUMBUS  K AH0 - L AH1 M - B AH0 S
+COLUMBUS'  K AH0 - L AH1 M - B AH0 S
+COLUMBUS'S  K AH0 - L AH1 M - B AH0 - S IH0 Z
+COLUMN  K AA1 - L AH0 M
+COLUMNED  K AA1 - L AH0 M D
+COLUMNIST  K AA1 - L AH0 M - N AH0 S T
+COLUMNISTS  K AA1 - L AH0 M - N AH0 S T S
+COLUMNISTS(2)  K AA1 - L AH0 M - N AH0 S S
+COLUMNISTS(3)  K AA1 - L AH0 M - N AH0 S
+COLUMNS  K AA1 - L AH0 M Z
+COLUNGA  K OW0 - L UW1 NG - G AH0
+COLUSSY  K AH0 - L UW1 - S IY0
+COLVARD  K AA1 L - V ER0 D
+COLVER  K OW1 L - V ER0
+COLVERT  K AA1 L - V ER0 T
+COLVILLE  K AA1 L - V IH0 L
+COLVIN  K OW1 L - V IH0 N
+COLWELL  K OW1 L - W EH2 L
+COLYER  K OW1 - L IY0 - ER0
+COM  K AA1 M
+COM'S  K AA1 M Z
+COMA  K OW1 - M AH0
+COMAIR  K AA1 - M EH1 R
+COMAN  K OW1 - M AH0 N
+COMANCHE  K AH0 - M AE1 N - CH IY0
+COMANCHES  K AH0 - M AE1 N - CH IY0 Z
+COMANDANTE  K OW2 - M AH0 N - D AA1 N - T EY0
+COMANDANTES  K OW2 - M AH0 N - D AA1 N - T EH0 Z
+COMARCO  K OW0 - M AA1 R - K OW0
+COMAS  K OW1 - M AH0 Z
+COMATOSE  K OW1 - M AH0 - T OW2 S
+COMB  K OW1 M
+COMBAT  K AA1 M - B AE0 T
+COMBAT(2)  K AH0 M - B AE1 T
+COMBATANT  K AH0 M - B AE1 - T AH0 N T
+COMBATANTS  K AH0 M - B AE1 - T AH0 N T S
+COMBATING  K AH0 M - B AE1 - T IH0 NG
+COMBATIVE  K AH0 M - B AE1 - T IH0 V
+COMBATIVE(2)  K AA2 M - B AE1 - T IH2 V
+COMBATIVENESS  K AH0 M - B AE1 - T IH0 V - N AH0 S
+COMBATS  K AH0 M - B AE1 T S
+COMBATTING  K AH0 M - B AE1 - T IH0 NG
+COMBE  K OW1 M
+COMBED  K OW1 M D
+COMBEE  K AA1 M - B IY2
+COMBER  K OW1 - M ER0
+COMBES  K OW1 M Z
+COMBEST  K OW1 - M IH0 S T
+COMBINABILITY  K AH0 M - B AY2 - N AH0 - B IH1 - L AH0 - T IY0
+COMBINABILITY  K AH2 M - B IH0 N - AH0 - B IH1 - L AH0 - T IY0
+COMBINABLE  K AH0 M - B AY1 - N AH0 - B AH0 L
+COMBINATION  K AA2 M - B AH0 - N EY1 - SH AH0 N
+COMBINATIONS  K AA2 M - B AH0 - N EY1 - SH AH0 N Z
+COMBINE  K AA1 M - B AY0 N
+COMBINE(2)  K AH0 M - B AY1 N
+COMBINED  K AH0 M - B AY1 N D
+COMBINES  K AH0 M - B AY1 N Z
+COMBING  K OW1 - M IH0 NG
+COMBINING  K AH0 M - B AY1 - N IH0 NG
+COMBO  K AA1 M - B OW2
+COMBS  K OW1 M Z
+COMBUST  K AH0 M - B AH1 S T
+COMBUSTABLE  K AH0 M - B AH1 - S T AH0 - B AH0 L
+COMBUSTION  K AH0 M - B AH1 S - CH AH0 N
+COMCAST  K AA1 M - K AE2 S T
+COMCAST'S  K AA1 M - K AE2 S T S
+COMDATA  K AA1 M - D AE2 - D AH0
+COMDATA(2)  K AA1 M - D EY2 - D AH0
+COMDEN  K AA1 M - D IH0 N
+COMDEX  K AA1 M - D AH0 K S
+COMDISCO  K AA2 M - D IH1 - S K OW0
+COME  K AH1 M
+COME-ON  K AH1 - M AA1 N
+COME-ONS  K AH1 - M AA1 N Z
+COMEAU  K AH0 - M OW1
+COMEAUX  K AH0 - M OW1
+COMEBACK  K AH1 M - B AE2 K
+COMEBACKS  K AH1 M - B AE2 K S
+COMECON  K AA1 - M AH0 - K AA2 N
+COMEDIAN  K AH0 - M IY1 - D IY0 - AH0 N
+COMEDIAN'S  K AH0 - M IY1 - D IY0 - AH0 N Z
+COMEDIANS  K AH0 - M IY1 - D IY0 - AH0 N Z
+COMEDIC  K AH0 - M IY1 - D IH0 K
+COMEDIENNE  K AH0 - M IY2 - D IY0 - EH1 N
+COMEDIES  K AA1 - M AH0 - D IY0 Z
+COMEDOWN  K AH1 M - D AW2 N
+COMEDY  K AA1 - M AH0 - D IY0
+COMEDY'S  K AA1 - M AH0 - D IY0 Z
+COMEGYS  K AA1 - M IH0 - JH IY0 Z
+COMELLA  K OW0 - M EH1 - L AH0
+COMELY  K AH1 M - L IY0
+COMER  K AH1 - M ER0
+COMERFORD  K AH0 - M ER1 - F ER0 D
+COMERICA  K AH0 - M EH1 - R IH0 - K AH0
+COMERS  K AH1 - M ER0 Z
+COMES  K AH1 M Z
+COMET  K AA1 - M AH0 T
+COMET'S  K AA1 - M AH0 T S
+COMETARY  K AA1 - M AH0 - T EH2 - R IY0
+COMETH  K AH1 - M IH0 TH
+COMETRA  K OW0 - M EH1 - T R AH0
+COMETS  K AA1 - M AH0 T S
+COMEUPPANCE  K AH2 - M AH1 - P AH0 N S
+COMEX  K AA1 - M EH2 K S
+COMEX'S  K AA1 - M EH2 K - S IH0 Z
+COMFED  K AA1 M - F EH2 D
+COMFINANCE  K AA1 M - F IH0 - N AH0 N S
+COMFORT  K AH1 M - F ER0 T
+COMFORTABLE  K AH1 M - F ER0 - T AH0 - B AH0 L
+COMFORTABLY  K AH1 M - F ER0 - T AH0 - B L IY0
+COMFORTED  K AH1 M - F ER0 - T IH0 D
+COMFORTER  K AH1 M - F ER0 - T ER0
+COMFORTERS  K AH1 M - F ER0 - T ER0 Z
+COMFORTING  K AH1 M - F ER0 - T IH0 NG
+COMFORTS  K AH1 M - F ER0 T S
+COMFREY  K AH1 M - F R IY0
+COMFY  K AH1 M - F IY0
+COMIC  K AA1 - M IH0 K
+COMICAL  K AA1 - M IH0 - K AH0 L
+COMICALLY  K AA1 - M IH0 - K AH0 - L IY0
+COMICALLY(2)  K AA1 - M IH0 K - L IY0
+COMICOPIA  K AA2 - M IH0 - K OW1 - P IY0 - AH0
+COMICS  K AA1 - M IH0 K S
+COMIN'  K AH1 - M IH0 N
+COMINCO  K OW0 - M IH1 NG - K OW0
+COMING  K AH1 - M IH0 NG
+COMINGS  K AH1 - M IH0 NG Z
+COMINO  K AH0 - M IY1 - N OW0
+COMINS  K OW1 - M IH0 N Z
+COMINSKY  K AH0 - M IH1 N - S K IY0
+COMISKEY  K OW1 - M IH0 S - K IY1
+COMITATUS  K AO0 - M AH0 - T EY1 - T AH0 S
+COMITO  K OW0 - M IY1 - T OW0
+COMITY  K OW1 - M IH0 - T IY0
+COMLEY  K AA1 M - L IY0
+COMLY  K AA1 M - L IY0
+COMMA  K AA1 - M AH0
+COMMACK  K AA1 - M AH0 K
+COMMAND  K AH0 - M AE1 N D
+COMMAND'S  K AH0 - M AE1 N D Z
+COMMANDANT  K AA2 - M AH0 N - D AA1 N T
+COMMANDED  K AH0 - M AE1 N - D AH0 D
+COMMANDED(2)  K AH0 - M AE1 N - D IH0 D
+COMMANDEER  K AA2 - M AH0 N - D IH1 R
+COMMANDEERED  K AA2 - M AH0 N - D IH1 R D
+COMMANDER  K AH0 - M AE1 N - D ER0
+COMMANDER'S  K AH0 - M AE1 N - D ER0 Z
+COMMANDERS  K AH0 - M AE1 N - D ER0 Z
+COMMANDING  K AH0 - M AE1 N - D IH0 NG
+COMMANDMENT  K AH0 - M AE1 N D - M AH0 N T
+COMMANDMENTS  K AH0 - M AE1 N D - M AH0 N T S
+COMMANDO  K AH0 - M AE1 N - D OW2
+COMMANDOS  K AH0 - M AE1 N - D OW2 Z
+COMMANDS  K AH0 - M AE1 N D Z
+COMMAS  K AA1 - M AH0 Z
+COMMEMORATE  K AH0 - M EH1 - M ER0 - EY2 T
+COMMEMORATED  K AH0 - M EH1 - M ER0 - EY2 - T IH0 D
+COMMEMORATES  K AH0 - M EH1 - M ER0 - EY2 T S
+COMMEMORATING  K AH0 - M EH1 - M ER0 - EY2 - T IH0 NG
+COMMEMORATION  K AH0 - M EH2 - M ER0 - EY1 - SH AH0 N
+COMMEMORATIONS  K AH0 - M EH2 - M ER0 - EY1 - SH AH0 N Z
+COMMEMORATIVE  K AH0 - M EH1 M - R AH0 - T IH0 V
+COMMEMORATIVE(2)  K AH0 - M EH1 - M ER0 - EY2 - T IH0 V
+COMMENCE  K AH0 - M EH1 N S
+COMMENCED  K AH0 - M EH1 N S T
+COMMENCEMENT  K AH0 - M EH1 N - S M AH0 N T
+COMMENCES  K AH0 - M EH1 N - S AH0 Z
+COMMENCING  K AH0 - M EH1 N - S IH0 NG
+COMMEND  K AH0 - M EH1 N D
+COMMENDABLE  K AH0 - M EH1 N - D AH0 - B AH0 L
+COMMENDATION  K AA2 - M AH0 N - D EY1 - SH AH0 N
+COMMENDED  K AH0 - M EH1 N - D IH0 D
+COMMENDING  K AH0 - M EH1 N - D IH0 NG
+COMMENDS  K AH0 - M EH1 N D Z
+COMMENSURATE  K AH0 - M EH1 N - S ER0 - AH0 T
+COMMENSURATE(2)  K AH0 - M EH1 N - S ER0 - IH0 T
+COMMENSURATELY  K AH0 - M EH1 N - S ER0 - AH0 T - L IY0
+COMMENSURATELY  K AH0 - M EH1 N - SH ER0 - AH0 T - L IY0
+COMMENT  K AA1 - M EH0 N T
+COMMENTARIES  K AA1 - M AH0 N - T EH2 - R IY0 Z
+COMMENTARY  K AA1 - M AH0 N - T EH2 - R IY0
+COMMENTATOR  K AA1 - M AH0 N - T EY2 - T ER0
+COMMENTATOR'S  K AA1 - M AH0 N - T EY2 - T ER0 Z
+COMMENTATORS  K AA1 - M AH0 N - T EY2 - T ER0 Z
+COMMENTED  K AA1 - M EH0 N - T AH0 D
+COMMENTER  K AA1 - M EH0 N - T ER0
+COMMENTERS  K AA1 - M EH0 N - T ER0 Z
+COMMENTING  K AA1 - M EH0 N - T IH0 NG
+COMMENTS  K AA1 - M EH0 N T S
+COMMERCE  K AA1 - M ER0 S
+COMMERCE'S  K AA1 - M ER0 - S IH0 Z
+COMMERCEBANCORP  K AA2 - M ER0 S - B AE1 N - K AO2 R P
+COMMERCIAL  K AH0 - M ER1 - SH AH0 L
+COMMERCIAL'S  K AH0 - M ER1 - SH AH0 L Z
+COMMERCIALE  K AH0 - M ER2 - S IY0 - AE1 L
+COMMERCIALE'S  K AH0 - M ER2 - S IY0 - AE1 L Z
+COMMERCIALE'S(2)  K OW0 - M EH2 R - S IY0 - AE1 - L EY2 Z
+COMMERCIALISM  K AH0 - M ER1 - SH AH0 - L IH2 - Z AH0 M
+COMMERCIALIZATION  K AH0 - M ER2 - SH AH0 - L IH0 - Z EY1 - SH AH0 N
+COMMERCIALIZE  K AH0 - M ER1 - SH AH0 - L AY2 Z
+COMMERCIALIZED  K AH0 - M ER1 - SH AH0 - L AY2 Z D
+COMMERCIALIZING  K AH0 - M ER1 - SH AH0 - L AY2 - Z IH0 NG
+COMMERCIALLY  K AH0 - M ER1 - SH AH0 - L IY0
+COMMERCIALS  K AH0 - M ER1 - SH AH0 L Z
+COMMERFORD  K AA1 - M ER0 - F ER0 D
+COMMERICAL  K AH0 - M ER1 - SH AH0 L
+COMMERZBANK  K AA1 - M ER0 Z - B AE2 NG K
+COMMERZBANK'S  K AA1 - M ER0 Z - B AE1 NG K S
+COMMIE  K AA1 - M IY0
+COMMIES  K AA1 - M IY0 Z
+COMMINGLE  K AH0 - M IH1 NG - G AH0 L
+COMMINGLE(2)  K OW0 - M IH1 NG - G AH0 L
+COMMINGLED  K AA0 - M IH1 NG - G AH0 L D
+COMMINGLED(2)  K OW0 - M IH1 NG - G AH0 L D
+COMMINGLING  K AA0 - M IH1 NG - G AH0 L - IH0 NG
+COMMINGLING(2)  K OW0 - M IH1 NG - G L IH0 NG
+COMMINS  K AA1 - M IH0 N Z
+COMMISERATE  K AH0 - M IH1 - S ER0 - EY2 T
+COMMISH  K AH0 - M IH1 SH
+COMMISION  K AH0 - M IH1 - Z AH0 N
+COMMISION(2)  K AH0 - M IH1 - SH AH0 N
+COMMISSAR  K AA1 - M AH0 - S AA2 R
+COMMISSARIES  K AA1 - M AH0 - S EH2 - R IY0 Z
+COMMISSARS  K AA1 - M IH0 - S AA0 Z
+COMMISSARY  K AA1 - M AH0 - S EH2 - R IY0
+COMMISSION  K AH0 - M IH1 - SH AH0 N
+COMMISSION'S  K AH0 - M IH1 - SH AH0 N Z
+COMMISSIONED  K AH0 - M IH1 - SH AH0 N D
+COMMISSIONER  K AH0 - M IH1 - SH AH0 N - ER0
+COMMISSIONER'S  K AH0 - M IH1 - SH AH0 N - ER0 Z
+COMMISSIONERS  K AH0 - M IH1 - SH AH0 N - ER0 Z
+COMMISSIONING  K AH0 - M IH1 - SH AH0 N - IH0 NG
+COMMISSIONS  K AH0 - M IH1 - SH AH0 N Z
+COMMISSO  K OW0 - M IY1 - S OW0
+COMMIT  K AH0 - M IH1 T
+COMMITEE  K AA1 - M IH0 - T IY0
+COMMITEE(2)  K AH0 - M IH1 - T IY0
+COMMITMENT  K AH0 - M IH1 T - M AH0 N T
+COMMITMENTS  K AH0 - M IH1 T - M AH0 N T S
+COMMITS  K AH0 - M IH1 T S
+COMMITTAL  K AH0 - M IH1 - T AH0 L
+COMMITTED  K AH0 - M IH1 - T AH0 D
+COMMITTEE  K AH0 - M IH1 - T IY0
+COMMITTEE'S  K AH0 - M IH1 - T IY0 Z
+COMMITTEEMAN  K AH0 - M IH1 - T IY0 - M AH0 N
+COMMITTEES  K AH0 - M IH1 - T IY0 Z
+COMMITTEES'  K AH0 - M IH1 - T IY0 Z
+COMMITTING  K AH0 - M IH1 - T IH0 NG
+COMMODE  K AH0 - M OW1 D
+COMMODIOUS  K AH0 - M OW1 - D IY0 - AH0 S
+COMMODITIES  K AH0 - M AA1 - D AH0 - T IY0 Z
+COMMODITY  K AH0 - M AA1 - D AH0 - T IY0
+COMMODITY'S  K AH0 - M AA1 - D AH0 - T IY0 Z
+COMMODORE  K AA1 - M AH0 - D AO2 R
+COMMODORE'S  K AA1 - M AH0 - D AO2 R Z
+COMMON  K AA1 - M AH0 N
+COMMONALITIES  K AA2 - M AH0 - N AE1 - L AH0 - T IY0 Z
+COMMONALITY  K AA2 - M AH0 - N AE1 - L AH0 - T IY0
+COMMONER  K AA1 - M AH0 - N ER0
+COMMONERS  K AA1 - M AH0 - N ER0 Z
+COMMONLY  K AA1 - M AH0 N - L IY0
+COMMONPLACE  K AA1 - M AH0 N - P L EY2 S
+COMMONS  K AA1 - M AH0 N Z
+COMMONSENSE  K AA2 - M AH0 N - S EH1 N S
+COMMONSENSICAL  K AA2 - M AH0 N - S EH1 N - S IH0 - K AH0 L
+COMMONWEALTH  K AA1 - M AH0 N - W EH2 L TH
+COMMONWEALTH'S  K AA1 - M AH0 N - W EH2 L TH S
+COMMOTION  K AH0 - M OW1 - SH AH0 N
+COMMUNAL  K AH0 - M Y UW1 - N AH0 L
+COMMUNE  K AA1 - M Y UW0 N
+COMMUNE(2)  K AH0 - M Y UW1 N
+COMMUNES  K AA1 - M Y UW0 N Z
+COMMUNES(2)  K AH0 - M Y UW1 N Z
+COMMUNICABLE  K AH0 - M Y UW1 - N AH0 - K AH0 - B AH0 L
+COMMUNICATE  K AH0 - M Y UW1 - N AH0 - K EY2 T
+COMMUNICATED  K AH0 - M Y UW1 - N AH0 - K EY2 - T IH0 D
+COMMUNICATES  K AH0 - M Y UW1 - N IH0 - K EY2 T S
+COMMUNICATING  K AH0 - M Y UW1 - N AH0 - K EY2 - T IH0 NG
+COMMUNICATION  K AH0 - M Y UW2 - N AH0 - K EY1 - SH AH0 N
+COMMUNICATION'S  K AH0 - M Y UW2 - N IH0 - K EY1 - SH AH0 N Z
+COMMUNICATIONS  K AH0 - M Y UW2 - N AH0 - K EY1 - SH AH0 N Z
+COMMUNICATIONS'  K AH0 - M Y UW2 - N AH0 - K EY1 - SH AH0 N Z
+COMMUNICATIVE  K AH0 - M Y UW1 - N AH0 - K AH0 - T IH0 V
+COMMUNICATOR  K AH0 - M Y UW1 - N AH0 - K EY2 - T ER0
+COMMUNICATORS  K AH0 - M Y UW1 - N AH0 - K EY0 - T ER0 Z
+COMMUNION  K AH0 - M Y UW1 - N Y AH0 N
+COMMUNIQUE  K AH0 - M Y UW1 - N AH0 - K EY2
+COMMUNIQUE(2)  K AH0 - M Y UW2 - N AH0 - K EY1
+COMMUNIQUES  K AH0 - M Y UW2 - N IH0 - K EY1 Z
+COMMUNISM  K AA1 - M Y AH0 - N IH2 - Z AH0 M
+COMMUNISM'S  K AA1 - M Y AH0 - N IH2 - Z AH0 M Z
+COMMUNIST  K AA1 - M Y AH0 - N AH0 S T
+COMMUNIST'S  K AA1 - M Y AH0 - N AH0 S T S
+COMMUNISTS  K AA1 - M Y AH0 - N AH0 S T S
+COMMUNISTS'  K AA1 - M Y UW0 - N IH0 S T S
+COMMUNISTS(2)  K AA1 - M Y AH0 - N AH0 S S
+COMMUNISTS(3)  K AA1 - M Y AH0 - N AH0 S
+COMMUNITIES  K AH0 - M Y UW1 - N AH0 - T IY0 Z
+COMMUNITIES(2)  K AH0 - M Y UW1 - N IH0 - T IY0 Z
+COMMUNITY  K AH0 - M Y UW1 - N AH0 - T IY0
+COMMUNITY'S  K AH0 - M Y UW1 - N IH0 - T IY0 Z
+COMMUNITY(2)  K AH0 - M Y UW1 - N IH0 - T IY0
+COMMUNITYWIDE  K AH0 - M Y UW1 - N IH0 - T IY0 - W AY2 D
+COMMUNIZATION  K AA2 - M Y AH0 - N AH0 - Z EY1 - SH AH0 N
+COMMUNIZE  K AA1 - M Y AH0 - N AY2 Z
+COMMUTE  K AH0 - M Y UW1 T
+COMMUTED  K AH0 - M Y UW1 - T IH0 D
+COMMUTER  K AH0 - M Y UW1 - T ER0
+COMMUTERS  K AH0 - M Y UW1 - T ER0 Z
+COMMUTES  K AH0 - M Y UW1 T S
+COMMUTING  K AH0 - M Y UW1 - T IH0 NG
+COMO  K OW1 - M OW0
+COMP  K AA1 M P
+COMPACT  K AA1 M - P AE0 K T
+COMPACT(2)  K AH0 M - P AE1 K T
+COMPACTED  K AH0 M - P AE1 K - T IH0 D
+COMPACTNESS  K AH0 M - P AE1 K T - N AH0 S
+COMPACTOR  K AH0 M - P AE1 K - T ER0
+COMPACTS  K AH0 M - P AE1 K T S
+COMPACTS(2)  K AA1 M - P AE0 K T S
+COMPAGNIE  K AH1 M - P AH0 - N IY0
+COMPANHIA  K AH0 M - P AE1 N - HH IY0 - AH0
+COMPANIA  K AH0 M - P EY1 - N IY0 - AH0
+COMPANIES  K AH1 M - P AH0 - N IY0 Z
+COMPANIES'  K AH1 M - P AH0 - N IY0 Z
+COMPANIES'S  K AH1 M - P AH0 - N IY0 - Z IH0 Z
+COMPANION  K AH0 M - P AE1 - N Y AH0 N
+COMPANIONS  K AH0 M - P AE1 - N Y AH0 N Z
+COMPANIONSHIP  K AH0 M - P AE1 - N Y AH0 N - SH IH2 P
+COMPANIONWAY  K AH0 M - P AE1 - N Y AH0 N - W EY2
+COMPANY  K AH1 M - P AH0 - N IY0
+COMPANY'S  K AH1 M - P AH0 - N IY0 Z
+COMPANYWIDE  K AH1 M - P AH0 - N IY0 - W AY2 D
+COMPAQ  K AA1 M - P AE2 K
+COMPAQ'S  K AA1 M - P AE2 K S
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+COMPARABLE  K AA1 M - P ER0 - AH0 - B AH0 L
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+COMPARABLE(3)  K AH0 M - P R AH0 - B AH0 L
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+COMPARATIVELY  K AH0 M - P EH1 - R AH0 - T IH0 V - L IY0
+COMPARATOR  K AH0 M - P ER1 - AH0 - T ER0
+COMPARE  K AH0 M - P EH1 R
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+COMPARES  K AH0 M - P EH1 R Z
+COMPARING  K AH0 M - P EH1 - R IH0 NG
+COMPARISON  K AH0 M - P EH1 - R AH0 - S AH0 N
+COMPARISONS  K AH0 M - P EH1 - R AH0 - S AH0 N Z
+COMPARTMENT  K AH0 M - P AA1 R T - M AH0 N T
+COMPARTMENTAL  K AH0 M - P AA2 R T - M EH1 N - T AH0 L
+COMPARTMENTALIZE  K AH0 M - P AA2 R T - M EH1 N - T AH0 - L AY2 Z
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+COMPAS  K AA1 M - P AH0 S
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+COMPASSION  K AH0 M - P AE1 - SH AH0 N
+COMPASSIONATE  K AH0 M - P AE1 - SH AH0 - N AH0 T
+COMPASSIONATELY  K AH0 M - P AE1 - SH AH0 - N AH0 T - L IY0
+COMPATIBILITY  K AH0 M - P AE2 - T AH0 - B IH1 - L AH0 - T IY0
+COMPATIBLE  K AH0 M - P AE1 - T AH0 - B AH0 L
+COMPATIBLES  K AH0 M - P AE1 - T IH0 - B AH0 L Z
+COMPATRIOT  K AH0 M - P EY1 - T R IY0 - AH0 T
+COMPATRIOTS  K AH0 M - P EY1 - T R IY0 - AH0 T S
+COMPEAN  K AA1 M - P AH0 N
+COMPEAU  K AH0 M - P OW1
+COMPEL  K AH0 M - P EH1 L
+COMPELLED  K AH0 M - P EH1 L D
+COMPELLING  K AH0 M - P EH1 - L IH0 NG
+COMPELLINGLY  K AH0 M - P EH1 - L IH0 NG - L IY0
+COMPELS  K AH0 M - P EH1 L Z
+COMPENDIUM  K AH0 M - P EH1 N - D IY0 - AH0 M
+COMPENSABLE  K AH0 M - P EH1 N - S AH0 - B AH0 L
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+COMPENSATED  K AA1 M - P AH0 N - S EY2 - T AH0 D
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+COMPENSATING  K AA1 M - P AH0 N - S EY2 - T IH0 NG
+COMPENSATION  K AA2 M - P AH0 N - S EY1 - SH AH0 N
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+COMPENSATORY  K AH0 M - P EH1 N - S AH0 - T AO2 - R IY0
+COMPETE  K AH0 M - P IY1 T
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+COMPETENCY  K AA1 M - P AH0 - T IH0 N - S IY0
+COMPETENT  K AA1 M - P AH0 - T IH0 N T
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+COMPETITIONS  K AA2 M - P AH0 - T IH1 - SH AH0 N Z
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+COMPETITOR  K AH0 M - P EH1 - T AH0 - T ER0
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+COMPETITOR(2)  K AH0 M - P EH1 - T IH0 - T ER0
+COMPETITORS  K AH0 M - P EH1 - T AH0 - T ER0 Z
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+COMPETITORS(2)  K AH0 M - P EH1 - T IH0 - T ER0 Z
+COMPHER  K AA1 M - F ER0
+COMPILATION  K AA2 M - P AH0 - L EY1 - SH AH0 N
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+COMPILER  K AH0 M - P AY1 - L ER0
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+COMPILES  K AH0 M - P AY1 L Z
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+COMPLACENCY  K AH0 M - P L EY1 - S AH0 N - S IY0
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+COMPLAIN  K AH0 M - P L EY1 N
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+COMPLAINS  K AH0 M - P L EY1 N Z
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+COMPLEMENT  K AA1 M - P L AH0 - M AH0 N T
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+COMPLEMENTED  K AA1 M - P L AH0 - M EH2 N - T IH0 D
+COMPLEMENTING  K AA1 M - P L AH0 - M EH2 N - T IH0 NG
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+COMPLICIT  K AH0 M - P L IH1 - S AH0 T
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+CONCURRENTLY  K AH0 N - K ER1 - AH0 N T - L IY0
+CONCURRING  K AH0 N - K ER1 - IH0 NG
+CONCURS  K AH0 N - K ER1 Z
+CONCUSSION  K AH0 N - K AH1 - SH AH0 N
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+CONDE  K AA1 N D
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+CONDEMN  K AH0 N - D EH1 M
+CONDEMNATION  K AA2 N - D AH0 M - N EY1 - SH AH0 N
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+CONDENSATES  K AA1 N - D AH0 N - S EY2 T S
+CONDENSATION  K AA2 N - D AH0 N - S EY1 - SH AH0 N
+CONDENSE  K AH0 N - D EH1 N S
+CONDENSED  K AH0 N - D EH1 N S T
+CONDENSER  K AH0 N - D EH1 N - S ER0
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+CONDER  K AA1 N - D ER0
+CONDESCEND  K AA2 N - D IH0 - S EH1 N D
+CONDESCENDING  K AA2 N - D IH0 - S EH1 N - D IH0 NG
+CONDESCENSION  K AA2 N - D AH0 - S EH1 N - SH AH0 N
+CONDIE  K AA1 N - D IY0
+CONDIMENT  K AA1 N - D AH0 - M AH0 N T
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+CONDIT  K AA1 N - D IH0 T
+CONDITION  K AH0 N - D IH1 - SH AH0 N
+CONDITIONAL  K AH0 N - D IH1 - SH AH0 - N AH0 L
+CONDITIONALITY  K AH0 N - D IH2 - SH AH0 - N AE1 - L IH0 - T IY0
+CONDITIONALLY  K AH0 N - D IH1 - SH AH0 N - AH0 - L IY0
+CONDITIONALLY(2)  K AH0 N - D IH1 SH - N AH0 - L IY0
+CONDITIONED  K AH0 N - D IH1 - SH AH0 N D
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+CONDITIONING  K AH0 N - D IH1 - SH AH0 N - IH0 NG
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+CONDITT  K AA1 N - D IH0 T
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+CONDOM  K AA1 N - D AH0 M
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+CONDOMS  K AA1 N - D AH0 M Z
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+CONDREN  K AA1 N - D ER0 - AH0 N
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+CONEHEAD  K OW1 N - HH EH0 D
+CONEHEADS  K OW1 N - HH EH0 D Z
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+CONEY  K OW1 - N IY0
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+CONFAIR  K AA1 N - F EH2 R
+CONFECT  K AH0 N - F EH1 K T
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+CONFECTIONARY  K AH0 N - F EH1 K - SH AH0 N - EH2 - R IY0
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+CONFECTIONERY  K AH0 N - F EH1 K - SH AH0 N - EH2 - R IY0
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+CONFEDERACY  K AH0 N - F EH1 - D ER0 - AH0 - S IY0
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+CONFEDERACY(2)  K AH0 N - F EH1 - D R AH0 - S IY0
+CONFEDERATE  K AH0 N - F EH1 - D ER0 - AH0 T
+CONFEDERATE(2)  K AH0 N - F EH1 - D ER0 - EY2 T
+CONFEDERATION  K AH0 N - F EH2 - D ER0 - EY1 - SH AH0 N
+CONFER  K AH0 N - F ER1
+CONFEREE  K AA2 N - F ER0 - IY1
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+CONFERENCE  K AA1 N - F ER0 - AH0 N S
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+CONFERENCE'S(2)  K AA1 N - F R AH0 N - S IH0 Z
+CONFERENCE(2)  K AA1 N - F R AH0 N S
+CONFERENCES  K AA1 N - F ER0 - AH0 N - S AH0 Z
+CONFERENCES(2)  K AA1 N - F R AH0 N - S AH0 Z
+CONFERENCING  K AA1 N - F R AH0 N - S IH0 NG
+CONFERRED  K AH0 N - F ER1 D
+CONFERRING  K AH0 N - F ER1 - IH0 NG
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+CONFESS  K AH0 N - F EH1 S
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+CONFESSES  K AH0 N - F EH1 - S IH0 Z
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+CONFESSION  K AH0 N - F EH1 - SH AH0 N
+CONFESSIONAL  K AH0 N - F EH1 - SH AH0 - N AH0 L
+CONFESSIONALS  K AH0 N - F EH1 - SH AH0 - N AH0 L Z
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+CONFETTI  K AH0 N - F EH1 - T IY0
+CONFIDANT  K AA1 N - F AH0 - D AA2 N T
+CONFIDANTE  K AA1 N - F AH0 - D AE2 N T
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+CONFIDE  K AH0 N - F AY1 D
+CONFIDED  K AH0 N - F AY1 - D AH0 D
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+CONFIDENCE  K AA1 N - F AH0 - D AH0 N S
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+CONFIDENCES  K AA1 N - F AH0 - D AH0 N - S IH0 Z
+CONFIDENT  K AA1 N - F AH0 - D AH0 N T
+CONFIDENTIAL  K AA2 N - F AH0 - D EH1 N - SH AH0 L
+CONFIDENTIAL(2)  K AA2 N - F AH0 - D EH1 N - CH AH0 L
+CONFIDENTIALITY  K AA2 N - F AH0 - D EH2 N - SH IY0 - AE1 - L AH0 - T IY0
+CONFIDENTIALITY(2)  K AA2 N - F AH0 - D EH2 N - CH IY0 - AE1 - L AH0 - T IY0
+CONFIDENTIALLY  K AA2 N - F AH0 - D EH1 N - SH AH0 - L IY0
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+CONFIDENTLY  K AA1 N - F AH0 - D AH0 N T - L IY0
+CONFIDES  K AH0 N - F AY1 D Z
+CONFIDING  K AH0 N - F AY1 - D IH0 NG
+CONFIGURATION  K AH0 N - F IH2 - G Y ER0 - EY1 - SH AH0 N
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+CONFIGURE  K AH0 N - F IH1 - G Y ER0
+CONFIGURED  K AH0 N - F IH1 - G Y ER0 D
+CONFIGURING  K AH0 N - F IH1 - G Y ER0 - IH0 NG
+CONFINDUSTRIA  K AA2 N - F IH0 N - D AH1 S - T R IY0 - AH0
+CONFINE  K AH0 N - F AY1 N
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+CONFINING  K AH0 N - F AY1 - N IH0 NG
+CONFIRM  K AH0 N - F ER1 M
+CONFIRMABLE  K AH0 N - F ER1 - M AH0 - B AH0 L
+CONFIRMATION  K AA2 N - F ER0 - M EY1 - SH AH0 N
+CONFIRMATIONS  K AA2 N - F ER0 - M EY1 - SH AH0 N Z
+CONFIRMATORY  K AH0 N - F ER1 - M AH0 - T AO2 - R IY0
+CONFIRMED  K AH0 N - F ER1 M D
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+CONFISCATE  K AA1 N - F AH0 - S K EY2 T
+CONFISCATED  K AA1 N - F AH0 - S K EY2 - T AH0 D
+CONFISCATING  K AA1 N - F AH0 - S K EY2 - T IH0 NG
+CONFISCATION  K AA2 N - F AH0 - S K EY1 - SH AH0 N
+CONFISCATORY  K AH0 N - F IH1 S - K AH0 - T AO2 - R IY0
+CONFITERIAS  K AA2 N - F IH0 - T IH1 - R IY0 - AH0 Z
+CONFLAGRATION  K AA2 N - F L AH0 - G R EY1 - SH AH0 N
+CONFLATE  K AH0 N - F L EY1 T
+CONFLATES  K AH0 N - F L EY1 T S
+CONFLICT  K AA1 N - F L IH0 K T
+CONFLICT(2)  K AH0 N - F L IH1 K T
+CONFLICTED  K AH0 N - F L IH1 K - T IH0 D
+CONFLICTING  K AH0 N - F L IH1 K - T IH0 NG
+CONFLICTS  K AH0 N - F L IH1 K T S
+CONFLICTS(2)  K AA1 N - F L IH0 K T S
+CONFLICTS(3)  K AH0 N - F L IH1 K S
+CONFLICTS(4)  K AA1 N - F L IH0 K S
+CONFLUENCE  K AA1 N - F L UW0 - AH0 N S
+CONFLUENT  K AA0 N - F L UW1 - AH0 N T
+CONFORM  K AH0 N - F AO1 R M
+CONFORMANCE  K AH0 N - F AO1 R - M AH0 N S
+CONFORMATIONAL  K AA2 N - F ER0 - M EY1 - SH AH0 - N AH0 L
+CONFORMED  K AH0 N - F AO1 R M D
+CONFORMING  K AH0 N - F AO1 R - M IH0 NG
+CONFORMIST  K AH0 N - F AO1 R - M IH0 S T
+CONFORMISTS  K AH0 N - F AO1 R - M AH0 S T S
+CONFORMISTS(2)  K AH0 N - F AO1 R - M AH0 S S
+CONFORMISTS(3)  K AH0 N - F AO1 R - M AH0 S
+CONFORMITY  K AH0 N - F AO1 R - M AH0 - T IY0
+CONFORMS  K AH0 N - F AO1 R M Z
+CONFORTI  K AA0 N - F AO1 R - T IY0
+CONFOUND  K AA0 N - F AW1 N D
+CONFOUND(2)  K AA1 N - F AW2 N D
+CONFOUND(3)  K AH0 N - F AW1 N D
+CONFOUNDED  K AH0 N - F AW1 N - D IH0 D
+CONFOUNDING  K AH0 N - F AW1 N - D IH0 NG
+CONFOUNDS  K AH0 N - F AW1 N D Z
+CONFRONT  K AH0 N - F R AH1 N T
+CONFRONTATION  K AA2 N - F R AH0 N - T EY1 - SH AH0 N
+CONFRONTATIONAL  K AA2 N - F R AH0 N - T EY1 - SH AH0 - N AH0 L
+CONFRONTATIONS  K AA2 N - F R AH0 N - T EY1 - SH AH0 N Z
+CONFRONTED  K AH0 N - F R AH1 N - T AH0 D
+CONFRONTED(2)  K AH0 N - F R AH1 N - T IH0 D
+CONFRONTING  K AH0 N - F R AH1 N - T IH0 NG
+CONFRONTS  K AH0 N - F R AH1 N T S
+CONFUCIAN  K AH0 N - F Y UW1 - SH AH0 N
+CONFUCIANISM  K AH0 N - F Y UW1 - SH AH0 - N IH2 - Z AH0 M
+CONFUCIUS  K AH0 N - F Y UW1 - SH AH0 S
+CONFUSE  K AH0 N - F Y UW1 Z
+CONFUSED  K AH0 N - F Y UW1 Z D
+CONFUSES  K AH0 N - F Y UW1 - Z IH0 Z
+CONFUSING  K AH0 N - F Y UW1 - Z IH0 NG
+CONFUSINGLY  K AH0 N - F Y UW1 - Z IH0 NG - L IY0
+CONFUSION  K AH0 N - F Y UW1 - ZH AH0 N
+CONFUSIONS  K AH0 N - F Y UW1 - ZH AH0 N Z
+CONG  K AO1 NG
+CONGA  K AO1 NG - G AH0
+CONGDON  K AA1 NG - D AH0 N
+CONGEAL  K AH0 N - JH IY1 L
+CONGEALED  K AH0 N - JH IY1 L D
+CONGENIAL  K AH0 N - JH IY1 - N Y AH0 L
+CONGENIALITY  K AH0 N - JH IY2 - N IY0 - AE1 - L AH0 - T IY0
+CONGENITAL  K AH0 N - JH EH1 - N AH0 - T AH0 L
+CONGER  K AO1 NG - ER0
+CONGEST  K AH0 N - JH EH1 S T
+CONGESTED  K AH0 N - JH EH1 - S T AH0 D
+CONGESTED(2)  K AH0 N - JH EH1 - S T IH0 D
+CONGESTION  K AH0 N - JH EH1 S - CH AH0 N
+CONGESTIVE  K AH0 N - JH EH1 - S T IH0 V
+CONGLETON  K AA1 NG - G AH0 L - T AA0 N
+CONGLOMERATE  K AH0 N - G L AA1 - M ER0 - AH0 T
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+CONGLOMERATES  K AH0 N - G L AA1 - M ER0 - AH0 T S
+CONGLOMERATION  K AH0 N - G L AA2 - M ER0 - EY1 - SH AH0 N
+CONGO  K AA1 NG - G OW0
+CONGRATULATE  K AH0 N - G R AE1 - CH AH0 - L EY2 T
+CONGRATULATED  K AH0 N - G R AE1 - CH AH0 - L EY2 - T IH0 D
+CONGRATULATING  K AH0 N - G R AE1 - CH AH0 - L EY2 - T IH0 NG
+CONGRATULATION  K AH0 N - G R AE2 - CH AH0 - L EY1 - SH AH0 N
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+CONGRATULATORY  K AH0 N - G R AE1 - CH AH0 - L AH0 - T AO2 - R IY0
+CONGREGATE  K AA1 NG - G R AH0 - G EY2 T
+CONGREGATED  K AA1 NG - G R IH0 - G EY2 - T IH0 D
+CONGREGATION  K AA2 NG - G R AH0 - G EY1 - SH AH0 N
+CONGREGATION'S  K AA2 NG - G R AH0 - G EY1 - SH AH0 N Z
+CONGREGATIONAL  K AA2 NG - G R AH0 - G EY1 - SH AH0 - N AH0 L
+CONGREGATIONS  K AA2 NG - G R AH0 - G EY1 - SH AH0 N Z
+CONGRESS  K AA1 NG - G R AH0 S
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+CONGRESS'S  K AA1 NG - G R AH0 - S IH0 Z
+CONGRESSES  K AA1 NG - G R AH0 - S IH0 Z
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+CONGRESSIONALLY(2)  K AH0 N - G R EH1 SH - N AH0 - L IY0
+CONGRESSMAN  K AA1 NG - G R AH0 S - M AH0 N
+CONGRESSMAN'S  K AA1 NG - G R AH0 S - M AH0 N Z
+CONGRESSMEN  K AA1 NG - G R AH0 S - M IH0 N
+CONGRESSPEOPLE  K AA1 NG - G R AH0 - S P IY2 - P AH0 L
+CONGRESSPERSON  K AA1 NG - G R AH0 - S P ER2 - S AH0 N
+CONGRESSPERSONS  K AA1 NG - G R AH0 - S P ER2 - S AH0 N Z
+CONGRESSWOMAN  K AA1 NG - G R AH0 S - W UH2 - M AH0 N
+CONGRESSWOMAN'S  K AA1 NG - G R AH0 S - W UH2 - M AH0 N Z
+CONGRESSWOMEN  K AA1 NG - G R AH0 S - W IH2 - M IH0 N
+CONGROVE  K AA1 NG - G R AH0 V
+CONGRUENCE  K AO1 N - G R UW0 - AH0 N S
+CONGRUITY  K AH0 N - G R UW1 - AH0 - T IY0
+CONIC  K AA1 - N IH0 K
+CONIC(2)  K OW1 - N IH0 K
+CONICAL  K AA1 - N IH0 - K AH0 L
+CONICAL(2)  K OW1 - N IH0 - K AH0 L
+CONICS  K AA1 - N IH0 K S
+CONICS(2)  K OW1 - N IH0 K S
+CONIFER  K AA1 - N AH0 - F ER0
+CONIFER'S  K AA1 - N AH0 - F ER0 Z
+CONIFEROUS  K AH0 - N IH1 - F ER0 - AH0 S
+CONIFERS  K AA1 - N AH0 - F ER0 Z
+CONIGLIARO  K AH0 - N IH2 G - L IY0 - AA1 - R OW0
+CONIGLIO  K AH0 - N IH1 G - L IY0 - OW0
+CONISTON  K AA1 - N AH0 - S T AH0 N
+CONJECTURE  K AH0 N - JH EH1 K - CH ER0
+CONJECTURE(2)  K AH0 N - JH EH1 K - SH ER0
+CONJECTURES  K AH0 N - JH EH1 K - CH ER0 Z
+CONJECTURES(2)  K AH0 N - JH EH1 K - SH ER0 Z
+CONJOIN  K AA2 N - JH OY1 N
+CONJOINED  K AA2 N - JH OY1 N D
+CONJUGAL  K AA1 N - JH AH0 - G AH0 L
+CONJUGATE  K AA2 N - JH AH0 - G EY1 T
+CONJUGATE(2)  K AA1 N - JH AH0 - G EY2 T
+CONJUGATED  K AA2 N - JH AH0 - G EY1 - T IH0 D
+CONJUGATED(2)  K AA1 N - JH AH0 - G EY2 - T IH0 D
+CONJUGATES  K AA2 N - JH AH0 - G EY1 T S
+CONJUGATES(2)  K AA1 N - JH AH0 - G EY2 T S
+CONJUGATION  K AA2 N - JH AH0 - G EY1 - SH AH0 N
+CONJUGATIONS  K AA2 N - JH AH0 - G EY1 - SH AH0 N Z
+CONJUL  K AA1 N - JH AH0 L
+CONJUNCTION  K AH0 N - JH AH1 NG K - SH AH0 N
+CONJUNCTIONS  K AH0 N - JH AH1 NG K - SH AH0 N Z
+CONJUNCTIVA  K AA2 N - JH AH0 NG K - T AY1 - V AH0
+CONJURE  K AA1 N - JH ER0
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+CONJURES  K AA1 N - JH ER0 Z
+CONJURING  K AA1 N - JH ER0 - IH0 NG
+CONJUROR  K AA1 N - JH ER0 - ER0
+CONK  K AA1 NG K
+CONKEL  K AA1 NG - K AH0 L
+CONKEY  K AA1 N - K IY0
+CONKIN  K AA1 NG - K IH0 N
+CONKLE  K AA1 NG - K AH0 L
+CONKLIN  K AA1 NG - K L IH0 N
+CONKLING  K AA1 NG - K L IH0 NG
+CONKRIGHT  K AA1 NG K - R AY2 T
+CONLAN  K AA1 N - L AH0 N
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+CONLEY  K AA1 N - L IY0
+CONLIN  K AA1 N - L IH0 N
+CONLON  K AA1 N - L AH0 N
+CONLOW  K AA1 N - L OW0
+CONLY  K AA1 N - L IY0
+CONN  K AA1 N
+CONN.  K AA1 N
+CONN.(2)  K AH0 - N EH1 - T AH0 - K AH0 T
+CONNALLY  K AA1 - N AH0 - L IY0
+CONNALLY'S  K AA1 - N AH0 - L IY0 Z
+CONNAUGHT  K AA1 - N AO0 T
+CONNAUGHT'S  K AA1 - N AO0 T S
+CONNAUGHTON  K AA1 - N AO0 - T AA0 N
+CONNAWAY  K AA1 N - AH0 - W EY2
+CONNECT  K AH0 - N EH1 K T
+CONNECTED  K AH0 - N EH1 K - T AH0 D
+CONNECTED(2)  K AH0 - N EH1 K - T IH0 D
+CONNECTER  K AH0 - N EH1 K - T ER0
+CONNECTICUT  K AH0 - N EH1 - T AH0 - K AH0 T
+CONNECTICUT'S  K AH0 - N EH1 - T AH0 - K AH0 T S
+CONNECTING  K AH0 - N EH1 K - T IH0 NG
+CONNECTION  K AH0 - N EH1 K - SH AH0 N
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+CONNECTIVE  K AH0 - N EH1 K - T IH0 V
+CONNECTIVITY  K AH0 - N EH0 K - T IH1 - V IH0 - T IY0
+CONNECTOR  K AH0 - N EH1 K - T ER0
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+CONNECTS  K AH0 - N EH1 K T S
+CONNED  K AA1 N D
+CONNEELY  K AH0 - N IY1 - L IY0
+CONNELL  K AA1 - N AH0 L
+CONNELLEY  K AA1 - N IH0 - L IY0
+CONNELLY  K AA1 - N AH0 - L IY0
+CONNELLY'S  K AA1 - N AH0 - L IY0 Z
+CONNELY  K AA1 N - L IY0
+CONNER  K AA1 - N ER0
+CONNER'S  K AA1 - N ER0 Z
+CONNERLY  K AA1 - N ER0 - L IY0
+CONNERS  K AA1 - N ER0 Z
+CONNERY  K AA1 - N ER0 - IY0
+CONNERY'S  K AA1 - N ER0 - IY0 Z
+CONNETT  K AA1 - N IH0 T
+CONNICK  K AA1 - N IH0 K
+CONNIE  K AO1 - N IY0
+CONNIE'S  K AO1 - N IY0 Z
+CONNIFF  K AA1 - N IH0 F
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+CONNIPTION  K AH0 - N IH1 P - SH AH0 N
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+CONNON  K AA1 - N AH0 N
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+CONNOTE  K AH0 - N OW1 T
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+CONNY  K AA1 - N IY0
+CONOCO  K AA1 - N AH0 - K OW0
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+CONOCO(2)  K AH0 - N AA1 - K OW0
+CONOLLY  K AA1 - N OW0 - L IY0
+CONOLY  K AA1 - N OW0 - L IY0
+CONOVER  K AA1 - N AH0 - V ER0
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+CONQUERING  K AA1 NG - K ER0 - IH0 NG
+CONQUEROR  K AA1 NG - K ER0 - ER0
+CONQUEROR'S  K AA1 NG - K ER0 - ER0 Z
+CONQUERORS  K AA1 NG - K ER0 - ER0 Z
+CONQUERS  K AA1 NG - K ER0 Z
+CONQUEST  K AA1 NG - K W EH0 S T
+CONQUEST'S  K AA1 NG - K W EH0 S T S
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+CONRAC  K AA1 N - R AE0 K
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+CONRADINE  K AA1 N - R AH0 - D AY2 N
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+CONRAIL'S  K AA1 N - R EY2 L Z
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+CONROY  K AO1 N - R OY0
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+CONSECRATION  K AA2 N - S AH0 - K R EY1 - SH AH0 N
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+CONSENTINO  K AA0 N - S EH0 N - T IY1 - N OW0
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+CONSEQUENT  K AA1 N - S AH0 - K W AH0 N T
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+CONSER  K AA1 N - S ER0
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+CONSERVATISM  K AH0 N - S ER1 - V AH0 - T IH2 - Z AH0 M
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+CRAVER  K R EY1 - V ER0
+CRAVES  K R EY1 V Z
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+CRAVIN  K R EY1 - V IH0 N
+CRAVING  K R EY1 - V IH0 NG
+CRAVINGS  K R EY1 - V IH0 NG Z
+CRAW  K R AO1
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+CRAWFORD  K R AO1 - F ER0 D
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+CRAWFORDSVILLE  K R AO1 - F ER0 D Z - V IH2 L
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+CRAWSHAW  K R AO1 - SH AO2
+CRAXI  K R AE1 K - S IY0
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+CRAY'S  K R EY1 Z
+CRAYCRAFT  K R EY1 - K R AE2 F T
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+CRAZILY  K R EY1 - Z AH0 - L IY0
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+CREAGH  K R IY1 G
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+CREAKED  K R IY1 K T
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+CREAKY  K R IY1 - K IY0
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+CREAMIEST  K R IY1 - M IY0 - IH0 S T
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+CREASON  K R IY1 - S AH0 N
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+CREATE-A-BOOK  K R IY0 - EY2 - T AH0 - B UH1 K
+CREATED  K R IY0 - EY1 - T AH0 D
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+CREATES  K R IY0 - EY1 T S
+CREATH  K R EH1 TH
+CREATING  K R IY0 - EY1 - T IH0 NG
+CREATION  K R IY0 - EY1 - SH AH0 N
+CREATIONISM  K R IY0 - EY1 - SH AH0 N - IH2 - Z AH0 M
+CREATIONS  K R IY0 - EY1 - SH AH0 N Z
+CREATIVE  K R IY0 - EY1 - T IH0 V
+CREATIVELY  K R IY0 - EY1 - T IH0 V - L IY0
+CREATIVENESS  K R IY0 - EY1 - T IH0 V - N AH0 S
+CREATIVITY  K R IY2 - EY0 - T IH1 - V AH0 - T IY0
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+CREATOLOGISTS(3)  K R IY0 - EY2 - T AO1 - L AH0 - JH IH0 S
+CREATOR  K R IY0 - EY1 - T ER0
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+CREDEUR  K R IH0 - D ER1
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+CREDIBLE  K R EH1 - D AH0 - B AH0 L
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+CREDITANSTALT  K R EH2 - D IH1 - T AH0 N SH - T AO2 L T
+CREDITBANK  K R EH1 - D IH0 T - B AE2 NG K
+CREDITED  K R EH1 - D AH0 - T AH0 D
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+CREDITORS'  K R EH1 - D IH0 - T ER0 Z
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+CREDITWORTHINESS  K R EH1 - D IH0 T - W ER2 - DH IY0 - N AH0 S
+CREDITWORTHY  K R EH1 - D IH0 T - W ER2 - DH IY0
+CREDLE  K R EH1 - D AH0 L
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+CREER  K R IH1 R
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+CREME  K R IY1 M
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+CREOSOTE  K R IY1 - AH0 - S OW2 T
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+CRESCI  K R EH1 - S IY0
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+CRESTING  K R EH1 - S T IH0 NG
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+CREUTZFELDT  K R UH1 T S - F EH0 L D
+CREUTZFELDT(2)  K R UH1 T S - F EH0 L T
+CREVELING  K R EH1 - V AH0 L - IH0 NG
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+CRIMINOLOGY  K R IH2 - M IH0 - N AA1 - L AH0 - JH IY0
+CRIMM  K R IH1 M
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+CRIMP  K R IH1 M P
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+CRINER  K R AY1 - N ER0
+CRINGE  K R IH1 N JH
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+CRIPPS  K R IH1 P S
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+CRISANTI  K R IH0 - S AE1 N - T IY0
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+CRISE  K R AY1 Z
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+CRISSCROSS  K R IH1 S - K R AO2 S
+CRISSCROSSED  K R IH1 S - K R AO2 S T
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+CRISTIANI'S  K R IH2 - S T IY0 - AA1 - N IY0 Z
+CRISTIANI'S(2)  K R IH2 - S CH IY0 - AA1 - N IY0 Z
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+CRITERIA  K R AY0 - T IH1 - R IY0 - AH0
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+DECLARANT  D IH0 - K L EH1 - R AH0 N T
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+DECLARE  D IH0 - K L EH1 R
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+DECLARING  D IH0 - K L EH1 - R IH0 NG
+DECLASSIFIED  D IH0 - K L AE1 - S AH0 - F AY2 D
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+DECLERCK  D AH0 K - L ER1 K
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+DECLERQUE  D AH0 K - L ER1 K
+DECLERQUE'S  D AH0 K - L ER1 K S
+DECLINE  D IH0 - K L AY1 N
+DECLINED  D IH0 - K L AY1 N D
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+DECLINES  D IH0 - K L AY1 N Z
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+DECOMPOSE  D IY2 - K AH0 M - P OW1 Z
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+DECONSTRUCT  D IY2 - K AH0 N - S T R AH1 K T
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+DECORATE  D EH1 - K ER0 - EY2 T
+DECORATED  D EH1 - K ER0 - EY2 - T AH0 D
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+DECORATING  D EH1 - K ER0 - EY2 - T IH0 NG
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+DEFORGE  D EH1 - F ER0 G
+DEFORM  D IY2 - F AO1 R M
+DEFORMATION  D IY2 - F AO0 R - M EY1 - SH AH0 N
+DEFORMED  D IH0 - F AO1 R M D
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+DEGENERACY  D IH0 - JH EH1 - N ER0 - AH0 - S IY0
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+DEGRADE  D IH0 - G R EY1 D
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+DELINEATE  D IH0 - L IH1 - N IY0 - EY2 T
+DELINEATED  D IH0 - L IH1 - N IY0 - EY2 - T IH0 D
+DELINEATES  D IH0 - L IH1 - N IY0 - EY2 T S
+DELINEATING  D IH0 - L IH1 - N IY0 - EY2 - T IH0 NG
+DELINEATION  D IH0 - L IH2 - N IY0 - EY1 - SH AH0 N
+DELINQUENCIES  D IH0 - L IH1 NG - K W AH0 N - S IY0 Z
+DELINQUENCY  D IH0 - L IH1 NG - K W AH0 N - S IY0
+DELINQUENT  D IH0 - L IH1 NG - K W AH0 N T
+DELINQUENTS  D IH0 - L IH1 NG - K W AH0 N T S
+DELIO  D EY1 - L IY0 - OW0
+DELIRIOUS  D IH0 - L IH1 - R IY0 - AH0 S
+DELIRIUM  D IH0 - L IH1 - R IY0 - AH0 M
+DELISA  D EH0 - L IY1 - S AH0
+DELISE  D EH1 - L AY0 Z
+DELISI  D EH0 - L IY1 - S IY0
+DELISIO  D EH0 - L IY1 - S IY0 - OW0
+DELISLE  D IH0 - L AY1 L
+DELIST  D IY2 - L IH1 S T
+DELISTED  D IY2 - L IH1 - S T IH0 D
+DELISTING  D IY0 - L IH1 - S T IH0 NG
+DELIVER  D IH0 - L IH1 - V ER0
+DELIVERABLE  D IH0 - L IH1 - V ER0 - AH0 - B AH0 L
+DELIVERABLE(2)  D IH0 - L IH1 - V R AH0 - B AH0 L
+DELIVERANCE  D IH0 - L IH1 - V ER0 - AH0 N S
+DELIVERANCE(2)  D IH0 - L IH1 - V R AH0 N S
+DELIVERED  D IH0 - L IH1 - V ER0 D
+DELIVERER  D IH0 - L IH1 - V ER0 - ER0
+DELIVERERS  D IH0 - L IH1 - V ER0 - ER0 Z
+DELIVERIES  D IH0 - L IH1 - V ER0 - IY0 Z
+DELIVERIES(2)  D IH0 - L IH1 - V R IY0 Z
+DELIVERING  D IH0 - L IH1 - V ER0 - IH0 NG
+DELIVERS  D IH0 - L IH1 - V ER0 Z
+DELIVERY  D IH0 - L IH1 - V ER0 - IY0
+DELK  D EH1 L K
+DELKER  D EH1 L - K ER0
+DELL  D EH1 L
+DELL'AQUILA  D EH1 - L AH0 - K W IY1 - L AH0
+DELL'S  D EH1 L Z
+DELLA  D EH1 - L AH0
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+DELLAERT(2)  D EH1 - L ER0 T
+DELLAPENNA  D EH1 - L AH0 - P EH2 - N AH0
+DELLAQUILA  D EY0 - L AA0 K - W IY1 - L AH0
+DELLAROCCO  D EH1 - L ER0 - OW0 - K OW0
+DELLAVALLE  D EH1 - L AH0 - V AA0 - L IY0
+DELLAVECCHIA  D EH1 - L AH0 - V EH2 - K IY0 - AH0
+DELLE  D EH1 L
+DELLER  D EH1 - L ER0
+DELLIGATTI  D EH0 - L IY0 - G AA1 - T IY0
+DELLING  D EH1 - L IH0 NG
+DELLINGER  D EH1 - L IH0 - NG ER0
+DELLIS  D EH1 - L IH0 S
+DELLOLIO  D EH0 - L OW1 - L IY0 - OW0
+DELLUMS  D EH1 - L AH0 M Z
+DELMA  D EH1 L - M AH0
+DELMAN  D EH1 L - M AH0 N
+DELMAR  D EH1 L - M ER0
+DELMARVA  D EH2 L - M AA1 R - V AH0
+DELMAS  D EH1 L - M AH0 Z
+DELMASTRO  D EH2 L - M AE1 - S T R OW0
+DELMED  D EH1 L - M EH2 D
+DELMED'S  D EH1 L - M EH2 D Z
+DELMER  D EH1 L - M ER0
+DELMONACO  D EH0 L - M OW0 - N AA1 - K OW0
+DELMONICO  D EH0 L - M AA0 - N IY1 - K OW0
+DELMONT  D EY1 L - M OW0 N T
+DELMONTE  D EH0 L - M AA1 N - T IY0
+DELMORE  D EH1 L - M AO0 R
+DELNEGRO  D EH2 L - N EH1 - G R OW0
+DELNERO  D EH0 L - N EH1 - R OW0
+DELO  D EH1 - L OW0
+DELOACH  D EH1 - L OW0 CH
+DELOATCH  D EH1 - L OW0 CH
+DELOITTE  D AH0 - L OY1 T
+DELONEY  D EH1 - L AH0 - N IY0
+DELONG  D AH0 - L AO1 NG
+DELORA  D EH0 - L AO1 - R AH0
+DELORE  D AH0 - L AO1 R
+DELORE'S  D AH0 - L AO1 R Z
+DELORE'S(2)  D AH0 - L AO1 - R IY0 Z
+DELORE(2)  D AH0 - L AO1 - R IY0
+DELOREAN  D AH0 - L AO1 - R IY0 - AH0 N
+DELORENZO  D EH0 - L AO0 - R EH1 N - Z OW0
+DELORENZO(2)  D EY2 - L AO0 - R EH1 N - Z OW0
+DELORES  D AH0 - L AO1 - R IH0 S
+DELOREY  D EH1 - L ER0 - IY0
+DELORIA  D EH0 - L AO1 - R IY0 - AH0
+DELORIS  D EH1 - L ER0 - IH0 S
+DELORME  D EH0 - L AO1 R - M IY0
+DELORS  D AH0 - L AO1 R Z
+DELOSH  D EH1 - L AH0 SH
+DELOSREYES  D IH0 - L AA1 - S ER0 - AY0 Z
+DELOSREYES(2)  D EH0 - L OW0 - S R EY1 Z
+DELOSREYES(3)  D EH0 - L OW0 - S R EY1 - AH0 Z
+DELOSSANTOS  D EY0 - L OW0 - S AA1 N - T OW0 Z
+DELOUIS  D EH2 - L UW0 - IY1 Z
+DELOZIER  D EH1 - L AH0 - Z IY0 - ER0
+DELP  D EH1 L P
+DELPH  D EH1 L F
+DELPHAX  D EH1 L - F AE0 K S
+DELPHI  D EH1 L - F AY0
+DELPHIA  D EH1 L - F IY0 - AH0
+DELPHIC  D EH1 L - F IH0 K
+DELPHINA  D EH0 L - F IY1 - N AH0
+DELPHINE  D EH0 L - F IY1 - N IY0
+DELPINO  D EH2 L - P IY1 - N OW0
+DELPIZZO  D EH0 L - P IY1 - Z OW0
+DELPONTE  D EH0 L - P OW1 N - T IY0
+DELPOZO  D EH2 L - P OW1 - Z OW0
+DELPRETE  D EH1 L - P R IY0 T
+DELPRIORE  D EH0 L - P R IY0 - AO1 - R IY0
+DELRAY  D EH2 L - R EY1
+DELRE  D EH1 L R
+DELREAL  D EH1 - L R AH0 L
+DELRINA  D EH2 L - R IY1 - N AH0
+DELRINA'S  D EH2 L - R IY1 - N AH0 Z
+DELRIO  D EH1 L - R IY0 - OW0
+DELROSARIO  D EH0 L - R OW0 - S AA1 - R IY0 - OW0
+DELROSSI  D EH0 L - R AA1 - S IY0
+DELROSSO  D EH0 L - R OW1 - S OW0
+DELSANTO  D EH0 L - S AA1 N - T OW0
+DELSIGNORE  D EH0 L - S IY0 G - N AO1 - R IY0
+DELTA  D EH1 L - T AH0
+DELTA'S  D EH1 L - T AH0 Z
+DELTACORP  D EH1 L - T AH0 - K AO2 R P
+DELTADROMEUS  D EH2 L - T AH0 - D R OW1 - M AH0 S
+DELTAIC  D EH0 L - T EY1 - IH0 K
+DELTAK  D EH1 L - T AE2 K
+DELTEC  D EH1 L - T EH2 K
+DELTONA  D EH2 L - T OW1 - N AH0
+DELTONA'S  D EH2 L - T OW1 - N AH0 Z
+DELTORO  D EH0 L - T AO1 - R OW0
+DELUCA  D IH0 - L UW1 - K AH0
+DELUCAS  D IH0 - L UW1 - K AH0 Z
+DELUCCA  D EH0 - L UW1 - K AH0
+DELUCCHI  D EH0 - L UW1 - K IY0
+DELUCCIA  D EH0 - L UW1 - CH AH0
+DELUCIA  D EH0 - L UW1 - CH AH0
+DELUDE  D IH0 - L UW1 D
+DELUDED  D IH0 - L UW1 - D IH0 D
+DELUDING  D IH0 - L UW1 - D IH0 NG
+DELUGE  D EH1 - L Y UW0 JH
+DELUGED  D EH1 - L Y UW0 JH D
+DELUISE  D EH0 - L UW1 - S IY0
+DELUNA  D EH0 - L UW1 - N AH0
+DELUSION  D IH0 - L UW1 - ZH AH0 N
+DELUSIONAL  D IH0 - L UW1 - ZH AH0 - N AH0 L
+DELUSIONS  D IH0 - L UW1 - ZH AH0 N Z
+DELUXE  D AH0 - L AH1 K S
+DELVALLE  D EH2 L - V AE1 - L IY0
+DELVALLE'S  D EH2 L - V AE1 - L IY0 Z
+DELVE  D EH1 L V
+DELVECCHIO  D EH2 L - V EH1 - K IY0 - OW0
+DELVED  D EH1 L V D
+DELVES  D EH1 L V Z
+DELVING  D EH1 L - V IH0 NG
+DELWIN  D EH1 L - W IH0 N
+DELWIP  D EH1 L - W IH0 P
+DELWYN  D EH1 L - W IH0 N
+DELZELL  D EH1 L - Z AH0 L
+DELZER  D EH1 L - Z ER0
+DEMAGGIO  D IH0 - M AA1 - JH IY0 - OW0
+DEMAGOGIC  D EH2 - M AH0 - G AA1 - JH IH0 K
+DEMAGOGUE  D EH1 - M AH0 - G AA2 G
+DEMAGOGUERY  D EH1 - M AH0 - G AA2 - G ER0 - IY0
+DEMAGOGUES  D EH1 - M AH0 - G AA2 G Z
+DEMAGOGUING  D EH1 - M AH0 - G AA2 - G IH0 NG
+DEMAGOGY  D EH1 - M AH0 - G AA2 - JH IY0
+DEMAIN  D IH0 - M EY1 N
+DEMAIO  D IH0 - M AA1 - IY0 - OW0
+DEMAIO(2)  D IH0 - M AA1 - OW0
+DEMAN  D IY1 - M AH0 N
+DEMAND  D IH0 - M AE1 N D
+DEMANDED  D IH0 - M AE1 N - D AH0 D
+DEMANDED(2)  D IH0 - M AE1 N - D IH0 D
+DEMANDING  D IH0 - M AE1 N - D IH0 NG
+DEMANDINGLY  D IH0 - M AE1 N - D IH0 NG - L IY0
+DEMANDS  D IH0 - M AE1 N D Z
+DEMAR  D IH0 - M AA1 R
+DEMARAIS  D EH1 - M ER0 - EY0
+DEMARAY  D EH1 - M ER0 - EY0
+DEMARCATION  D IY2 - M AA0 R - K EY1 - SH AH0 N
+DEMARCATIONS  D IY2 - M AA0 R - K EY1 - SH AH0 N Z
+DEMARCHE  D IH0 - M AA1 R CH
+DEMARCHE(2)  D IY0 - M AA1 R CH
+DEMARCHI  D IH0 - M AA1 R - K IY0
+DEMARCO  D IH0 - M AA1 R - K OW0
+DEMARCUS  D EH1 - M AA0 R - K IH0 S
+DEMAREE  D EH0 - M ER0 - IY1
+DEMAREST  D EY0 - M AA0 - R EY1 - IH0 S T
+DEMAREST(2)  D EH1 - M ER0 - IH0 S T
+DEMARIA  D IH0 - M AA1 - R IY0 - AH0
+DEMARINIS  D EH1 - M ER0 - IH0 - N IH0 S
+DEMARINO  D IH0 - M AA0 - R IY1 - N OW0
+DEMARIO  D IH0 - M AA1 - R IY0 - OW0
+DEMARIS  D EH1 - M ER0 - IH0 S
+DEMARK  D AH0 - M AA1 R K
+DEMARS  D EH1 - M ER0 Z
+DEMARSH  D EH1 - M AA0 R SH
+DEMARTIN  D IH0 - M AA1 R - T IH0 N
+DEMARTINI  D IH0 - M AA0 R - T IY1 - N IY0
+DEMARTINO  D IH0 - M AA0 R - T IY1 - N OW0
+DEMARY  D EH1 - M EH0 - R IY0
+DEMARZO  D IH0 - M AA1 R - Z OW0
+DEMAS  D IY1 - M AH0 S
+DEMASI  D IH0 - M AA1 - S IY0
+DEMASTERS  D IY1 - M AE0 - S T ER0 Z
+DEMATTEIS  D EH1 - M AH0 - T AY0 Z
+DEMATTEO  D IH0 - M AA1 - T IY0 - OW0
+DEMATTIA  D IH0 - M AA1 - SH AH0
+DEMAURO  D IH0 - M AO1 - R OW0
+DEMAY  D EH1 - M EY0
+DEMAYO  D EY0 - M EY1 - OW0
+DEMBECK  D EH1 M - B EH2 K
+DEMBINSKI  D IH0 M - B IH1 N - S K IY0
+DEMBOWSKI  D IH0 M - B AO1 F S - K IY0
+DEMBSKI  D EH1 M S - K IY0
+DEMBY  D EH1 M - B IY0
+DEMCHAK  D EH1 M - CH AH0 K
+DEMEAN  D IH0 - M IY1 N
+DEMEANED  D IH0 - M IY1 N D
+DEMEANING  D IH0 - M IY1 - N IH0 NG
+DEMEANOR  D IH0 - M IY1 - N ER0
+DEMEANS  D IH0 - M IY1 N Z
+DEMEL  D EH1 - M AH0 L
+DEMELLO  D IH0 - M EH1 - L OW0
+DEMELO  D IH0 - M EH1 - L OW0
+DEMENT  D AH0 - M EH1 N T
+DEMENTED  D IH0 - M EH1 N - T IH0 D
+DEMENTIA  D IH0 - M EH1 N - SH IY0 - AH0
+DEMEO  D IY1 - M IY0 - OW0
+DEMEREE  D EH1 - M ER0 - IY0
+DEMERGER  D IY0 - M ER1 - JH ER0
+DEMERIST  D IH0 - M ER1 - IH0 S T
+DEMERIST'S  D IH0 - M ER1 - IH0 S T S
+DEMERIST'S(2)  D IH0 - M ER1 - IH0 S S
+DEMERIST'S(3)  D IH0 - M ER1 - IH0 S
+DEMERIST(2)  D EH1 - M ER0 - IH0 S T
+DEMERIT  D IY0 - M EH1 - R AH0 T
+DEMERITS  D IY0 - M EH1 - R AH0 T S
+DEMERITT  D EH1 - M ER0 - IH0 T
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+DEMETRE  D EH0 - M IY1 - T ER0
+DEMETRIA  D IH0 - M EH1 - T R IY0 - AH0
+DEMETRIO  D IH0 - M EH1 - T R IY0 - OW0
+DEMETRIOU  D IH0 - M EH0 - T R IY1 - UW0
+DEMETRIUS  D IH0 - M IY1 - T R IY0 - AH0 S
+DEMEYER  D EH1 - M AY0 - ER0
+DEMI  D EH1 - M IY0
+DEMI'S  D EH1 - M IY0 Z
+DEMICCO  D IH0 - M IY1 - K OW0
+DEMICHAEL  D EH1 - M IH0 - K EH0 L
+DEMICHELE  D EH1 - M IH0 - K AH0 L
+DEMICK  D EH1 - M IH0 K
+DEMILIO  D IH0 - M IY1 - L IY0 - OW0
+DEMILITARIZATION  D IY0 - M IH2 - L AH0 - T ER0 - AH0 - Z EY1 - SH AH0 N
+DEMILITARIZE  D IY0 - M IH1 - L AH0 - T ER0 - AY2 Z
+DEMILITARIZED  D IY0 - M IH1 - L AH0 - T ER0 - AY2 Z D
+DEMILITARIZES  D IY0 - M IH1 - L AH0 - T ER0 - AY2 - Z IH0 Z
+DEMILITARIZING  D IY0 - M IH1 - L AH0 - T ER0 - AY2 - Z IH0 NG
+DEMILLE  D IH0 - M IY1 - L IY0
+DEMILLE(2)  D IH0 - M IH1 L
+DEMILO  D IH0 - M IH1 - L OW0
+DEMILO(2)  D IH0 - M AY1 - L OW0
+DEMING  D EH1 - M IH0 NG
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+DEMIRAG  D EY2 - M IH0 - R AA1 JH
+DEMIREL  D AH0 - M IH1 - R AH0 L
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+DEMISCH  D AH0 - M IH1 SH
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+DEMJANJUK  D EH0 - M Y AA1 - N Y UW0 K
+DEMJANJUK'S  D EH0 - M Y AA1 - N Y UW0 K S
+DEMJANJUK'S(2)  D EH0 - M Y AE1 - N Y UW0 K S
+DEMJANJUK(2)  D EH0 - M Y AE1 - N Y UW0 K
+DEMKO  D EH1 M - K OW0
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+DEMMA  D IY1 - M AH0
+DEMME  D EH1 M
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+DEMMON  D EH1 - M AH0 N
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+DEMOBILIZATION  D IY0 - M OW2 - B AH0 - L AY0 - Z EY1 - SH AH0 N
+DEMOBILIZATION(2)  D IY0 - M OW2 - B AH0 - L AH0 - Z EY1 - SH AH0 N
+DEMOBILIZE  D IH0 - M OW1 - B AH0 - L AY2 Z
+DEMOBILIZED  D IH0 - M OW1 - B AH0 - L AY2 Z D
+DEMOCRACIES  D IH0 - M AA1 - K R AH0 - S IY0 Z
+DEMOCRACY  D IH0 - M AA1 - K R AH0 - S IY0
+DEMOCRACY'S  D IH0 - M AA1 - K R AH0 - S IY0 Z
+DEMOCRAT  D EH1 - M AH0 - K R AE2 T
+DEMOCRAT'S  D EH1 - M AH0 - K R AE2 T S
+DEMOCRATIC  D EH2 - M AH0 - K R AE1 - T IH0 K
+DEMOCRATIC'S  D EH2 - M AH0 - K R AE1 - T IH0 K S
+DEMOCRATICA  D EH2 - M AH0 - K R AE1 - T IH0 - K AH0
+DEMOCRATICALLY  D EH2 - M AH0 - K R AE1 - T IH0 K - L IY0
+DEMOCRATICS  D EH2 - M AH0 - K R AE1 - T IH0 K S
+DEMOCRATIZATION  D IH0 - M AA2 - K R AH0 - T AH0 - Z EY1 - SH AH0 N
+DEMOCRATIZE  D IH0 - M AA1 - K R AH0 - T AY2 Z
+DEMOCRATIZED  D IH0 - M AA1 - K R AH0 - T AY2 Z D
+DEMOCRATIZING  D IH0 - M AA1 - K R AH0 - T AY2 - Z IH0 NG
+DEMOCRATS  D EH1 - M AH0 - K R AE2 T S
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+DEMODULATE  D IY2 - M AA2 - JH AH0 - L EY1 T
+DEMODULATION  D IY2 - M AA2 - JH AH0 - L EY1 - SH AH0 N
+DEMOGRAPHER  D IH0 - M AA1 - G R AH0 - F ER0
+DEMOGRAPHERS  D IH0 - M AA1 - G R AH0 - F ER0 Z
+DEMOGRAPHIC  D EH2 - M AH0 - G R AE1 - F IH0 K
+DEMOGRAPHICALLY  D EH2 - M AH0 - G R AE1 - F IH0 K - L IY0
+DEMOGRAPHICS  D EH2 - M AH0 - G R AE1 - F IH0 K S
+DEMOGRAPHY  D IH0 - M AA1 - G R AH0 - F IY0
+DEMOLISH  D IH0 - M AA1 - L IH0 SH
+DEMOLISHED  D IH0 - M AA1 - L IH0 SH T
+DEMOLISHING  D IH0 - M AA1 - L IH0 - SH IH0 NG
+DEMOLITION  D EH2 - M AH0 - L IH1 - SH AH0 N
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+DEMONIC  D IH0 - M AA1 - N IH0 K
+DEMONIZATION  D IY2 - M AH0 - N AH0 - Z EY1 - SH AH0 N
+DEMONIZE  D IY1 - M AH0 - N AY2 Z
+DEMONIZED  D IY1 - M AH0 - N AY2 Z D
+DEMONIZER  D IY1 - M AH0 - N AY2 - Z ER0
+DEMONIZEZ  D IY1 - M AH0 - N AY2 - Z IH0 Z
+DEMONIZING  D IY1 - M AH0 - N AY2 - Z IH0 NG
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+DEMONSTRABLY  D IH0 - M AA1 N - S T R AH0 - B L IY0
+DEMONSTRATE  D EH1 - M AH0 N - S T R EY2 T
+DEMONSTRATED  D EH1 - M AH0 N - S T R EY2 - T AH0 D
+DEMONSTRATED(2)  D EH1 - M AH0 N - S T R EY2 - T IH0 D
+DEMONSTRATES  D EH1 - M AH0 N - S T R EY2 T S
+DEMONSTRATING  D EH1 - M AH0 N - S T R EY2 - T IH0 NG
+DEMONSTRATION  D EH2 - M AH0 N - S T R EY1 - SH AH0 N
+DEMONSTRATIONS  D EH2 - M AH0 N - S T R EY1 - SH AH0 N Z
+DEMONSTRATIVE  D IH0 - M AA1 N - S T R AH0 - T IH0 V
+DEMONSTRATOR  D EH1 - M AH0 N - S T R EY2 - T ER0
+DEMONSTRATORS  D EH1 - M AH0 N - S T R EY2 - T ER0 Z
+DEMONT  D EH1 - M AH0 N T
+DEMONTE  D AH0 - M AA1 N - T IY0
+DEMOPOULOS  D AH0 - M AA1 - P AH0 - L IH0 S
+DEMORALIZATION  D IH0 - M AO2 - R AH0 - L IH0 - Z EY1 - SH AH0 N
+DEMORALIZE  D IH0 - M AO1 - R AH0 - L AY2 Z
+DEMORALIZED  D IH0 - M AO1 - R AH0 - L AY2 Z D
+DEMORALIZING  D IH0 - M AO1 - R AH0 - L AY2 - Z IH0 NG
+DEMORE  D EH1 - M AO0 R
+DEMOREST  D EY0 - M AO1 - R IH0 S T
+DEMORY  D IH0 - M ER1 - IY0
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+DEMOTED  D IH0 - M OW1 - T IH0 D
+DEMOTION  D IH0 - M OW1 - SH AH0 N
+DEMOTIONS  D IH0 - M OW1 - SH AH0 N Z
+DEMOTT  D AH0 - M AA1 T
+DEMOULIN  D EH1 - M UW0 - L AE0 N
+DEMOV  D EH1 - M AA0 V
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+DEMSKY  D EH1 M S - K IY0
+DEMUR  D IH0 - M ER1
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+DESULTORY  D EH1 - S AH0 L - T AO2 - R IY0
+DETACH  D IH0 - T AE1 CH
+DETACH(2)  D IY0 - T AE1 CH
+DETACHABLE  D IH0 - T AE1 - CH AH0 - B AH0 L
+DETACHABLE(2)  D IY0 - T AE1 - CH AH0 - B AH0 L
+DETACHED  D IH0 - T AE1 CH T
+DETACHED(2)  D IY0 - T AE1 CH T
+DETACHES  D IH0 - T AE1 - CH IH0 Z
+DETACHES(2)  D IY0 - T AE1 - CH AH0 Z
+DETACHMENT  D IH0 - T AE1 CH - M AH0 N T
+DETACHMENT(2)  D IY0 - T AE1 CH - M AH0 N T
+DETAIL  D IH0 - T EY1 L
+DETAIL(2)  D IY1 - T EY0 L
+DETAILED  D IH0 - T EY1 L D
+DETAILEE  D IH0 - T EY2 - L IY1
+DETAILER  D IY1 - T EY0 - L ER0
+DETAILING  D IH0 - T EY1 - L IH0 NG
+DETAILS  D IH0 - T EY1 L Z
+DETAILS(2)  D IY1 - T EY0 L Z
+DETAIN  D IH0 - T EY1 N
+DETAINED  D IH0 - T EY1 N D
+DETAINEE  D IY2 - T EY0 - N IY1
+DETAINEES  D IH0 - T EY2 - N IY1 Z
+DETAINING  D IH0 - T EY1 - N IH0 NG
+DETAMORE  D IH0 - T AA1 - M AO0 R
+DETAR  D IH0 - T AA1 R
+DETAR(2)  D IY0 - T AA0 R
+DETECT  D IH0 - T EH1 K T
+DETECTABLE  D IH0 - T EH1 K - T AH0 - B AH0 L
+DETECTED  D IH0 - T EH1 K - T AH0 D
+DETECTED(2)  D IH0 - T EH1 K - T IH0 D
+DETECTING  D IH0 - T EH1 K - T IH0 NG
+DETECTION  D IH0 - T EH1 K - SH AH0 N
+DETECTIVE  D IH0 - T EH1 K - T IH0 V
+DETECTIVE'S  D IH0 - T EH1 K - T IH0 V Z
+DETECTIVES  D IH0 - T EH1 K - T IH0 V Z
+DETECTOR  D IH0 - T EH1 K - T ER0
+DETECTORS  D IH0 - T EH1 K - T ER0 Z
+DETECTS  D IH0 - T EH1 K T S
+DETEMPLE  D EH1 - T IH0 M - P AH0 L
+DETENTE  D EY0 - T AA1 N T
+DETENTION  D IH0 - T EH1 N - SH AH0 N
+DETENTIONS  D IH0 - T EH1 N - SH AH0 N Z
+DETER  D IH0 - T ER1
+DETERDING  D EH1 - T ER0 - D IH0 NG
+DETERGENT  D IH0 - T ER1 - JH AH0 N T
+DETERGENTS  D IH0 - T ER1 - JH AH0 N T S
+DETERIORATE  D IH0 - T IH1 - R IY0 - ER0 - EY2 T
+DETERIORATED  D IH0 - T IH1 - R IY0 - ER0 - EY2 - T IH0 D
+DETERIORATES  D IH0 - T IH1 - R IY0 - ER0 - EY2 T S
+DETERIORATING  D IH0 - T IH1 - R IY0 - ER0 - EY2 - T IH0 NG
+DETERIORATION  D IH0 - T IH1 - R IY0 - ER0 - EY2 - SH AH0 N
+DETERMAN  D IY1 - T ER0 - M AH0 N
+DETERMENT  D IH0 - T ER1 - M AH0 N T
+DETERMINABLE  D IH0 - T ER1 - M AH0 - N AH0 - B AH0 L
+DETERMINANT  D IH0 - T ER1 - M AH0 - N AH0 N T
+DETERMINANTS  D IH0 - T ER1 - M AH0 - N AH0 N T S
+DETERMINATE  D IH0 - T ER1 - M AH0 - N EY2 T
+DETERMINATION  D IH0 - T ER2 - M AH0 - N EY1 - SH AH0 N
+DETERMINATION'S  D IH0 - T ER2 - M IH0 - N EY1 - SH AH0 N Z
+DETERMINATIONS  D IH0 - T ER2 - M IH0 - N EY1 - SH AH0 N Z
+DETERMINATIVE  D IH0 - T ER1 - M IH0 - N AH0 - T IH2 V
+DETERMINE  D AH0 - T ER1 - M AH0 N
+DETERMINE(2)  D IH0 - T ER1 - M AH0 N
+DETERMINED  D IH0 - T ER1 - M AH0 N D
+DETERMINEDLY  D AH0 - T ER1 - M AH0 - N AH0 D - L IY0
+DETERMINEDLY(2)  D AH0 - T ER1 - M AH0 N D - L IY0
+DETERMINES  D AH0 - T ER1 - M AH0 N Z
+DETERMINES(2)  D IH0 - T ER1 - M AH0 N Z
+DETERMINING  D IH0 - T ER1 - M AH0 - N IH0 NG
+DETERMINISM  D IH0 - T ER1 - M AH0 - N IH2 - Z AH0 M
+DETERMINIST  D IH0 - T ER1 - M AH0 - N AH0 S T
+DETERMINISTIC  D IH0 - T ER2 - M AH0 - N IH1 - S T IH0 K
+DETERRED  D IH0 - T ER1 D
+DETERRENCE  D IH0 - T ER1 - AH0 N S
+DETERRENT  D IH0 - T ER1 - R AH0 N T
+DETERRENTS  D IH0 - T ER1 - AH0 N T S
+DETERRING  D IH0 - T ER1 - IH0 NG
+DETERS  D IH0 - T ER1 Z
+DETERT  D EH1 - T ER0 T
+DETEST  D IH0 - T EH1 S T
+DETEST(2)  D IY0 - T EH1 S T
+DETESTED  D IH0 - T EH1 - S T IH0 D
+DETESTED(2)  D IY0 - T EH1 - S T IH0 D
+DETHERAGE  D EH1 - DH ER0 - IH0 JH
+DETHLEFS  D EH1 TH - L IH0 F S
+DETHLEFSEN  D EH1 TH - L IH0 F - S AH0 N
+DETHLOFF  D EH1 TH - L AO0 F
+DETHOMAS  D IH0 - TH OW1 - M AH0 Z
+DETHOMAS(2)  D IH0 - T AA1 - M AH0 S
+DETHRONE  D IH0 - TH R OW1 N
+DETHRONE(2)  D IY0 - TH R OW1 N
+DETHRONED  D IH0 - TH R OW1 N D
+DETHRONED(2)  D IY0 - TH R OW1 N D
+DETIENNE  D EH1 - T IY0 - EH0 N
+DETJEN  D EH1 T - JH AH0 N
+DETLEFSEN  D EH1 T - L IH0 F - S AH0 N
+DETLOFF  D EH1 T - L AO0 F
+DETMER  D EH1 T - M ER0
+DETONATE  D EH1 - T AH0 - N EY2 T
+DETONATED  D EH1 - T AH0 - N EY2 - T AH0 D
+DETONATING  D EH1 - T AH0 - N EY2 - T IH0 NG
+DETONATION  D EH2 - T AH0 - N EY1 - SH AH0 N
+DETONATIONS  D EH2 - T AH0 - N EY1 - SH AH0 N Z
+DETONATOR  D EH1 - T AH0 - N EY2 - T ER0
+DETONATORS  D EH1 - T AH0 - N EY2 - T ER0 Z
+DETORE  D IH0 - T AO1 - R IY0
+DETOUR  D IH0 - T UH1 R
+DETOUR(2)  D IY1 - T UH0 R
+DETOURED  D IY1 - T UH0 R D
+DETOURS  D IH0 - T UH1 R Z
+DETOURS(2)  D IY1 - T UH0 R Z
+DETOX  D IY1 - T AA2 K S
+DETOXICATION  D IH0 - T AA2 K - S AH0 - K EY1 - SH AH0 N
+DETOXIFICATION  D IH0 - T AA2 K - S IH0 - F IH0 - K EY1 - SH AH0 N
+DETOXIFY  D IH0 - T AA1 K - S AH0 - F AY2
+DETRACT  D IH0 - T R AE1 K T
+DETRACTED  D IH0 - T R AE1 K - T IH0 D
+DETRACTING  D IH0 - T R AE1 K - T IH0 NG
+DETRACTOR(2)  D IY0 - T R AE1 K - T ER0
+DETRACTORS  D IH0 - T R AE1 K - T ER0 Z
+DETRACTORS(2)  D IY0 - T R AE1 K - T ER0 Z
+DETRACTS  D IH0 - T R AE1 K T S
+DETRICH  D EH1 - T R IH0 K
+DETRICK  D EH1 - T R IH0 K
+DETRIMENT  D EH1 - T R AH0 - M AH0 N T
+DETRIMENTAL  D EH2 - T R AH0 - M EH1 N - T AH0 L
+DETRIMENTAL(2)  D EH2 - T R AH0 - M EH1 - N AH0 L
+DETRITUS  D IH0 - T R AY1 - T AH0 S
+DETRITUS(2)  D EH1 - T R AH0 - T AH0 S
+DETRO  D IY1 - T R OW0
+DETROIT  D IH0 - T R OY1 T
+DETROIT'S  D AH0 - T R OY1 T S
+DETROIT'S(2)  D IH0 - T R OY1 T S
+DETROIT(2)  D IY1 - T R OY2 T
+DETROITERS  D AH0 - T R OY1 - T ER0 Z
+DETROITERS(2)  D IY1 - T R OY2 - T ER0 Z
+DETTER  D EH1 - T ER0
+DETTINGER  D EH1 - T IH0 N - JH ER0
+DETTLING  D EH1 T - L IH0 NG
+DETTLOFF  D EH1 T - L AO0 F
+DETTMAN  D EH1 T - M AH0 N
+DETTMANN  D EH1 T - M AH0 N
+DETTMER  D EH1 T - M ER0
+DETTORE  D IH0 - T AO1 - R IY0
+DETTY  D EH1 - T IY0
+DETURK  D EH1 - T ER0 K
+DETWEILER  D EH1 T - W AY2 - L ER0
+DETWILER  D EH1 T - W AY2 - L ER0
+DETZEL  D EH1 T - Z AH0 L
+DEUBEL  D OY1 - B AH0 L
+DEUBLER  D OY1 - B AH0 L - ER0
+DEUBLER(2)  D OY1 - B L ER0
+DEUCE  D UW1 S
+DEUEL  D UW1 - EH0 L
+DEUKMEJIAN  D UW0 K - M EY1 - JH IY0 - AH0 N
+DEUKMEJIAN'S  D UW0 K - M EY1 - JH IY0 - AH0 N Z
+DEUPREE  D UW0 - P R IY1
+DEUSCHLE  D OY1 - SH AH0 L
+DEUSER  D OY1 - S ER0
+DEUSS  D UW1 S
+DEUTCH  D OY1 CH
+DEUTERIUM  D UW0 - T IY1 - R IY0 - AH0 M
+DEUTERONS  D UW1 - T ER0 - AA2 N Z
+DEUTSCH  D OY1 CH
+DEUTSCHE  D OY1 CH
+DEUTSCHEMARK  D OY1 CH - M AA2 R K
+DEUTSCHEMARK'S  D OY1 CH - M AA2 R K S
+DEUTSCHEMARKS  D OY1 CH - M AA2 R K S
+DEUTSCHER  D OY1 - CH ER0
+DEUTSCHLAND  D OY1 CH - L AE0 N D
+DEUTSCHMAN  D OY1 CH - M AH0 N
+DEUTZ  D OY1 T S
+DEUX  D UW1
+DEV  D EH1 V
+DEVA  D EY1 - V AH0
+DEVAL  D IH0 - V AA1 L
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+DEVALL  D EY0 - V AA1 L
+DEVALLE  D IH0 - V AE1 L
+DEVALLE(2)  D IH0 - V AE1 - L IY0
+DEVALUATE  D IH0 - V AE1 L - Y UW0 - EY2 T
+DEVALUATED  D IH0 - V AE1 L - Y UW0 - EY2 - T IH0 D
+DEVALUATION  D IH0 - V AE2 L - Y UW0 - EY1 - SH AH0 N
+DEVALUATION(2)  D IY2 - V AE0 L - Y UW0 - EY1 - SH AH0 N
+DEVALUATIONS  D IY2 - V AE0 L - Y UW0 - EY1 - SH AH0 N Z
+DEVALUE  D IH0 - V AE1 L - Y UW2
+DEVALUED  D IH0 - V AE1 L - Y UW2 D
+DEVALUED(2)  D IY0 - V AE1 L - Y UW2 D
+DEVALUING  D IH0 - V AE1 L - Y UW0 - IH0 NG
+DEVAN  D EH1 - V AH0 N
+DEVANE  D IH0 - V EY1 N
+DEVANEY  D EH1 - V AH0 - N IY0
+DEVANY  D EH1 - V AH0 - N IY0
+DEVASTATE  D EH1 - V AH0 - S T EY2 T
+DEVASTATED  D EH1 - V AH0 - S T EY2 - T AH0 D
+DEVASTATED(2)  D EH1 - V AH0 - S T EY2 - T IH0 D
+DEVASTATING  D EH1 - V AH0 - S T EY2 - T IH0 NG
+DEVASTATINGLY  D EH1 - V AH0 - S T EY2 - T IH0 NG - L IY0
+DEVASTATION  D EH2 - V AH0 - S T EY1 - SH AH0 N
+DEVAUGHN  D EH1 - V AO0 N
+DEVAUL  D IH0 - V OW1 L
+DEVAULT  D IH0 - V OW1
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+DEVEAU  D IH0 - V OW1
+DEVEAUX  D IH0 - V OW1
+DEVELCON  D AH0 - V EH1 L - K AH0 N
+DEVELLE  D AH0 - V EH1 L
+DEVELOP  D IH0 - V EH1 - L AH0 P
+DEVELOPABLE  D IH0 - V EH1 - L AH0 - P AH0 - B AH0 L
+DEVELOPED  D IH0 - V EH1 - L AH0 P T
+DEVELOPER  D IH0 - V EH1 - L AH0 - P ER0
+DEVELOPER'S  D IH0 - V EH1 - L AH0 - P ER0 Z
+DEVELOPERS  D IH0 - V EH1 - L AH0 - P ER0 Z
+DEVELOPERS'  D IH0 - V EH1 - L AH0 - P ER0 Z
+DEVELOPING  D IH0 - V EH1 - L AH0 - P IH0 NG
+DEVELOPMENT  D IH0 - V EH1 - L AH0 P - M AH0 N T
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+DEVELOPMENTAL  D IH0 - V EH2 - L AH0 P - M EH1 N - T AH0 L
+DEVELOPMENTAL(2)  D IH0 - V EH2 - L AH0 P - M EH1 - N AH0 L
+DEVELOPMENTALLY  D IH0 - V EH2 - L AH0 P - M EH1 N - AH0 - L IY0
+DEVELOPMENTALLY(2)  D IH0 - V EH2 - L AH0 P - M EH1 N - T AH0 - L IY0
+DEVELOPMENTS  D IH0 - V EH1 - L AH0 P - M AH0 N T S
+DEVELOPS  D IH0 - V EH1 - L AH0 P S
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+DEVENEY  D EH1 - V IH0 - N IY0
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+DEVENNY  D EH1 - V IH0 - N IY0
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+DEVENS  D IY1 - V AH0 N Z
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+DEVEREUX  D EH1 - V ER0 - UW2
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+DEVERS  D EH1 - V ER0 Z
+DEVEY  D IH0 - V EY1
+DEVIANCE  D IY1 - V IY0 - AH0 N S
+DEVIANCY  D IY1 - V IY0 - EH2 N - S IY0
+DEVIANCY(2)  D IY1 - V Y EH0 N - S IY0
+DEVIANT  D IY1 - V IY0 - AH0 N T
+DEVIANTS  D IY1 - V IY0 - AH0 N T S
+DEVIATE  D IY1 - V IY0 - EY2 T
+DEVIATED  D IY1 - V IY0 - EY2 - T IH0 D
+DEVIATES  D IY1 - V IY0 - EY2 T S
+DEVIATION  D IY2 - V IY0 - EY1 - SH AH0 N
+DEVIATIONS  D IY0 - V IY0 - EY1 - SH AH0 N Z
+DEVICE  D IH0 - V AY1 S
+DEVICE'S  D IH0 - V AY1 - S IH0 Z
+DEVICES  D IH0 - V AY1 - S AH0 Z
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+DEVILISH  D EH1 V - L IH0 SH
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+DEVILISHLY(2)  D EH1 V - L IH0 SH - L IY0
+DEVILLE  D AH0 - V IH1 L
+DEVILLE'S  D AH0 - V IH1 L Z
+DEVILLIER  D AH0 - V IH1 L - Y ER0
+DEVILLIER'S  D AH0 - V IH1 L - Y ER0 S
+DEVILS  D EH1 - V AH0 L Z
+DEVILWOOD  D EH1 - V AH0 L - W UH2 D
+DEVIN  D EH1 - V IH0 N
+DEVINCENT  D EY0 - V IY1 N - S AH0 N T
+DEVINCENTIS  D EH0 - V IH0 N - S EH1 N - T IH0 S
+DEVINCENZI  D IH0 - V IY0 N - CH EH1 N - Z IY0
+DEVINCENZO  D IH0 - V IY0 N - CH EH1 N - Z OW0
+DEVINCI'S  D IH0 - V IH1 N - CH IY0 Z
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+DEVINNEY  D EH1 - V IH0 - N IY0
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+DEVISED  D IH0 - V AY1 Z D
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+DEVITA  D IH0 - V IY1 - T AH0
+DEVITO  D IH0 - V IY1 - T OW0
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+DEVOLVE  D IH0 - V AA1 L V
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+DEVOURED  D IH0 - V AW1 - ER0 D
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+DEVOY  D EH1 - V OY0
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+DEWALL  D UW1 - AH0 L
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+DEWARR  D UW1 - ER0
+DEWART  D UW1 - AA0 R T
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+DEWBERRY  D UW1 - B EH2 - R IY0
+DEWBRE  D UW1 - B ER0
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+DEWEERD  D UW1 - IH0 R D
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+DEWEESE  D UW1 - IY0 Z
+DEWEISS  D IH0 - W AY1 S
+DEWELL  D EH1 - W EH0 L
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+DEWEY'S  D UW1 - IY0 Z
+DEWHIRST  D EH1 - W ER0 S T
+DEWHURST  D EH1 - W ER0 S T
+DEWILDE  D IY1 - W AY0 L D
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+DEWIRE  D UW1 - AY0 R
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+DEWITZ  D EH1 - W IH0 T S
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+DEXTER  D EH1 K - S T ER0
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+DEXTRO  D EH1 K - S T R OW0
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+DEZERN  D EY0 - Z EH1 R N
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+DFW  D IY1 - EH1 F - D AH1 - B AH0 L - Y UW1
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+DHABI  D AA1 - B IY0
+DHAHARAN  D AH0 - R AA1 N
+DHAHRAN  D AH0 - R AA1 N
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+DHAKA(2)  D AE1 - K AH0
+DHAKA(3)  D AE1 - K AE0
+DHALI  D AA1 - L IY0
+DHARMA  D AA1 R - M AH0
+DHEIN  D AY1 N
+DHIA  D IY1 - AH0
+DHILLON  D IH1 - L AH0 N
+DHIRAJ  D IH2 - R AA1 ZH
+DHLAKAMA  D AH0 - L AH0 - K AA1 - M AH0
+DHOLE  D OW1 L
+DHONDT  D HH AA1 N T
+DHOWS  D AW1 Z
+DI  D IY1
+DI'S  D AY1 Z
+DI(2)  D AY1
+DIA  D IY1 - AH0
+DIAB  D AY1 - AH0 B
+DIABASE  D AY1 - AH0 - B EY2 S
+DIABASIC  D AY2 - AH0 - B EY1 - S IH0 K
+DIABETES  D AY2 - AH0 - B IY1 - T IY0 Z
+DIABETIC  D AY2 - AH0 - B EH1 - T IH0 K
+DIABETICS  D AY2 - AH0 - B EH1 - T IH0 K S
+DIABLO  D AY2 - AE1 - B L OW0
+DIABLO(2)  D IY2 - AE1 - B L OW0
+DIABOLICAL  D AY2 - AH0 - B AA1 - L IH0 - K AH0 L
+DIACONATE  D AY0 - AE1 - K AH0 - N AH0 T
+DIACRITIC  D AY2 - AH0 - K R IH1 - T AH0 K
+DIACRITICAL  D AY2 - AH0 - K R IH1 - T AH0 - K AH0 L
+DIADEM  D AY1 - AH0 - D EH2 M
+DIAGNOSE  D AY2 - AH0 G - N OW1 S
+DIAGNOSED  D AY2 - AH0 G - N OW1 S T
+DIAGNOSES  D AY2 - AH0 G - N OW1 - S IY0 Z
+DIAGNOSING  D AY2 - AH0 G - N OW1 - S IH0 NG
+DIAGNOSIS  D AY2 - AH0 G - N OW1 - S AH0 S
+DIAGNOSTEK  D AY2 - AH0 G - N AA1 - S T EH0 K
+DIAGNOSTIC  D AY2 - AH0 G - N AA1 - S T IH0 K
+DIAGNOSTICS  D AY2 - AH0 G - N AA1 - S T IH0 K S
+DIAGONAL  D AY0 - AE1 - G AH0 - N AH0 L
+DIAGONALLY  D AY0 - AE1 - G AH0 - N AH0 - L IY0
+DIAGONALS  D AY0 - AE1 - G AH0 - N AH0 L Z
+DIAGRAM  D AY1 - AH0 - G R AE2 M
+DIAGRAMING  D AY1 - AH0 - G R AE2 - M IH0 NG
+DIAGRAMMATIC  D AY2 - AH0 - G R AH0 - M AE1 - T IH0 K
+DIAGRAMMED  D AY1 - AH0 - G R AE2 M D
+DIAGRAMS  D AY1 - AH0 - G R AE2 M Z
+DIAHANN  D AY2 - AE1 N
+DIAL  D AY1 - AH0 L
+DIAL'S  D AY1 - AH0 L Z
+DIAL'S(2)  D AY1 L Z
+DIAL(2)  D AY1 L
+DIALECT  D AY1 - AH0 - L EH2 K T
+DIALECTIC  D AY2 - AH0 - L EH1 K - T IH0 K
+DIALECTICAL  D AY2 - AH0 - L EH1 K - T IH0 - K AH0 L
+DIALECTS  D AY1 - AH0 - L EH2 K T S
+DIALED  D AY1 - AH0 L D
+DIALING  D AY1 - AH0 - L IH0 NG
+DIALING(2)  D AY1 - L IH0 NG
+DIALOG  D AY1 - AH0 - L AO0 G
+DIALOGUE  D AY1 - AH0 - L AO2 G
+DIALOGUES  D AY1 - AH0 - L AO2 G Z
+DIALS  D AY1 - AH0 L Z
+DIALS(2)  D AY1 L Z
+DIALTONE  D AY1 - AH0 L - T OW2 N
+DIALTONE(2)  D AY1 L - T OW2 N
+DIALYSIS  D AY0 - AE1 - L AH0 - S AH0 S
+DIALYSIS(2)  D AY0 - AE1 - L IH0 - S IH0 S
+DIAMAGNETIC  D AY2 - AH0 - M AE0 G - N EH1 - T IH0 K
+DIAMAGNETISM  D AY2 - AH0 - M AE1 G - N IH0 - T IH2 - Z AH0 M
+DIAMANDIS  D AY2 - AH0 - M AE1 N - D IH0 S
+DIAMANDIS(2)  D IY2 - AH0 - M AE1 N - D IH0 S
+DIAMANT  D AY1 - AH0 - M AH0 N T
+DIAMANTA  D AY2 - AH0 - M AE1 N - T AH0
+DIAMANTE  D AY2 - AH0 - M AA1 N - T IY0
+DIAMETER  D AY0 - AE1 - M AH0 - T ER0
+DIAMETRICALLY  D AY2 - AH0 - M EH1 - T R IH0 - K AH0 - L IY0
+DIAMETRICALLY(2)  D AY2 - AH0 - M EH1 - T R IH0 K - L IY0
+DIAMOND  D AY1 - M AH0 N D
+DIAMOND'S  D AY1 - M AH0 N D Z
+DIAMONDS  D AY1 - M AH0 N D Z
+DIAN  D AY1 - AH0 N
+DIANA  D AY0 - AE1 - N AH0
+DIANA'S  D AY0 - AE1 - N AH0 Z
+DIANE  D AY0 - AE1 N
+DIANE'S  D AY0 - AE1 N Z
+DIANETICS  D AY2 - AH0 - N EH1 - T IH0 K S
+DIANGELO  D AY0 - AH0 NG - G EH1 - L OW0
+DIANNA  D AY2 - AE1 - N AH0
+DIANNE  D AY0 - AE1 N
+DIANTHA  D AY2 - AE1 N - TH AH0
+DIANTHE  D AY0 - AE1 N - DH IY0
+DIANTHIA  D AY2 - AE1 N - TH IY0 - AH0
+DIANTONIO  D AY2 - AH0 N - T OW1 - N IY0 - OW0
+DIAPER  D AY1 - P ER0
+DIAPERING  D AY1 - P ER0 - IH0 NG
+DIAPERS  D AY1 - AH0 - P ER0 Z
+DIAPERS(2)  D AY1 - P ER0 Z
+DIAPHONIA  D AY2 - AH0 - F OW1 - N IY0 - AH0
+DIAPHRAGM  D AY1 - AH0 - F R AE2 M
+DIAPSID  D AY2 - AE1 P - S IH0 D
+DIARIES  D AY1 - ER0 - IY0 Z
+DIARIES(2)  D AY1 - R IY0 Z
+DIARIO  D AY0 - EH1 - R IY0 - OW0
+DIARRHEA  D AY2 - ER0 - IY1 - AH0
+DIARRHOEA  D AY2 - ER0 - IY1 - AH0
+DIARY  D AY1 - ER0 - IY0
+DIARY(2)  D AY1 - R IY0
+DIAS  D AY1 - AH0 Z
+DIASA  D IY0 - AA1 - S AH0
+DIASA'S  D IY0 - AA1 - S AH0 Z
+DIASONIC  D AY2 - AH0 - S AA1 - N IH0 K
+DIASONICS  D AY2 - AH0 - S AA1 - N IH0 K S
+DIASPORA  D AY0 - AE1 - S P ER0 - AH0
+DIASTASE  D AY1 - AH0 - S T EY2 S
+DIASTOLE  D AY0 - AE1 - S T AH0 - L IY2
+DIASTOLIC  D AY2 - AH0 - S T AA1 - L IH0 K
+DIASTROPHISM  D AY0 - AE1 - S T R AH0 - F IH2 - Z AH0 M
+DIATHERMY  D AY1 - AH0 - TH ER2 - M IY0
+DIATOMIC  D AY2 - AH0 - T AA1 - M IH0 K
+DIATOMS  D AY1 - AH0 - T AA2 M Z
+DIATONIC  D AY2 - AH0 - T AA1 - N IH0 K
+DIATRIBE  D AY1 - AH0 - T R AY2 B
+DIATRIBES  D AY1 - AH0 - T R AY2 B Z
+DIAZ  D IY1 - AE2 Z
+DIAZ(2)  D IY1 - AA2 Z
+DIAZ-CALDERON  D IY1 - AE2 Z - K AE2 L - D ER0 - OW1 N
+DIAZO  D AY0 - AE1 - Z OW2
+DIBACCO  D IH0 - B AA1 - K OW0
+DIBARI  D IH0 - B AA1 - R IY0
+DIBARTOLO  D IY2 - B AA0 R - T OW1 - L OW0
+DIBARTOLOMEO  D IH0 - B AA0 R - T OW0 - L OW1 - M IY0 - OW0
+DIBATTISTA  D IH0 - B AA0 - T IY1 - S T AH0
+DIBB  D IH1 B
+DIBBERN  D IH1 - B ER0 N
+DIBBLE  D IH1 - B AH0 L
+DIBBLED  D IH1 - B AH0 L D
+DIBELLA  D IH0 - B EH1 - L AH0
+DIBELLO  D IH0 - B EH1 - L OW0
+DIBENEDETTO  D IH0 - B IH0 - N AH0 - D EH1 - T OW0
+DIBERNARDO  D IH0 - B ER0 - N AA1 R - D OW0
+DIBERT  D IH1 - B ER0 T
+DIBIASE  D IY2 - B IY0 - AA1 - S IY0
+DIBIASIO  D IH0 - B IY0 - AA1 - S IY0 - OW0
+DIBLASI  D IH0 - B L AA1 - S IY0
+DIBLASIO  D IH0 - B L AA1 - S IY0 - OW0
+DIBLE  D AY1 - B AH0 L
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+DIBONA  D IH0 - B OW1 - N AH0
+DIBRELL  D IH1 - B R AH0 L
+DIBS  D IH1 B Z
+DIBUONO  D IH0 - B W OW1 - N OW0
+DIC  D IH1 K
+DICAMBA  D IH0 - K AE1 M - B AH0
+DICAMILLO  D IH0 - K AA0 - M IH1 - L OW0
+DICAPRIO  D IH0 - K AE1 - P R IY0 - OW0
+DICARLO  D IH0 - K AA1 R - L OW0
+DICE  D AY1 S
+DICECCO  D IH0 - S EH1 - K OW0
+DICED  D AY1 S T
+DICELLO  D IH0 - S EH1 - L OW0
+DICENSO  D IH0 - S EH1 N - S OW0
+DICENZO  D IH0 - S EH1 N - Z OW0
+DICEON  D IH1 - S IY0 - AH0 N
+DICESARE  D IH0 - CH EH0 - S AA1 - R IY0
+DICEY  D AY1 - S IY0
+DICHIARA  D IH0 - K IY0 - AA1 - R AH0
+DICHOTOMY  D AY0 - K AA1 - T AH0 - M IY0
+DICHROIC  D AY0 - K R OW1 - IH0 K
+DICHROMATE  D AY0 - K R OW1 - M EY2 T
+DICHROMATE(2)  D AY1 - K R OW0 - M EY2 T
+DICHTER  D IH1 K - T ER0
+DICICCO  D IH0 - S IH1 - K OW0
+DICIER  D AY1 - S IY0 - ER0
+DICIOCCIO  D IH0 - CH OW1 - CH IY0 - OW0
+DICK  D IH1 K
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+DICKARD  D IH1 - K ER0 D
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+DICKE  D IH1 K
+DICKEL  D IH1 - K AH0 L
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+DICKENS  D IH1 - K AH0 N Z
+DICKENS'  D IH1 - K AH0 N Z
+DICKENS'S  D IH1 - K AH0 N - Z IH0 Z
+DICKENSHEETS  D IH1 - K AH0 N - SH IY2 T S
+DICKENSIAN  D IH0 - K EH1 N - Z IY0 - AH0 N
+DICKENSON  D IH1 - K IH0 N - S AH0 N
+DICKER  D IH1 - K ER0
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+DICKERING  D IH1 - K ER0 - IH0 NG
+DICKERMAN  D IH1 - K ER0 - M AH0 N
+DICKERSON  D IH1 - K ER0 - S AH0 N
+DICKERT  D IH1 - K ER0 T
+DICKES  D IH1 K S
+DICKESON  D IH1 - K IH0 - S AH0 N
+DICKEY  D IH1 - K IY0
+DICKEY'S  D IH1 - K IY0 Z
+DICKHAUT  D IH1 K - HH AW2 T
+DICKIE  D IH1 - K IY0
+DICKINSON  D IH1 - K IH0 N - S AH0 N
+DICKISON  D IH1 - K IH0 - S AH0 N
+DICKLER  D IH1 - K L ER0
+DICKMAN  D IH1 K - M AH0 N
+DICKMANN  D IH1 K - M AH0 N
+DICKMEYER  D IH1 K - M AY0 - ER0
+DICKS  D IH1 K S
+DICKSON  D IH1 K - S AH0 N
+DICKSTEIN  D IH1 K - S T AY0 N
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+DICKSTEIN'S(2)  D IH1 K S - T IY2 N Z
+DICKSTEIN(2)  D IH1 K S - T IY0 N
+DICKY  D IH1 - K IY0
+DICLEMENTE  D IH2 - K L AH0 - M EH1 N - T EY0
+DICOCCO  D IH0 - K OW1 - K OW0
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+DICOMED  D IH1 - K AH0 - M EH0 D
+DICOMED(2)  D IY0 - K OW1 M D
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+DICOTS  D AY1 - K AA0 T S
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+DICTAPHONE  D IH1 K - T AH0 - F OW2 N
+DICTATE  D IH0 K - T EY1 T
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+DICTATED  D IH0 K - T EY1 - T AH0 D
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+DICTATES  D IH0 K - T EY1 T S
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+DICTATING  D IH1 K - T EY2 - T IH0 NG
+DICTATION  D IH0 K - T EY1 - SH AH0 N
+DICTATOR  D IH0 K - T EY1 - T ER0
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+DICTATORIAL  D IH2 K - T AH0 - T AO1 - R IY0 - AH0 L
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+DICTATORSHIP  D IH0 K - T EY1 - T ER0 - SH IH2 P
+DICTATORSHIPS  D IH0 K - T EY1 - T ER0 - SH IH2 P S
+DICTION  D IH1 K - SH AH0 N
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+DICTIONARY  D IH1 K - SH AH0 - N EH2 - R IY0
+DICTUM  D IH1 K - T AH0 M
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+DIDO  D AY1 - D OW0
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+DIEFENDORF  D IY1 - F IH0 N - D AO0 R F
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+DIEGANS  D IY1 - G AH0 N Z
+DIEGEL  D IY1 - G AH0 L
+DIEGO  D IY0 - EY1 - G OW0
+DIEGO'S  D IY2 - EY1 - G OW2 Z
+DIEGO-GARCIA  D IY0 - EY1 - G OW0 - G AA2 R - S IY1 - AH0
+DIEGUEZ  D IH0 - G EH1 Z
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+DIET  D AY1 - AH0 T
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+DIETEL  D IY1 - T AH0 L
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+DIETETIC  D AY2 - AH0 - T EH1 - T IH0 K
+DIETING  D AY1 - AH0 - T IH0 NG
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+DIETITIAN'S  D AY2 - AH0 - T IH1 - SH AH0 N Z
+DIETITIANS  D AY2 - AH0 - T IH1 - SH AH0 N Z
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+DIETRICH  D IY1 - T R IH0 K
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+DIEVLER  D IY1 V - L ER0
+DIEZ  D AY1 - AH0 Z
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+DIFABIO(2)  D IH0 - F AE1 - B IY0 - OW0
+DIFALCO  D IH0 - F AE1 L - K OW0
+DIFAZIO  D IH0 - F EY1 - Z IY0 - OW0
+DIFELICE  D IH0 - F EH1 - L IH0 S
+DIFELICE(2)  D IH0 - F EH1 - L IY0 S
+DIFELICE(3)  D IH0 - F IH0 - L IY1 - CH EY0
+DIFF  D IH1 F
+DIFFEE  D IH1 - F IY0
+DIFFENDERFER  D IH1 - F IH0 N - D ER0 - F ER0
+DIFFER  D IH1 - F ER0
+DIFFERED  D IH1 - F ER0 D
+DIFFERENCE  D IH1 - F ER0 - AH0 N S
+DIFFERENCE(2)  D IH1 - F R AH0 N S
+DIFFERENCES  D IH1 - F ER0 - AH0 N - S IH0 Z
+DIFFERENCES(2)  D IH1 - F R AH0 N - S AH0 Z
+DIFFERENT  D IH1 - F ER0 - AH0 N T
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+DIFFERENTIAL  D IH2 - F ER0 - EH1 N - CH AH0 L
+DIFFERENTIAL(2)  D IH2 - F ER0 - EH1 N - SH AH0 L
+DIFFERENTIALS  D IH2 - F ER0 - EH1 N - CH AH0 L Z
+DIFFERENTIALS(2)  D IH2 - F ER0 - EH1 N - CH AH0 L Z
+DIFFERENTIATE  D IH2 - F ER0 - EH1 N - SH IY0 - EY2 T
+DIFFERENTIATE(2)  D IH2 - F ER0 - EH1 N - CH IY0 - EY2 T
+DIFFERENTIATED  D IH2 - F ER0 - EH1 N - CH IY0 - EY2 - T IH0 D
+DIFFERENTIATED(2)  D IH2 - F ER0 - EH1 N - SH IY0 - EY2 - T AH0 D
+DIFFERENTIATES  D IH0 - F ER0 - EH1 N - SH IY0 - EY2 T S
+DIFFERENTIATES(2)  D IH2 - F ER0 - EH1 N - CH IY0 - EY2 T S
+DIFFERENTIATING  D IH2 - F ER0 - EH1 N - CH IY0 - EY2 - T IH0 NG
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+DIFFERENTIATION  D IH0 - F ER0 - EH2 N - SH IY0 - EY1 - SH AH0 N
+DIFFERENTIATION(2)  D IH2 - F ER0 - EH2 N - CH IY0 - EY1 - SH AH0 N
+DIFFERENTLY  D IH1 - F R AH0 N T - L IY0
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+DIFFERING  D IH1 - F ER0 - IH0 NG
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+DIFFERS  D IH1 - F ER0 Z
+DIFFICULT  D IH1 - F AH0 - K AH0 L T
+DIFFICULTIES  D IH1 - F AH0 - K AH0 L - T IY0 Z
+DIFFICULTIES(2)  D IH1 - F IH0 - K AH2 L - T IY0 Z
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+DIGITAL  D IH1 - JH AH0 - T AH0 L
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+DILAPIDATE  D AH0 - L AE1 - P AH0 - D EY2 T
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+DIPLOMATS'  D IH1 - P L AH0 - M AE2 T S
+DIPOLE  D AY1 - P OW2 L
+DIPPED  D IH1 P T
+DIPPEL  D IH1 - P AH0 L
+DIPPER  D IH1 - P ER0
+DIPPERS  D IH1 - P ER0 Z
+DIPPING  D IH1 - P IH0 NG
+DIPPLE  D IH1 - P AH0 L
+DIPPOLD  D IH1 - P OW2 L D
+DIPPOLITO  D IH0 - P OW0 - L IY1 - T OW0
+DIPPY  D IH1 - P IY0
+DIPRIMA  D IH0 - P R IY1 - M AH0
+DIPS  D IH1 P S
+DIPSTICK  D IH1 P - S T IH2 K
+DIRCKS  D ER1 K S
+DIRE  D AY1 R
+DIRE(2)  D AY1 - ER0
+DIRECT  D ER0 - EH1 K T
+DIRECT(2)  D AY0 - R EH1 K T
+DIRECT(3)  D IY0 - R EH1 K T
+DIRECT(4)  D IH0 - R EH1 K T
+DIRECTED  D ER0 - EH1 K - T AH0 D
+DIRECTED(2)  D ER0 - EH1 K - T IH0 D
+DIRECTED(3)  D AY0 - R EH1 K - T IH0 D
+DIRECTED(4)  D IY0 - R EH1 K - T IH0 D
+DIRECTED(5)  D IH0 - R EH1 K - T IH0 D
+DIRECTING  D ER0 - EH1 K - T IH0 NG
+DIRECTING(2)  D IY0 - R EH1 K - T IH0 NG
+DIRECTING(3)  D AY0 - R EH1 K - T IH0 NG
+DIRECTING(4)  D IH0 - R EH1 K - T IH0 NG
+DIRECTION  D ER0 - EH1 K - SH AH0 N
+DIRECTION(2)  D IY0 - R EH1 K - SH IH0 N
+DIRECTION(3)  D AY0 - R EH1 K - SH IH0 N
+DIRECTION(4)  D IH0 - R EH1 K - SH IH0 N
+DIRECTIONAL  D ER0 - EH1 K - SH AH0 - N AH0 L
+DIRECTIONAL(2)  D IY0 - R EH1 K - SH IH0 - N AH0 L
+DIRECTIONAL(3)  D AY0 - R EH1 K - SH IH0 - N AH0 L
+DIRECTIONAL(4)  D IH0 - R EH1 K - SH IH0 - N AH0 L
+DIRECTIONLESS  D ER0 - EH1 K - SH AH0 N - L AH0 S
+DIRECTIONLESS(2)  D IY0 - R EH1 K - SH IH0 N - L AH0 S
+DIRECTIONLESS(3)  D AY0 - R EH1 K - SH IH0 N - L AH0 S
+DIRECTIONLESS(4)  D IH0 - R EH1 K - SH IH0 N - L AH0 S
+DIRECTIONS  D ER0 - EH1 K - SH AH0 N Z
+DIRECTIONS(2)  D IY0 - R EH1 K - SH IH0 N Z
+DIRECTIONS(3)  D AY0 - R EH1 K - SH IH0 N Z
+DIRECTIONS(4)  D IH0 - R EH1 K - SH IH0 N Z
+DIRECTIVE  D ER0 - EH1 K - T IH0 V
+DIRECTIVE(2)  D IY0 - R EH1 K - T IH0 V
+DIRECTIVE(3)  D AY0 - R EH1 K - T IH0 V
+DIRECTIVE(4)  D IH0 - R EH1 K - T IH0 V
+DIRECTIVES  D AY0 - R EH1 K - T IH0 V Z
+DIRECTIVES(2)  D IY0 - R EH1 K - T IH0 V Z
+DIRECTIVES(3)  D ER0 - EH1 K - T IH0 V Z
+DIRECTIVES(4)  D IH0 - R EH1 K - T IH0 V Z
+DIRECTLY  D ER0 - EH1 K T - L IY0
+DIRECTLY(2)  D IY0 - R EH1 K - L IY0
+DIRECTLY(3)  D AY0 - R EH1 K - L IY0
+DIRECTLY(4)  D IH0 - R EH1 K - L IY0
+DIRECTNESS  D ER0 - EH1 K T - N AH0 S
+DIRECTNESS(2)  D IY0 - R EH1 K - N AH0 S
+DIRECTNESS(3)  D AY0 - R EH1 K - N AH0 S
+DIRECTNESS(4)  D IH0 - R EH1 K - N AH0 S
+DIRECTOR  D ER0 - EH1 K - T ER0
+DIRECTOR'S  D AY0 - R EH1 K - T ER0 Z
+DIRECTOR'S(2)  D ER0 - EH1 K - T ER0 Z
+DIRECTOR'S(3)  D IY0 - R EH1 K - T ER0 Z
+DIRECTOR'S(4)  D IH0 - R EH1 K - T ER0 Z
+DIRECTOR(2)  D AY0 - R EH1 K - T ER0
+DIRECTOR(3)  D IY0 - R EH1 K - T ER0
+DIRECTOR(4)  D IH0 - R EH1 K - T ER0
+DIRECTORAL  D ER0 - EH1 K - T ER0 - AH0 L
+DIRECTORATE  D ER0 - EH1 K - T ER0 - AH0 T
+DIRECTORATE(2)  D AY0 - R EH1 K - T ER0 - AH0 T
+DIRECTORATE(3)  D IY0 - R EH1 K - T ER0 - AH0 T
+DIRECTORATE(4)  D IH0 - R EH1 K - T ER0 - AH0 T
+DIRECTORIAL  D ER0 - EH0 K - T AO1 - R IY0 - AH0 L
+DIRECTORIAL(2)  D AY0 - R EH0 K - T AO1 - R IY0 - AH0 L
+DIRECTORIAL(3)  D IY0 - R EH0 K - T AO1 - R IY0 - AH0 L
+DIRECTORIAL(4)  D IH0 - R EH0 K - T AO1 - R IY0 - AH0 L
+DIRECTORIES  D AY0 - R EH1 K - T ER0 - IY0 Z
+DIRECTORIES(2)  D ER0 - EH1 K - T ER0 - IY0 Z
+DIRECTORIES(3)  D IY0 - R EH1 K - T ER0 - IY0 Z
+DIRECTORIES(4)  D IH0 - R EH1 K - T ER0 - IY0 Z
+DIRECTORS  D ER0 - EH1 K - T ER0 Z
+DIRECTORS'  D IH0 - R EH1 K - T ER0 Z
+DIRECTORS'(2)  D ER0 - EH1 K - T ER0 Z
+DIRECTORS'(3)  D IY0 - R EH1 K - T ER0 Z
+DIRECTORS(2)  D AY0 - R EH1 K - T ER0 Z
+DIRECTORS(3)  D IY0 - R EH1 K - T ER0 Z
+DIRECTORS(4)  D IH0 - R EH1 K - T ER0 Z
+DIRECTORSHIP  D ER0 - EH1 K - T ER0 - SH IH2 P
+DIRECTORSHIP(2)  D AY0 - R EH1 K - T ER0 - SH IH2 P
+DIRECTORSHIP(3)  D IY0 - R EH1 K - T ER0 - SH IH2 P
+DIRECTORSHIP(4)  D IH0 - R EH1 K - T ER0 - SH IH2 P
+DIRECTORSHIPS  D ER0 - EH1 K - T ER0 - SH IH2 P S
+DIRECTORSHIPS(2)  D AY0 - R EH1 K - T ER0 - SH IH2 P S
+DIRECTORSHIPS(3)  D IY0 - R EH1 K - T ER0 - SH IH2 P S
+DIRECTORSHIPS(4)  D IH0 - R EH1 K - T ER0 - SH IH2 P S
+DIRECTORY  D ER0 - EH1 K - T ER0 - IY0
+DIRECTORY(2)  D AY0 - R EH1 K - T ER0 - IY0
+DIRECTORY(3)  D IY0 - R EH1 K - T ER0 - IY0
+DIRECTORY(4)  D IH0 - R EH1 K - T ER0 - IY0
+DIRECTS  D ER0 - EH1 K T S
+DIRECTS(2)  D AY0 - R EH1 K T S
+DIRECTS(3)  D IY0 - R EH1 K T S
+DIRECTS(4)  D IH0 - R EH1 K T S
+DIRECTV  D ER0 - EH1 K - T IY1 - V IY1
+DIRECTV(2)  D AY0 - R EH1 K - T IY1 - V IY1
+DIRECTV(3)  D IY0 - R EH1 K - T IY1 - V IY1
+DIRECTV(4)  D IH0 - R EH1 K - T IY1 - V IY1
+DIRENZO  D IH0 - R EH1 N - Z OW0
+DIREST  D AY1 - R AH0 S T
+DIRGE  D ER1 JH
+DIRHAMS  D ER1 - AH0 M Z
+DIRICKSON  D AO1 - R IH0 K - S AH0 N
+DIRIENZO  D IH0 - R IY1 N - Z OW0
+DIRK  D ER1 K
+DIRKES  D ER1 K S
+DIRKS  D ER1 K S
+DIRKSE  D ER1 K S
+DIRKSEN  D ER1 K - S AH0 N
+DIRLAM  D ER0 - L AE1 M
+DIROCCO  D IH0 - R AA1 - K OW0
+DIROSA  D IH0 - R OW1 - S AH0
+DIRR  D ER1
+DIRT  D ER1 T
+DIRT'S  D ER1 T S
+DIRTIER  D ER1 - T IY0 - ER0
+DIRTIEST  D ER1 - T IY0 - AH0 S T
+DIRTY  D ER1 - T IY0
+DIRUSSO  D IH0 - R UW1 - S OW0
+DIS  D IH1 S
+DISA  D IH1 - S AH0
+DISABATINO  D IH0 S - AA0 - B AA0 - T IY1 - N OW0
+DISABATO  D IH0 S - AA0 - B AA1 - T OW0
+DISABILITIES  D IH0 S - AH0 - B IH1 - L AH0 - T IY0 Z
+DISABILITIES(2)  D IH0 S - AH0 - B IH1 - L IH0 - T IY0 Z
+DISABILITY  D IH2 S - AH0 - B IH1 - L IH0 - T IY0
+DISABILITY(2)  D IH0 S - AH0 - B IH1 - L IH0 - T IY0 Z
+DISABLE  D IH0 S - EY1 - B AH0 L
+DISABLED  D IH0 S - EY1 - B AH0 L D
+DISABLES  D IH0 S - EY1 - B AH0 L Z
+DISABLING  D IH0 S - EY1 - B AH0 L - IH0 NG
+DISABLING(2)  D IH2 S - EY1 - B L IH0 NG
+DISABUSE  D IH0 S - AH0 - B Y UW1 S
+DISABUSE(2)  D IH0 S - AH0 - B Y UW1 Z
+DISABUSED  D IH0 S - AH0 - B Y UW1 Z D
+DISABUSES  D IH0 S - AH0 - B Y UW1 - S IH0 Z
+DISADVANTAGE  D IH2 S - AH0 D - V AE1 N - T IH0 JH
+DISADVANTAGE(2)  D IH2 S - AH0 D - V AE1 - N IH0 JH
+DISADVANTAGED  D IH0 S - AH0 D - V AE1 N - T IH0 JH D
+DISADVANTAGED(2)  D IH2 S - AH0 D - V AE1 - N IH0 JH D
+DISADVANTAGEOUS  D IH2 S - AE2 D - V AE2 N - T EY1 - JH AH0 S
+DISADVANTAGES  D IH2 S - AH0 D - V AE1 N - T IH0 - JH IH0 Z
+DISADVANTAGES(2)  D IH2 S - AH0 D - V AE1 - N IH0 JH Z
+DISAFFECT  D IH2 S - AH0 - F EH1 K T
+DISAFFECTED  D IH2 S - AH0 - F EH1 K - T IH0 D
+DISAFFECTION  D IH2 S - AH0 - F EH1 K - SH AH0 N
+DISAGREE  D IH0 S - AH0 - G R IY1
+DISAGREEABLE  D IH2 S - AH0 - G R IY1 - AH0 - B AH0 L
+DISAGREED  D IH0 S - AH0 - G R IY1 D
+DISAGREEING  D IH0 S - AH0 - G R IY1 - IH0 NG
+DISAGREEMENT  D IH0 S - AH0 - G R IY1 - M AH0 N T
+DISAGREEMENTS  D IH2 S - AH0 - G R IY1 - M AH0 N T S
+DISAGREES  D IH0 S - AH0 - G R IY1 Z
+DISALLOW  D IH2 S - AH0 - L AW1
+DISALLOWANCE  D IH2 S - AH0 - L AW1 - AH0 N S
+DISALLOWANCES  D IH2 S - AH0 - L AW1 - AH0 N - S IH0 Z
+DISALLOWED  D IH2 S - AH0 - L AW1 D
+DISALLOWING  D IH0 S - AH0 - L AW1 - IH0 NG
+DISALVO  D IH0 - S AA1 L - V OW0
+DISANO  D IH0 S - AA1 - N OW0
+DISANTI  D IH0 - S AE1 N - T IY0
+DISANTIS  D IH0 - S AA1 N - T IH0 S
+DISANTO  D IH0 - S AE1 N - T OW0
+DISAPPEAR  D IH2 S - AH0 - P IH1 R
+DISAPPEAR(2)  D IH2 - S AH0 - P IY1 R
+DISAPPEARANCE  D IH2 S - AH0 - P IH1 - R AH0 N S
+DISAPPEARANCE(2)  D IH2 S - AH0 - P IY1 - R AH0 N S
+DISAPPEARANCES  D IH2 S - AH0 - P IH1 - R AH0 N - S IH0 Z
+DISAPPEARANCES(2)  D IH2 S - AH0 - P IY1 - R AH0 N - S IH0 Z
+DISAPPEARED  D IH2 S - AH0 - P IH1 R D
+DISAPPEARED(2)  D IH2 S - AH0 - P IY1 R D
+DISAPPEARING  D IH2 S - AH0 - P IH1 - R IH0 NG
+DISAPPEARING(2)  D IH2 S - AH0 - P IY1 - R IH0 NG
+DISAPPEARS  D IH2 S - AH0 - P IH1 R Z
+DISAPPEARS(2)  D IH2 S - AH0 - P IY1 R Z
+DISAPPOINT  D IH2 S - AH0 - P OY1 N T
+DISAPPOINTED  D IH2 S - AH0 - P OY1 N - T IH0 D
+DISAPPOINTED(2)  D IH2 S - AH0 - P OY1 - N IH0 D
+DISAPPOINTING  D IH2 S - AH0 - P OY1 N - T IH0 NG
+DISAPPOINTING(2)  D IH2 S - AH0 - P OY1 - N IH0 NG
+DISAPPOINTINGLY  D IH0 S - AH0 - P OY1 N - T IH0 NG - L IY0
+DISAPPOINTINGLY(2)  D IH0 S - AH0 - P OY1 - N IH0 NG - L IY0
+DISAPPOINTMENT  D IH2 S - AH0 - P OY1 N T - M AH0 N T
+DISAPPOINTMENTS  D IH0 S - AH0 - P OY1 N T - M AH0 N T S
+DISAPPOINTS  D IH2 S - AH0 - P OY1 N T S
+DISAPPROVAL  D IH0 S - AH0 - P R UW1 - V AH0 L
+DISAPPROVE  D IH2 S - AH0 - P R UW1 V
+DISAPPROVED  D IH2 S - AH0 - P R UW1 V D
+DISAPPROVES  D IH0 S - AH0 - P R UW1 V Z
+DISAPPROVING  D IH0 S - AH0 - P R UW1 - V IH0 NG
+DISARM  D IH0 S - AA1 R M
+DISARMAMENT  D IH0 S - AA1 R - M AH0 - M AH0 N T
+DISARMED  D IH0 S - AA1 R M D
+DISARMING  D IH0 S - AA1 R - M IH0 NG
+DISARMINGLY  D IH0 S - AA1 R - M IH0 NG - L IY0
+DISARRAY  D IH2 S - ER0 - EY1
+DISARRAY(2)  D IH2 S - AH0 - R EY1
+DISASSEMBLE  D IH2 S - AH0 - S EH1 M - B AH0 L
+DISASSEMBLED  D IH2 S - AH0 - S EH1 M - B AH0 L D
+DISASSOCIATE  D IH2 S - AH0 - S OW1 - SH IY0 - EY0 T
+DISASSOCIATE(2)  D IH2 S - AH0 - S OW1 - S IY0 - EY0 T
+DISASSOCIATED  D IH2 S - AH0 - S OW1 - SH IY0 - EY0 - T AH0 D
+DISASSOCIATED(2)  D IH2 S - AH0 - S OW1 - S IY0 - EY0 - T AH0 D
+DISASTER  D IH0 - Z AE1 - S T ER0
+DISASTERS  D IH0 - Z AE1 - S T ER0 Z
+DISASTROUS  D IH0 - Z AE1 - S T R AH0 S
+DISASTROUSLY  D IH0 - Z AE1 - S T R AH0 S - L IY0
+DISAVOW  D IH2 S - AH0 - V AW1
+DISAVOWED  D IH2 S - AH0 - V AW1 D
+DISAVOWING  D IH0 S - AH0 - V AW1 - IH0 NG
+DISBAND  D IH0 S - B AE1 N D
+DISBANDED  D IH0 S - B AE1 N - D IH0 D
+DISBANDING  D IH0 S - B AE1 N - D IH0 NG
+DISBAR  D IH2 S - B AA1 R
+DISBARMENT  D IH2 S - B AA1 R - M AH0 N T
+DISBARRED  D IH0 S - B AA1 R D
+DISBELIEF  D IH2 S - B IH0 - L IY1 F
+DISBELIEVE  D IH0 S - B AH0 - L IY1 V
+DISBELIEVING  D IH0 S - B AH0 - L IY1 - V IH0 NG
+DISBRO  D IH1 S - B R OW0
+DISBROW  D IH1 S - B R AW0
+DISBURSE  D IH0 S - B ER1 S
+DISBURSED  D IH0 S - B ER1 S T
+DISBURSEMENT  D IH0 S - B ER1 S - M AH0 N T
+DISBURSEMENTS  D IH0 S - B ER1 S - M AH0 N T S
+DISBURSING  D IH0 S - B ER1 - S IH0 NG
+DISC  D IH1 S K
+DISCARD  D IH0 S - K AA1 R D
+DISCARDED  D IH0 S - K AA1 R - D IH0 D
+DISCARDING  D IH0 S - K AA1 R - D IH0 NG
+DISCARDS  D IH0 S - K AA1 R D Z
+DISCENZA  D IH0 S - CH EH1 N - Z AH0
+DISCERN  D IH0 - S ER1 N
+DISCERNED  D IH0 - S ER1 N D
+DISCERNIBLE  D IH0 - S ER1 - N AH0 - B AH0 L
+DISCERNING  D IH0 - S ER1 - N IH0 NG
+DISCERNMENT  D IH0 - S ER1 N - M AH0 N T
+DISCH  D IH1 SH
+DISCHARGE  D IH0 S - CH AA1 R JH
+DISCHARGE(2)  D IH1 S - CH AA2 R JH
+DISCHARGED  D IH0 S - CH AA1 R JH D
+DISCHARGED(2)  D IH1 S - CH AA2 R JH D
+DISCHARGES  D IH0 S - CH AA1 R - JH AH0 Z
+DISCHARGES(2)  D IH1 S - CH AA2 R - JH AH0 Z
+DISCHARGING  D IH0 S - CH AA1 R - JH IH0 NG
+DISCHARGING(2)  D IH1 S - CH AA2 R - JH IH0 NG
+DISCHER  D IH1 - SH ER0
+DISCHINGER  D IH1 - SH IH0 N - JH ER0
+DISCIPLE  D IH0 - S AY1 - P AH0 L
+DISCIPLES  D IH0 - S AY1 - P AH0 L Z
+DISCIPLINARIAN  D IH2 - S IH0 - P L IH0 - N EH1 - R IY0 - AH0 N
+DISCIPLINARIANS  D IH2 - S IH0 - P L IH0 - N EH1 - R IY0 - AH0 N Z
+DISCIPLINARY  D IH1 - S AH0 - P L AH0 - N EH2 - R IY0
+DISCIPLINE  D IH1 - S AH0 - P L AH0 N
+DISCIPLINED  D IH1 - S AH0 - P L AH0 N D
+DISCIPLINES  D IH1 - S AH0 - P L AH0 N Z
+DISCIPLINING  D IH1 - S AH0 - P L AH0 - N IH0 NG
+DISCLAIM  D IH0 S - K L EY1 M
+DISCLAIMED  D IH0 S - K L EY1 M D
+DISCLAIMER  D IH0 S - K L EY1 - M ER0
+DISCLAIMERS  D IH0 S - K L EY1 - M ER0 Z
+DISCLAIMING  D IH0 S - K L EY1 - M IH0 NG
+DISCLAIMS  D IH0 S - K L EY1 M Z
+DISCLAND  D IH1 S K - L AE2 N D
+DISCLOSE  D IH0 S - K L OW1 Z
+DISCLOSED  D IH0 S - K L OW1 Z D
+DISCLOSES  D IH0 S - K L OW1 - Z IH0 Z
+DISCLOSING  D IH0 S - K L OW1 - Z IH0 NG
+DISCLOSURE  D IH0 S - K L OW1 - ZH ER0
+DISCLOSURES  D IH0 S - K L OW1 - ZH ER0 Z
+DISCO  D IH1 - S K OW0
+DISCOGRAPHY  D IH0 - S K AO1 - G R AH0 - F IY0
+DISCOLOR  D IH0 - S K AH1 - L ER0
+DISCOLORATION  D IH0 - S K AH2 - L ER0 - EY1 - SH AH0 N
+DISCOLORATIONS  D IH0 - S K AH2 - L ER0 - EY1 - SH AH0 N Z
+DISCOLORED  D IH0 S - K AH1 - L ER0 D
+DISCOLORS  D IH0 - S K AH1 - L ER0 Z
+DISCOMFORT  D IH0 S - K AH1 M - F ER0 T
+DISCONCERT  D IH2 S - K AH0 N - S ER1 T
+DISCONCERTING  D IH2 S - K AH0 N - S ER1 - T IH0 NG
+DISCONNECT  D IH0 S - K AH0 - N EH1 K T
+DISCONNECTED  D IH2 S - K AH0 - N EH1 K - T IH0 D
+DISCONNECTING  D IH2 S - K AH0 - N EH1 K - T IH0 NG
+DISCONNECTION  D IH2 S - K AH0 - N EH1 K - SH AH0 N
+DISCONTENT  D IH0 S - K AH0 N - T EH1 N T
+DISCONTENTED  D IH2 S - K AH0 N - T EH1 N - T IH0 D
+DISCONTENTS  D IH2 S - K AH0 N - T EH1 N T S
+DISCONTINUANCE  D IH2 S - K AH0 N - T IH1 - N Y UW0 - AH0 N S
+DISCONTINUATION  D IH2 S - K AH0 N - T IH2 - N Y UW0 - EY1 - SH AH0 N
+DISCONTINUE  D IH0 S - K AH0 N - T IH1 - N Y UW0
+DISCONTINUED  D IH0 S - K AH0 N - T IH1 - N Y UW0 D
+DISCONTINUING  D IH0 S - K AH0 N - T IH1 - N Y UW0 - IH0 NG
+DISCONTINUITY  D IH0 S - K AA2 N - T IH0 - N UW1 - IH0 - T IY0
+DISCORD  D IH1 - S K AO0 R D
+DISCORDANT  D IH0 - S K AO1 R - D AH0 N T
+DISCOS  D IH1 - S K OW0 Z
+DISCOTHEQUE  D IH1 - S K OW0 - T EH2 K
+DISCOUNT  D IH0 S - K AW1 N T
+DISCOUNT(2)  D IH1 S - K AW0 N T
+DISCOUNTABLE  D IH1 S - K AW2 N - T AH0 - B AH0 L
+DISCOUNTED  D IH1 S - K AW2 N - T IH0 D
+DISCOUNTED(2)  D IH1 S - K AW2 - N IH0 D
+DISCOUNTER  D IH1 S - K AW2 N - T ER0
+DISCOUNTERS  D IH0 S - K AW1 N - T ER0 Z
+DISCOUNTERS(2)  D IH1 S - K AW2 - N ER0 R Z
+DISCOUNTING  D IH1 S - K AW2 N - T IH0 NG
+DISCOUNTING(2)  D IH1 S - K AW2 - N IH0 NG
+DISCOUNTS  D IH0 S - K AW1 N T S
+DISCOUNTS(2)  D IH1 S - K AW2 N T S
+DISCOURAGE  D IH0 - S K ER1 - IH0 JH
+DISCOURAGED  D IH0 - S K ER1 - AH0 JH D
+DISCOURAGED(2)  D IH0 - S K ER1 - IH0 JH D
+DISCOURAGEMENT  D IH0 - S K ER1 - IH0 JH - M AH0 N T
+DISCOURAGES  D IH0 - S K ER1 - IH0 - JH IH0 Z
+DISCOURAGING  D IH0 - S K ER1 - AH0 - JH IH0 NG
+DISCOURAGING(2)  D IH0 - S K ER1 - IH0 - JH IH0 NG
+DISCOURSE  D IH1 S - K AO0 R S
+DISCOURSES  D IH0 S - K AO1 R - S IH0 Z
+DISCOURSES(2)  D IH1 S - K AO0 R - S IH0 Z
+DISCOVER  D IH0 - S K AH1 - V ER0
+DISCOVERABLE  D IH0 - S K AH1 - V ER0 - AH0 - B AH0 L
+DISCOVERABLE(2)  D IH0 - S K AH1 - V R AH0 - B AH0 L
+DISCOVERED  D IH0 - S K AH1 - V ER0 D
+DISCOVERIES  D IH0 - S K AH1 - V ER0 - IY0 Z
+DISCOVERING  D IH0 - S K AH1 - V ER0 - IH0 NG
+DISCOVERS  D IH0 - S K AH1 - V ER0 Z
+DISCOVERY  D IH0 - S K AH1 - V ER0 - IY0
+DISCOVERY'S  D IH0 - S K AH1 - V ER0 - IY0 Z
+DISCOVERY'S(2)  D IH0 - S K AH1 - V R IY0 Z
+DISCOVERY(2)  D IH0 - S K AH1 - V R IY0
+DISCOVERY(2)  D IH2 - S K AH1 - V R IY0
+DISCREDIT  D IH0 S - K R EH1 - D AH0 T
+DISCREDITED  D IH0 S - K R EH1 - D IH0 - T IH0 D
+DISCREDITING  D IH0 S - K R EH1 - D AH0 - T IH0 NG
+DISCREDITS  D IH0 S - K R EH1 - D AH0 T S
+DISCREET  D IH0 - S K R IY1 T
+DISCREETLY  D IH0 - S K R IY1 T - L IY0
+DISCREPANCIES  D IH0 - S K R EH1 - P AH0 N - S IY0 Z
+DISCREPANCY  D IH0 - S K R EH1 - P AH0 N - S IY0
+DISCRETE  D IH0 - S K R IY1 T
+DISCRETION  D IH0 - S K R EH1 - SH AH0 N
+DISCRETIONARY  D IH0 - S K R EH1 - SH AH0 N - EH2 - R IY0
+DISCRIMINATE  D IH0 - S K R IH1 - M AH0 - N EY2 T
+DISCRIMINATED  D IH0 - S K R IH1 - M AH0 - N EY2 - T AH0 D
+DISCRIMINATED(2)  D IH0 - S K R IH1 - M AH0 - N EY2 - T IH0 D
+DISCRIMINATES  D IH0 - S K R IH1 - M AH0 - N EY2 T S
+DISCRIMINATING  D IH0 - S K R IH1 - M AH0 - N EY2 - T IH0 NG
+DISCRIMINATION  D IH0 - S K R IH2 - M AH0 - N EY1 - SH AH0 N
+DISCRIMINATORY  D IH0 - S K R IH1 - M AH0 - N AH0 - T AO2 - R IY0
+DISCS  D IH1 S K S
+DISCURSIVE  D IH0 - S K ER1 - S IH0 V
+DISCUS  D IH1 - S K AH0 S
+DISCUSS  D IH0 - S K AH1 S
+DISCUSSED  D IH0 - S K AH1 S T
+DISCUSSES  D IH0 - S K AH1 - S AH0 Z
+DISCUSSES(2)  D IH0 - S K AH1 - S IH0 Z
+DISCUSSING  D IH0 - S K AH1 - S IH0 NG
+DISCUSSION  D IH0 - S K AH1 - SH AH0 N
+DISCUSSIONS  D IH0 - S K AH1 - SH AH0 N Z
+DISDAIN  D IH0 S - D EY1 N
+DISDAINED  D IH0 S - D EY1 N D
+DISDAINFUL  D IH0 S - D EY1 N - F AH0 L
+DISDAINING  D IH0 S - D EY1 - N IH0 NG
+DISDAINS  D IH0 S - D EY1 N Z
+DISE  D AY1 S
+DISE(2)  D AY1 Z
+DISEASE  D IH0 - Z IY1 Z
+DISEASE'S  D IH0 - Z IY1 - Z IH0 Z
+DISEASED  D IH0 - Z IY1 Z D
+DISEASES  D IH0 - Z IY1 - Z AH0 Z
+DISEASES(2)  D IH0 - Z IY1 - Z IH0 Z
+DISEMBARK  D IH0 S - EH0 M - B AA1 R K
+DISEMBARKATION  D IH0 S - EH2 M - B AA0 R - K EY1 - SH AH0 N
+DISEMBODIED  D IH0 S - IH0 - B AA1 - D IY0 D
+DISEMBODY  D IH0 S - IH0 - B AA1 - D IY0
+DISENCHANTED  D IH0 S - IH0 N - CH AE1 N - T IH0 D
+DISENCHANTED(2)  D IH0 S - IH0 N - CH AE1 - N IH0 D
+DISENCHANTMENT  D IH0 S - IH0 N - CH AE1 N T - M AH0 N T
+DISENFRANCHISE  D IH0 S - IH0 N - F R AE1 N - CH AY2 Z
+DISENFRANCHISED  D IH0 S - IH0 N - F R AE1 N - CH AY2 Z D
+DISENFRANCHISEMENT  D IH0 S - IH0 N - F R AE1 N - CH AY2 Z - M AH0 N T
+DISENGAGE  D IH0 S - IH0 N - G EY1 JH
+DISENGAGED  D IH0 S - IH0 N - G EY1 JH D
+DISENGAGEMENT  D IH0 S - IH0 N - G EY1 JH - M AH0 N T
+DISENGAGING  D IH0 S - IH0 N - G EY1 - JH IH0 NG
+DISENTANGLE  D IH2 S - AH0 N - T AE1 NG - G AH0 L
+DISEQUILIBRIUM  D IH0 - S IY2 - K W AH0 - L IH1 - B R IY0 - AH0 M
+DISESTABLISHMENT  D IH0 - S IH0 - S T AE1 - B L IH0 SH - M AH0 N T
+DISFAVOR  D IH0 S - F EY1 - V ER0
+DISFAVORING  D IH0 S - F EY1 - V ER0 - IH0 NG
+DISFIGURE  D IH0 S - F IH1 - G Y ER0
+DISFIGURED  D IH0 S - F IH1 - G Y ER0 D
+DISFIGUREMENT  D IH0 S - F IH1 - G Y ER0 - M EH0 N T
+DISFIGURING  D IH0 S - F IH1 - G Y ER0 - IH0 NG
+DISGORGE  D IH0 S - G AO1 R JH
+DISGORGED  D IH0 S - G AO1 R JH D
+DISGORGEMENT  D IH0 S - G AO1 R JH - M AH0 N T
+DISGRACE  D IH0 S - G R EY1 S
+DISGRACED  D IH0 S - G R EY1 S T
+DISGRACEFUL  D IH0 S - G R EY1 S - F AH0 L
+DISGRUNTLED  D IH0 S - G R AH1 N - T AH0 L D
+DISGRUNTLED(2)  D IH0 S - G R AH1 - N AH0 L D
+DISGRUNTLEMENT  D IH0 S - G R AH1 N - T AH0 L - M AH0 N T
+DISGRUNTLING  D IH0 S - G R AH1 N - T AH0 L - IH0 NG
+DISGRUNTLING(2)  D IH0 S - G R AH1 N T - L IH0 NG
+DISGUISE  D IH0 S - G AY1 Z
+DISGUISED  D IH0 S - G AY1 Z D
+DISGUISES  D IH0 S - G AY1 - Z IH0 Z
+DISGUISING  D IH0 S - G AY1 - Z IH0 NG
+DISGUST  D IH0 S - G AH1 S T
+DISGUSTED  D IH0 S - G AH1 - S T AH0 D
+DISGUSTED(2)  D IH0 S - G AH1 - S T IH0 D
+DISGUSTING  D IH0 S - G AH1 - S T IH0 NG
+DISGUSTS  D IH0 S - G AH1 S T S
+DISGUSTS(2)  D IH0 S - G AH1 S S
+DISGUSTS(3)  D IH0 S - G AH1 S
+DISH  D IH1 SH
+DISHARMONY  D IH0 S - HH AA1 R - M AH0 - N IY0
+DISHAROON  D IH0 - SH ER0 - UW1 N
+DISHAW  D IH1 - SH AO2
+DISHEARTENED  D IH0 S - HH AA1 R - T AH0 N D
+DISHEARTENING  D IH0 S - HH AA1 R - T AH0 N - IH0 NG
+DISHEARTENING(2)  D IH2 S - HH AA1 R T - N IH0 NG
+DISHED  D IH1 SH T
+DISHER  D IH1 - SH ER0
+DISHES  D IH1 - SH AH0 Z
+DISHES(2)  D IH1 - SH IH0 Z
+DISHEVEL  D IH0 - SH EH1 - V AH0 L
+DISHEVELED  D IH0 - SH EH1 - V AH0 L D
+DISHING  D IH1 - SH IH0 NG
+DISHMAN  D IH1 SH - M AH0 N
+DISHNER  D IH1 SH - N ER0
+DISHON  D IH1 - S AH0 N
+DISHONEST  D IH0 S - AA1 - N AH0 S T
+DISHONESTLY  D IH0 S - AO1 - N AH0 S T - L IY0
+DISHONESTY  D IH0 S - AA1 - N AH0 - S T IY0
+DISHONG  D IH1 - S AO0 NG
+DISHONOR  D IH0 S - AA1 - N ER0
+DISHONORABLE  D IH0 S - AA1 - N ER0 - AH0 - B AH0 L
+DISHONORED  D IH0 S - AA1 - N ER0 D
+DISHWASHER  D IH1 SH - W AA2 - SH ER0
+DISHWASHERS  D IH1 SH - W AA2 - SH ER0 Z
+DISHWASHING  D IH1 SH - W AA2 - SH IH0 NG
+DISILLUSION  D IH2 S - IH0 - L UW1 - ZH AH0 N
+DISILLUSIONED  D IH2 S - IH0 - L UW1 - ZH AH0 N D
+DISILLUSIONING  D IH2 S - IH0 - L UW1 - ZH AH0 N - IH0 NG
+DISILLUSIONMENT  D IH2 S - IH0 - L UW1 - ZH AH0 N - M AH0 N T
+DISILVESTRO  D IH0 - S IY0 L - V EH1 - S T R OW0
+DISIMONE  D IH0 - S IY0 - M OW1 - N IY0
+DISINCENTIVE  D IH2 S - IH0 N - S EH1 N - T IH0 V
+DISINCENTIVES  D IH2 S - IH0 N - S EH1 N - T IH0 V Z
+DISINCLINATION  D IH0 S - IH0 N - K L AH0 - N EY1 - SH AH0 N
+DISINCLINE  D IH2 S - IH0 N - K L AY1 N
+DISINCLINED  D IH2 S - IH0 N - K L AY1 N D
+DISINFECT  D IH0 S - IH0 N - F EH1 K T
+DISINFECTANT  D IH0 S - IH0 N - F EH1 K - T AH0 N T
+DISINFECTANTS  D IH0 S - IH0 N - F EH1 K - T AH0 N T S
+DISINFECTION  D IH0 S - IH0 N - F EH1 K - SH AH0 N
+DISINFLATE  D IH2 S - IH0 N - F L EY1 T
+DISINFLATION  D IH2 S - IH0 N - F L EY1 - SH AH0 N
+DISINFLATIONARY  D IH2 S - IH0 N - F L EY1 - SH AH0 N - EH2 - R IY0
+DISINFORM  D IH0 S - IH0 N - F AO1 R M
+DISINFORMATION  D IH0 - Z IH2 N - F ER0 - M EY1 - SH AH0 N
+DISINGENUOUS  D IH0 S - IH0 N - JH EH1 - N Y UW0 - AH0 S
+DISINGENUOUSNESS  D IH2 S - IH0 N - JH EH1 - N Y UW0 - AH0 S - N AH0 S
+DISINTEGRATE  D IH0 S - IH1 N - T AH0 - G R EY2 T
+DISINTEGRATED  D IH0 S - IH1 N - T AH0 - G R EY2 - T IH0 D
+DISINTEGRATES  D IH0 S - IH1 N - T AH0 - G R EY2 T S
+DISINTEGRATING  D IH0 S - IH1 N - T AH0 - G R EY2 - T IH0 NG
+DISINTEGRATION  D IH0 S - IH2 N - T AH0 - G R EY1 - SH AH0 N
+DISINTEGRATION(2)  D IH0 S - IH2 - N AH0 - G R EY1 - SH AH0 N
+DISINTEREST  D IH0 S - IH1 N - T ER0 - AH0 S T
+DISINTERESTED  D IH0 S - IH1 N - T R IH0 - S T IH0 D
+DISINTERESTED(2)  D IH0 S - IH1 N - R IH0 - S T IH0 D
+DISINVESTMENT  D IH0 S - IH0 N - V EH1 S T - M AH0 N T
+DISINVESTMENT(2)  D IH0 S - IH0 N - V EH1 S - M AH0 N T
+DISINVITE  D IH0 - S IH0 N - V AY1 T
+DISINVITED  D IH2 - S IH2 N - V AY1 - T IH0 D
+DISJOINT  D IH0 S - JH OY1 N T
+DISJOINTED  D IH0 S - JH OY1 N - T IH0 D
+DISK  D IH1 S K
+DISKETTE  D IH0 - S K EH1 T
+DISKETTES  D IH0 - S K EH1 T S
+DISKIN  D IH1 - S K IH0 N
+DISKLESS  D IH1 S K - L AH0 S
+DISKS  D IH1 S K S
+DISLIKE  D IH0 S - L AY1 K
+DISLIKED  D IH0 S - L AY1 K T
+DISLIKES  D IH0 S - L AY1 K S
+DISLIKING  D IH0 S - L AY1 - K IH0 NG
+DISLOCATE  D IH1 S - L OW0 - K EY0 T
+DISLOCATED  D IH1 S - L OW0 - K EY0 - T IH0 D
+DISLOCATION  D IH0 S - L OW1 - K EY1 - SH AH0 N
+DISLOCATIONS  D IH0 S - L OW1 - K EY1 - SH AH0 N Z
+DISLODGE  D IH0 S - L AA1 JH
+DISLODGED  D IH0 S - L AA1 JH D
+DISLODGING  D IH0 S - L AA1 - JH IH0 NG
+DISLOYAL  D IH0 S - L OY1 - AH0 L
+DISLOYALTY  D IH0 S - L OY1 - AH0 L - T IY0
+DISMAL  D IH1 Z - M AH0 L
+DISMALLY  D IH1 Z - M AH0 - L IY0
+DISMANTLE  D IH0 S - M AE1 N - T AH0 L
+DISMANTLE(2)  D IH0 S - M AE1 - N AH0 L
+DISMANTLED  D IH0 S - M AE1 N - T AH0 L D
+DISMANTLED(2)  D IH0 S - M AE1 - N AH0 L D
+DISMANTLEMENT  D IH0 S - M AE1 N - T AH0 L - M AH0 N T
+DISMANTLES  D IH0 S - M AE1 N - T AH0 L Z
+DISMANTLING  D IH0 S - M AE1 N - T AH0 L - IH0 NG
+DISMANTLING(2)  D IH0 S - M AE1 - N AH0 L - IH0 NG
+DISMANTLING(3)  D IH2 S - M AE1 N T - L IH0 NG
+DISMAY  D IH0 S - M EY1
+DISMAYED  D IH0 S - M EY1 D
+DISMAYING  D IH0 S - M EY1 - IH0 NG
+DISMAYS  D IH0 S - M EY1 Z
+DISMEMBER  D IH0 S - M EH1 M - B ER0
+DISMEMBERED  D IH0 S - M EH1 M - B ER0 D
+DISMEMBERING  D IH0 S - M EH1 M - B ER0 - IH0 NG
+DISMEMBERMENT  D IH0 S - M EH1 M - B ER0 - M AH0 N T
+DISMISS  D IH0 S - M IH1 S
+DISMISSAL  D IH0 S - M IH1 - S AH0 L
+DISMISSALS  D IH0 S - M IH1 - S AH0 L Z
+DISMISSED  D IH0 S - M IH1 S T
+DISMISSES  D IH0 S - M IH1 - S IH0 Z
+DISMISSING  D IH0 S - M IH1 - S IH0 NG
+DISMISSIVE  D IH0 S - M IH1 - S IH0 V
+DISMORE  D IH1 S - M AO0 R
+DISMUKE  D IH1 S - M Y UW0 K
+DISMUKES  D IH1 S - M Y UW0 K S
+DISMUTASE  D IH2 S - M Y UW0 - T EY1 Z
+DISNEY  D IH1 Z - N IY0
+DISNEY'S  D IH1 Z - N IY0 Z
+DISNEYLAND  D IH1 Z - N IY0 - L AE2 N D
+DISNEYWORLD  D IH1 Z - N IY0 - W ER0 L D
+DISOBEDIENCE  D IH2 S - AH0 - B IY1 - D IY0 - AH0 N S
+DISOBEDIENCE(2)  D IH2 S - OW0 - B IY1 - D IY0 - AH0 N S
+DISOBEDIENT  D IH2 S - AH0 - B IY1 - D IY0 - AH0 N T
+DISOBEDIENT(2)  D IH2 S - OW0 - B IY1 - D IY0 - AH0 N T
+DISOBEY  D IH2 S - AH0 - B EY1
+DISOBEYED  D IH2 S - OW0 - B EY1 D
+DISOBEYING  D IH2 S - OW0 - B EY1 - IH0 NG
+DISON  D IH1 - S AH0 N
+DISORDER  D IH0 S - AO1 R - D ER0
+DISORDERED  D IH0 S - AO1 R - D ER0 D
+DISORDERLY  D IH0 S - AO1 R - D ER0 - L IY0
+DISORDERS  D IH0 S - AO1 R - D ER0 Z
+DISORGANIZATION  D IH0 S - AO2 R - G AH0 - N AH0 - Z EY1 - SH AH0 N
+DISORGANIZE  D IH0 S - AO1 R - G AH0 - N AY2 Z
+DISORGANIZED  D IH0 S - AO1 R - G AH0 - N AY2 Z D
+DISORIENT  D IH0 S - AO1 - R IY0 - EH2 N T
+DISORIENTATION  D IH0 - S AO2 - R IY0 - AH0 N - T EY1 - SH AH0 N
+DISORIENTED  D IH0 S - AO1 - R IY0 - EH2 N - T IH0 D
+DISORIENTING  D IH0 S - AO1 - R IY0 - EH2 N - T IH0 NG
+DISOWN  D IH0 S - OW1 N
+DISOWNED  D IH0 S - OW1 N D
+DISPAIR  D IH0 - S P EH1 R
+DISPARAGE  D IH0 - S P EH1 - R IH0 JH
+DISPARAGED  D IH0 - S P EH1 - R IH0 JH D
+DISPARAGES  D IH0 - S P EH1 - R IH0 - JH IH0 Z
+DISPARAGING  D IH0 - S P EH1 - R IH0 - JH IH0 NG
+DISPARAGINGLY  D IH0 - S P EH1 - R IH0 - JH IH0 NG - L IY0
+DISPARATE  D IH1 - S P ER0 - IH0 T
+DISPARATE(2)  D IH0 - S P EH1 - R IH0 T
+DISPARITIES  D IH0 - S P EH1 - R AH0 - T IY0 Z
+DISPARITY  D IH0 - S P EH1 - R AH0 - T IY0
+DISPASSIONATE  D IH0 - S P AE1 - SH AH0 N - AH0 T
+DISPASSIONATELY  D IH0 - S P AE1 - SH AH0 N - AH0 T - L IY0
+DISPATCH  D IH0 - S P AE1 CH
+DISPATCHED  D IH0 - S P AE1 CH T
+DISPATCHER  D IH0 - S P AE1 - CH ER0
+DISPATCHER'S  D IH0 - S P AE1 - CH ER0 Z
+DISPATCHER'S(2)  D IH1 - S P AE2 - CH ER0 Z
+DISPATCHER(2)  D IH1 - S P AE2 - CH ER0
+DISPATCHERS  D IH0 - S P AE1 - CH ER0 Z
+DISPATCHES  D IH0 - S P AE1 - CH IH0 Z
+DISPATCHING  D IH0 - S P AE1 - CH IH0 NG
+DISPEL  D IH0 - S P EH1 L
+DISPELL  D IH0 - S P EH1 L
+DISPELLED  D IH0 - S P EH1 L D
+DISPELLING  D IH0 - S P EH1 - L IH0 NG
+DISPELS  D IH0 - S P EH1 L Z
+DISPENSABLE  D IH0 - S P EH1 N - S AH0 - B AH0 L
+DISPENSARY  D IH0 - S P EH1 N - S ER0 - IY0
+DISPENSARY(2)  D IH1 - S P EH0 N - S EH2 - R IY0
+DISPENSATION  D IH2 - S P AH0 N - S EY1 - SH AH0 N
+DISPENSE  D IH0 - S P EH1 N S
+DISPENSED  D IH0 - S P EH1 N S T
+DISPENSER  D IH0 - S P EH1 N - S ER0
+DISPENSERS  D IH0 - S P EH1 N - S ER0 Z
+DISPENSES  D IH0 - S P EH1 N - S IH0 Z
+DISPENSING  D IH0 - S P EH1 N - S IH0 NG
+DISPENZA  D IH0 - S P EH1 N - Z AH0
+DISPERSAL  D IH0 - S P ER1 - S AH0 L
+DISPERSANT  D IH2 - S P ER1 - S AH0 N T
+DISPERSANTS  D IH2 - S P ER1 - S AH0 N T S
+DISPERSE  D IH0 - S P ER1 S
+DISPERSED  D IH0 - S P ER1 S T
+DISPERSING  D IH0 - S P ER1 - S IH0 NG
+DISPERSION  D IH0 - S P ER1 - ZH AH0 N
+DISPERSIVE  D IH0 - S P ER1 - S IH0 V
+DISPIRITED  D IH0 - S P IH1 - R AH0 - T IH0 D
+DISPIRITING  D IH0 - S P IH1 - R IH0 - T IH0 NG
+DISPLACE  D IH0 S - P L EY1 S
+DISPLACED  D IH0 S - P L EY1 S T
+DISPLACEMENT  D IH0 S - P L EY1 S - M AH0 N T
+DISPLACEMENTS  D IH0 S - P L EY1 S - M AH0 N T S
+DISPLACES  D IH0 S - P L EY1 - S IH0 Z
+DISPLACING  D IH0 S - P L EY1 - S IH0 NG
+DISPLAY  D IH0 - S P L EY1
+DISPLAYED  D IH0 - S P L EY1 D
+DISPLAYING  D IH0 - S P L EY1 - IH0 NG
+DISPLAYS  D IH0 - S P L EY1 Z
+DISPLAYWRITE  D IH0 - S P L EY1 - R AY2 T
+DISPLEASE  D IH0 S - P L IY1 Z
+DISPLEASED  D IH0 S - P L IY1 Z D
+DISPLEASURE  D IH0 S - P L EH1 - ZH ER0
+DISPOSABLE  D IH0 - S P OW1 - Z AH0 - B AH0 L
+DISPOSABLES  D IH0 - S P OW1 - Z AH0 - B AH0 L Z
+DISPOSAL  D IH0 - S P OW1 - Z AH0 L
+DISPOSALS  D IH0 - S P OW1 - Z AH0 L Z
+DISPOSE  D IH0 - S P OW1 Z
+DISPOSED  D IH0 - S P OW1 Z D
+DISPOSER  D IH0 - S P OW1 - Z ER0
+DISPOSES  D IH0 - S P OW1 - Z IH0 Z
+DISPOSING  D IH0 - S P OW1 - Z IH0 NG
+DISPOSITION  D IH2 - S P AH0 - Z IH1 - SH AH0 N
+DISPOSITIONS  D IH2 - S P AH0 - Z IH1 - SH AH0 N Z
+DISPOSITIVE  D IH2 - S P AA1 - Z AH0 - T IH0 V
+DISPOSSESS  D IH2 S - P AH0 - Z EH1 S
+DISPOSSESSED  D IH2 S - P AH0 - Z EH1 S T
+DISPROPORTIONATE  D IH2 - S P R AH0 - P AO1 R - SH AH0 N - IH0 T
+DISPROPORTIONATELY  D IH2 - S P R AH0 - P AO1 R - SH AH0 N - AH0 T - L IY0
+DISPROVE  D IH0 S - P R UW1 V
+DISPROVED  D IH0 S - P R UW1 V D
+DISPROVEN  D IH0 S - P R UW1 - V IH0 N
+DISPROVES  D IH0 S - P R UW1 V Z
+DISPUTATION  D IH0 - S P Y UW1 - T EY1 - SH AH0 N
+DISPUTE  D IH0 - S P Y UW1 T
+DISPUTED  D IH0 - S P Y UW1 - T AH0 D
+DISPUTED(2)  D IH0 - S P Y UW1 - T IH0 D
+DISPUTES  D IH0 - S P Y UW1 T S
+DISPUTING  D IH0 - S P Y UW1 - T IH0 NG
+DISQUALIFICATION  D IH0 S - K W AA2 - L AH0 - F AH0 - K EY1 - SH AH0 N
+DISQUALIFIED  D IH0 S - K W AA1 - L AH0 - F AY2 D
+DISQUALIFIES  D IH0 S - K W AA1 - L AH0 - F AY2 Z
+DISQUALIFY  D IH0 S - K W AA1 - L AH0 - F AY2
+DISQUALIFYING  D IH0 S - K W AA1 - L AH0 - F AY2 - IH0 NG
+DISQUE  D IH1 S K
+DISQUIET  D IH0 S - K W AY1 - AH0 T
+DISQUIETING  D IH0 S - K W AY1 - AH0 - T IH0 NG
+DISRAELI  D IH0 Z - R EY1 - L IY0
+DISREGARD  D IH2 S - R IH0 - G AA1 R D
+DISREGARDED  D IH2 S - R IH0 - G AA1 R - D IH0 D
+DISREGARDING  D IH2 S - R IH0 - G AA1 R - D IH0 NG
+DISREGARDS  D IH2 S - R IH0 - G AA1 R D Z
+DISREPAIR  D IH2 S - R IH0 - P EH1 R
+DISREPUTABLE  D IH0 S - R EH1 - P Y AH0 - T AH0 - B AH0 L
+DISREPUTE  D IH2 S - R IH0 - P Y UW1 T
+DISRESPECT  D IH2 S - R IH0 - S P EH1 K T
+DISRESPECTED  D IH2 S - R IH0 - S P EH1 K - T IH0 D
+DISRESPECTFUL  D IH2 S - R IH0 - S P EH1 K T - F AH0 L
+DISRESPECTING  D IH2 S - R IH0 - S P EH1 K - T IH0 NG
+DISRESPECTS  D IH2 S - R IH0 - S P EH1 K T S
+DISRUPT  D IH0 S - R AH1 P T
+DISRUPTED  D IH0 S - R AH1 P - T IH0 D
+DISRUPTING  D IH0 S - R AH1 P - T IH0 NG
+DISRUPTION  D IH0 S - R AH1 P - SH AH0 N
+DISRUPTIONS  D IH0 S - R AH1 P - SH AH0 N Z
+DISRUPTIVE  D IH0 S - R AH1 P - T IH0 V
+DISRUPTS  D IH0 S - R AH1 P T S
+DISS  D IH1 S
+DISSATISFACTION  D IH2 S - AE0 - T IH0 S - F AE1 K - SH AH0 N
+DISSATISFIED  D IH0 S - AE1 - T AH0 S - F AY2 D
+DISSATISFY  D IH0 S - AE1 - T AH0 S - F AY2
+DISSECT  D AY0 - S EH1 K T
+DISSECTED  D AY0 - S EH1 K - T AH0 D
+DISSECTING  D AY0 - S EH1 K - T IH0 NG
+DISSECTION  D AY0 - S EH1 K - SH AH0 N
+DISSECTION(2)  D AY1 - S EH0 K - SH AH0 N
+DISSECTIONS  D AY0 - S EH1 K - SH AH0 N Z
+DISSECTIONS(2)  D AY1 - S EH0 K - SH AH0 N Z
+DISSECTS  D AY0 - S EH1 K T S
+DISSECTS(2)  D AY0 - S EH1 K S
+DISSEMBLE  D IH0 - S EH1 M - B AH0 L
+DISSEMBLING  D IH0 - S EH1 M - B L IH0 NG
+DISSEMINATE  D IH0 - S EH1 - M AH0 - N EY2 T
+DISSEMINATED  D IH0 - S EH1 - M AH0 - N EY2 - T AH0 D
+DISSEMINATING  D IH0 - S EH1 - M AH0 - N EY2 - T IH0 NG
+DISSEMINATION  D IH0 - S EH2 - M AH0 - N EY1 - SH AH0 N
+DISSENSION  D IH0 - S EH1 N - SH AH0 N
+DISSENT  D IH0 - S EH1 N T
+DISSENTED  D IH0 - S EH1 N - T IH0 D
+DISSENTED(2)  D IH0 - S EH1 - N IH0 D
+DISSENTER  D IH0 - S EH1 N - T ER0
+DISSENTERS  D IH0 - S EH1 N - T ER0 Z
+DISSENTERS(2)  D IH0 - S EH1 - N ER0 Z
+DISSENTING  D IH0 - S EH1 N - T IH0 NG
+DISSENTING(2)  D IH0 - S EH1 - N IH0 NG
+DISSENTS  D IH0 - S EH1 N T S
+DISSERTATION  D IH2 - S ER0 - T EY1 - SH AH0 N
+DISSERVICE  D IH0 S - S ER1 - V AH0 S
+DISSERVICE(2)  D IH0 - S ER1 - V AH0 S
+DISSIDENCE  D IH1 - S AH0 - D IH0 N S
+DISSIDENT  D IH1 - S AH0 - D IH0 N T
+DISSIDENTS  D IH1 - S AH0 - D AH0 N T S
+DISSIDENTS'  D IH1 - S AH0 - D AH0 N T S
+DISSIMILAR  D IH0 - S S IH1 - M AH0 - L ER0
+DISSIMILAR(2)  D IH0 - S IH1 - M AH0 - L ER0
+DISSIMILARITY  D IH0 - S S IH2 - M AH0 - L AE1 - R AH0 - T IY0
+DISSIMILARITY(2)  D IH2 - S IH2 - M AH0 - L AE1 - R AH0 - T IY0
+DISSINGER  D IH1 S - IH0 N - JH ER0
+DISSIPATE  D IH1 - S AH0 - P EY2 T
+DISSIPATED  D IH1 - S AH0 - P EY2 - T IH0 D
+DISSIPATES  D IH1 - S AH0 - P EY2 T S
+DISSIPATING  D IH1 - S AH0 - P EY2 - T IH0 NG
+DISSIPATION  D IH2 - S IH0 - P EY1 - SH AH0 N
+DISSIPATIVE  D IH1 - S AH0 - P EY2 - T IH0 V
+DISSOCIATE  D IH0 - S OW1 - S IY0 - EY0 T
+DISSOCIATION  D IH0 - S OW2 - S IY0 - EY1 - SH AH0 N
+DISSOLUTION  D IH2 - S AH0 - L UW1 - SH AH0 N
+DISSOLVE  D IH0 - Z AA1 L V
+DISSOLVED  D IH0 - Z AA1 L V D
+DISSOLVER  D IH0 - Z AA1 L - V ER0
+DISSOLVERS  D IH0 - Z AA1 L - V ER0 Z
+DISSOLVES  D IH0 - Z AA1 L V Z
+DISSOLVING  D IH0 - Z AO1 L - V IH0 NG
+DISSONANCE  D IH1 - S AH0 - N AH0 N S
+DISSONANT  D IH1 - S AH0 - N AH0 N T
+DISSUADE  D IH0 - S W EY1 D
+DISSUADED  D IH0 - S W EY1 - D IH0 D
+DISSYMMETRIC  D IH2 - S IH0 - M EH1 - T R IH0 K
+DISSYMMETRY  D IH0 - S IH1 - M AH0 - T R IY0
+DISTAD  D IH1 - S T AH0 D
+DISTAL  D IH1 - S T AH0 L
+DISTANCE  D IH1 - S T AH0 N S
+DISTANCED  D IH1 - S T AH0 N S T
+DISTANCES  D IH1 - S T AH0 N - S AH0 Z
+DISTANCES(2)  D IH1 - S T AH0 N - S IH0 Z
+DISTANCING  D IH1 - S T AH0 N - S IH0 NG
+DISTANT  D IH1 - S T AH0 N T
+DISTASI  D IH0 - S T AA1 - S IY0
+DISTASIO  D IH0 - S T AA1 - S IY0 - OW0
+DISTASTE  D IH0 S - T EY1 S T
+DISTASTEFUL  D IH0 S - T EY1 S T - F AH0 L
+DISTEFANO  D IH0 - S T EH0 - F AA1 - N OW0
+DISTEL  D IH1 - S T AH0 L
+DISTEMPER  D IH0 - S T EH1 M - P ER0
+DISTEND  D IH0 - S T EH1 N D
+DISTENDED  D IH0 - S T EH1 N - D IH0 D
+DISTIL  D IH0 - S T IH1 L
+DISTILL  D IH0 - S T IH1 L
+DISTILLATE  D IH1 - S T AH0 - L EY2 T
+DISTILLATE(2)  D IH1 - S T AH0 - L AH0 T
+DISTILLATES  D IH1 - S T AH0 - L EY2 T S
+DISTILLATION  D IH2 - S T AH0 - L EY1 - SH AH0 N
+DISTILLED  D IH0 - S T IH1 L D
+DISTILLER  D IH0 - S T IH1 - L ER0
+DISTILLER'S  D IH0 - S T IH1 - L ER0 Z
+DISTILLERIES  D IH0 - S T IH1 - L ER0 - IY0 Z
+DISTILLERS  D IH0 - S T IH1 - L ER0 Z
+DISTILLERS'  D IH0 - S T IH1 - L ER0 Z
+DISTILLERS'S  D IH0 - S T IH1 - L ER0 - Z IH0 Z
+DISTILLERY  D IH0 - S T IH1 - L ER0 - IY0
+DISTILLING  D IH0 - S T IH1 - L IH0 NG
+DISTILLS  D IH0 - S T IH1 L Z
+DISTINCT  D IH0 - S T IH1 NG K T
+DISTINCTION  D IH0 - S T IH1 NG K - SH AH0 N
+DISTINCTIONS  D IH0 - S T IH1 NG K - SH AH0 N Z
+DISTINCTIVE  D IH0 - S T IH1 NG K - T IH0 V
+DISTINCTIVELY  D IH0 - S T IH1 NG K - T IH0 V - L IY0
+DISTINCTIVENESS  D IH0 - S T IH1 NG K - T IH0 V - N AH0 S
+DISTINCTLY  D IH0 - S T IH1 NG K T - L IY0
+DISTINGUISH  D IH0 - S T IH1 NG - G W IH0 SH
+DISTINGUISHABLE  D IH0 - S T IH1 NG - G W IH0 - SH AH0 - B AH0 L
+DISTINGUISHED  D IH0 - S T IH1 NG - G W IH0 SH T
+DISTINGUISHES  D IH0 - S T IH1 NG - G W IH0 - SH IH0 Z
+DISTINGUISHING  D IH0 - S T IH1 NG - G W IH0 - SH IH0 NG
+DISTLER  D IH1 S T - L ER0
+DISTORT  D IH0 - S T AO1 R T
+DISTORTED  D IH0 - S T AO1 R - T AH0 D
+DISTORTED(2)  D IH0 - S T AO1 R - T IH0 D
+DISTORTING  D IH0 - S T AO1 R - T IH0 NG
+DISTORTION  D IH0 - S T AO1 R - SH AH0 N
+DISTORTIONS  D IH0 - S T AO1 R - SH AH0 N Z
+DISTORTS  D IH0 - S T AO1 R T S
+DISTRACT  D IH0 - S T R AE1 K T
+DISTRACTED  D IH0 - S T R AE1 K - T AH0 D
+DISTRACTED(2)  D IH0 - S T R AE1 K - T IH0 D
+DISTRACTING  D IH0 - S T R AE1 K - T IH0 NG
+DISTRACTION  D IH0 S - T R AE1 K - SH AH0 N
+DISTRACTIONS  D IH0 S - T R AE1 K - SH AH0 N Z
+DISTRACTS  D IH0 - S T R AE1 K T S
+DISTRAUGHT  D IH0 - S T R AO1 T
+DISTRESS  D IH0 - S T R EH1 S
+DISTRESSED  D IH0 - S T R EH1 S T
+DISTRESSES  D IH0 - S T R EH1 - S IH0 Z
+DISTRESSING  D IH0 - S T R EH1 - S IH0 NG
+DISTRESSINGLY  D IH0 - S T R EH1 - S IH0 NG - L IY0
+DISTRIBUTE  D IH0 - S T R IH1 - B Y UW0 T
+DISTRIBUTED  D IH0 S - T R IH1 - B Y AH0 - T AH0 D
+DISTRIBUTES  D IH0 - S T R IH1 - B Y UW0 T S
+DISTRIBUTING  D IH0 - S T R IH1 - B Y UW0 - T IH0 NG
+DISTRIBUTION  D IH2 S - T R AH0 - B Y UW1 - SH AH0 N
+DISTRIBUTIONS  D IH2 S - T R AH0 - B Y UW1 - SH AH0 N Z
+DISTRIBUTIVE  D IH0 - S T R IH1 - B Y UW0 - T IH0 V
+DISTRIBUTOR  D IH0 S - T R IH1 - B Y AH0 - T ER0
+DISTRIBUTOR'S  D IH0 - S T R IH1 - B Y UW0 - T ER0 Z
+DISTRIBUTORS  D IH0 S - T R IH1 - B Y AH0 - T ER0 Z
+DISTRIBUTORS'  D IH0 S - T R IH1 - B Y AH0 - T ER0 Z
+DISTRIBUTORSHIP  D IH0 - S T R IH1 - B Y UW0 - T ER0 - SH IH2 P
+DISTRIBUTORSHIPS  D IH0 - S T R IH1 - B Y UW0 - T ER0 - SH IH2 P S
+DISTRICT  D IH1 - S T R IH0 K T
+DISTRICT'S  D IH1 - S T R IH0 K T S
+DISTRICTING  D IH1 - S T R IH0 K - T IH0 N G
+DISTRICTS  D IH1 - S T R IH0 K T S
+DISTRIGAS  D IH0 S - T R IY1 - G AH0 S
+DISTRON  D IH1 - S T R AA2 N
+DISTRUST  D IH0 S - T R AH1 S T
+DISTRUSTED  D IH0 S - T R AH1 - S T AH0 D
+DISTRUSTED(2)  D IH0 S - T R AH1 - S T IH0 D
+DISTRUSTFUL  D IH0 S - T R AH1 S T - F AH0 L
+DISTRUSTS  D IH0 S - T R AH1 S T S
+DISTRUSTS(2)  D IH0 - S T R AH1 S S
+DISTRUSTS(3)  D IH0 - S T R AH1 S
+DISTURB  D IH0 - S T ER1 B
+DISTURBANCE  D IH0 - S T ER1 - B AH0 N S
+DISTURBANCES  D IH0 - S T ER1 - B AH0 N - S AH0 Z
+DISTURBANCES(2)  D IH0 - S T ER1 - B AH0 N - S IH0 Z
+DISTURBED  D IH0 - S T ER1 B D
+DISTURBING  D IH0 - S T ER1 - B IH0 NG
+DISTURBINGLY  D IH0 - S T ER1 - B IH0 NG - L IY0
+DISTURBS  D IH0 - S T ER1 B Z
+DISUNION  D IH0 S - Y UW1 - N Y AH0 N
+DISUNITY  D IH0 S - Y UW1 - N AH0 - T IY0
+DISUSE  D IH0 S - Y UW1 S
+DITCH  D IH1 CH
+DITCHED  D IH1 CH T
+DITCHES  D IH1 - CH AH0 Z
+DITCHES(2)  D IH1 - CH IH0 Z
+DITCHING  D IH1 - CH IH0 NG
+DITH  D IH1 TH
+DITHER  D IH1 - DH ER0
+DITHERING  D IH1 - DH ER0 - IH0 NG
+DITHERS  D IH1 - DH ER0 Z
+DITHYRAMB  D IH1 - TH ER0 - AE2 M
+DITKA  D IH1 T - K AH0
+DITKA'S  D IH1 T - K AH0 Z
+DITLOW  D IH1 T - L OW0
+DITMARS  D IH1 T - M ER0 Z
+DITMER  D IH1 T - M ER0
+DITMORE  D IH1 T - M AO0 R
+DITOMASSO  D IH0 - T OW0 - M AA1 - S OW0
+DITOMMASO  D IH0 - T OW0 - M AA1 - S OW0
+DITSY  D IH1 T - S IY0
+DITTBERNER  D IH1 T - B ER0 - N ER0
+DITTEMORE  D IH0 - T EH1 - M AO0 R
+DITTER  D IH1 - T ER0
+DITTIES  D IH1 - T IY0 Z
+DITTMAN  D IH1 T - M AH0 N
+DITTMANN  D IH1 T - M AH0 N
+DITTMAR  D IH1 T - M ER0
+DITTMER  D IH1 T - M ER0
+DITTO  D IH1 - T OW0
+DITTON  D IH1 - T AH0 N
+DITTRICH  D IH1 - T R IH0 K
+DITTUS  D IH1 - T AH0 S
+DITTY  D IH1 - T IY0
+DITULLIO  D IH0 - T AH1 - L IY0 - OW0
+DITZEL  D IH1 T - Z AH0 L
+DITZLER  D IH1 T - S L ER0
+DIURETIC  D AY2 - UW0 - R EH1 - T IH0 K
+DIURETICS  D AY2 - UW0 - R EH1 - T IH0 K S
+DIURNAL  D AY0 - ER1 - N AH0 L
+DIURNALLY  D AY0 - ER1 - N AH0 - L IY0
+DIVA  D IY1 - V AH0
+DIVAD  D IH1 - V AE0 D
+DIVALENT  D AY0 - V EY1 - L AH0 N T
+DIVALL  D IH1 - V AH0 L
+DIVAN  D IH0 - V AE1 N
+DIVAS  D IY1 - V AH0 Z
+DIVE  D AY1 V
+DIVED  D AY1 V D
+DIVELBISS  D IH0 - V EH1 L - B IH0 S
+DIVELEY  D IH1 - V IH0 - L IY0
+DIVELY  D AY1 V - L IY0
+DIVEN  D AY1 - V AH0 N
+DIVENS  D AY1 - V AH0 N Z
+DIVER  D AY1 - V ER0
+DIVER'S  D AY1 - V ER0 Z
+DIVERGE  D IH0 - V ER1 JH
+DIVERGED  D AY0 - V ER1 JH D
+DIVERGENCE  D AY0 - V ER1 - JH AH0 N S
+DIVERGENCE(2)  D IH0 - V ER1 - JH AH0 N S
+DIVERGENCES  D AY0 - V ER1 - JH AH0 N - S IH0 Z
+DIVERGENT  D AY0 - V ER1 - JH AH0 N T
+DIVERGENT(2)  D IH0 - V ER1 - JH AH0 N T
+DIVERGES  D AY0 - V ER1 - JH IH0 Z
+DIVERGING  D AY0 - V ER1 - JH IH0 NG
+DIVERS  D AY1 - V ER0 Z
+DIVERSE  D AY0 - V ER1 S
+DIVERSE(2)  D IH0 - V ER1 S
+DIVERSICARE  D IH1 - V ER0 - S IH0 - K EH2 R
+DIVERSIFICATION  D AY0 - V ER2 - S AH0 - F AH0 - K EY1 - SH AH0 N
+DIVERSIFICATION(2)  D IH0 - V ER2 - S AH0 - F AH0 - K EY1 - SH AH0 N
+DIVERSIFICATIONS  D AY0 - V ER2 - S AH0 - F AH0 - K EY1 - SH AH0 N Z
+DIVERSIFICATIONS(2)  D IH0 - V ER2 - S AH0 - F AH0 - K EY1 - SH AH0 N Z
+DIVERSIFIED  D AY0 - V ER1 - S AH0 - F AY2 D
+DIVERSIFIED(2)  D IH0 - V ER1 - S AH0 - F AY2 D
+DIVERSIFY  D AY0 - V ER1 - S AH0 - F AY2
+DIVERSIFY(2)  D IH0 - V ER1 - S AH0 - F AY2
+DIVERSIFYING  D AY0 - V ER1 - S AH0 - F AY2 - IH0 NG
+DIVERSIFYING(2)  D IH0 - V ER1 - S AH0 - F AY2 - IH0 NG
+DIVERSION  D AY0 - V ER1 - ZH AH0 N
+DIVERSION(2)  D IH0 - V ER1 - ZH AH0 N
+DIVERSIONARY  D AY0 - V ER1 - ZH AH0 N - EH2 - R IY0
+DIVERSIONARY(2)  D IH0 - V ER1 - ZH AH0 N - EH2 - R IY0
+DIVERSIONS  D IH0 - V ER1 - ZH AH0 N Z
+DIVERSIONS(2)  D AY0 - V ER1 - ZH AH0 N Z
+DIVERSITY  D IH0 - V ER1 - S AH0 - T IY0
+DIVERSITY(2)  D IH0 - V ER1 - S IH0 - T IY0
+DIVERSITY(3)  D AY0 - V ER1 - S AH0 - T IY0
+DIVERSITY(4)  D AY0 - V ER1 - S IH0 - T IY0
+DIVERT  D AY0 - V ER1 T
+DIVERT(2)  D IH0 - V ER1 T
+DIVERTED  D AY0 - V ER1 - T IH0 D
+DIVERTED(2)  D IH0 - V ER1 - T IH0 D
+DIVERTICULA  D AY2 - V ER0 - T IH1 - K Y AH0 - L AH0
+DIVERTICULUM  D AY2 - V ER0 - T IH1 - K Y AH0 - L AH0 M
+DIVERTIMENTO  D IH0 - V ER2 - T AH0 - M EH1 N - T OW2
+DIVERTING  D AY0 - V ER1 - T IH0 NG
+DIVERTING(2)  D IH0 - V ER1 - T IH0 NG
+DIVERTS  D AY0 - V ER1 T S
+DIVERTS(2)  D IH0 - V ER1 T S
+DIVES  D AY1 V Z
+DIVEST  D AY0 - V EH1 S T
+DIVEST(2)  D IH0 - V EH1 S T
+DIVESTED  D AY0 - V EH1 - S T IH0 D
+DIVESTING  D AY0 - V EH1 - S T IH0 NG
+DIVESTITURE  D IH0 - V EH1 - S T IH0 - CH ER0
+DIVESTITURE(2)  D AY0 - V EH1 - S T IH0 - CH ER0
+DIVESTITURES  D IH0 - V EH1 - S T IH0 - CH ER0 Z
+DIVESTITURES(2)  D AY0 - V EH1 - S T IH0 - CH ER0 Z
+DIVESTMENT  D AY0 - V EH1 S T - M AH0 N T
+DIVESTMENT(2)  D AY0 - V EH1 S - M AH0 N T
+DIVESTMENT(3)  D IH0 - V EH1 S - M AH0 N T
+DIVESTMENTS  D AY0 - V EH1 S T - M AH0 N T S
+DIVESTMENTS(2)  D AY0 - V EH1 S - M AH0 N T S
+DIVESTMENTS(3)  D IH0 - V EH1 S - M AH0 N T S
+DIVESTS  D AY0 - V EH1 S T S
+DIVESTS(2)  D AY0 - V EH1 S S
+DIVESTS(3)  D AY0 - V EH1 S
+DIVI  D IY1 - V IY0
+DIVIDE  D IH0 - V AY1 D
+DIVIDED  D IH0 - V AY1 - D AH0 D
+DIVIDEND  D IH1 - V IH0 - D EH2 N D
+DIVIDEND'S  D IH1 - V AH0 - D EH2 N D Z
+DIVIDENDS  D IH1 - V AH0 - D EH2 N D Z
+DIVIDER  D IH0 - V AY1 - D ER0
+DIVIDES  D IH0 - V AY1 D Z
+DIVIDING  D IH0 - V AY1 - D IH0 NG
+DIVINATION  D IH2 - V AH0 - N EY1 - SH AH0 N
+DIVINCENZO  D IH0 - V IY0 N - CH EH1 N - Z OW0
+DIVINE  D IH0 - V AY1 N
+DIVINELY  D IH0 - V AY1 N - L IY0
+DIVINEY  D IH1 - V IH0 - N IY0
+DIVING  D AY1 - V IH0 NG
+DIVINING  D AH0 - V AY1 - N IH0 NG
+DIVINITAS  D IH2 - V IH0 - N IY1 - T AH0 S
+DIVINITIES  D IH0 - V IH1 - N AH0 - T IY0 Z
+DIVINITY  D IH0 - V IH1 - N AH0 - T IY0
+DIVIRGILIO  D IH0 - V IH0 R - JH IY1 - L IY0 - OW0
+DIVIS  D IY1 - V IH0 S
+DIVISIBLE  D IH0 - V IH1 - Z AH0 - B AH0 L
+DIVISION  D IH0 - V IH1 - ZH AH0 N
+DIVISION'S  D IH0 - V IH1 - ZH AH0 N Z
+DIVISIONAL  D IH0 - V IH1 - ZH AH0 - N AH0 L
+DIVISIONS  D IH0 - V IH1 - ZH AH0 N Z
+DIVISIONS'  D IH0 - V IH1 - ZH AH0 N Z
+DIVISIVE  D IH0 - V AY1 - S IH0 V
+DIVISIVENESS  D IH0 - V AY1 - S IH0 V - N AH0 S
+DIVISON  D IH0 - V IH1 - ZH AH0 N
+DIVISON(2)  D IH0 - V IH1 - S AH0 N
+DIVISOR  D IH0 - V AY1 - Z ER0
+DIVITA  D IH0 - V IY1 - T AH0
+DIVITO  D IH0 - V IY1 - T OW0
+DIVORCE  D IH0 - V AO1 R S
+DIVORCED  D IH0 - V AO1 R S T
+DIVORCEE  D AH0 - V AO1 R - S IY2
+DIVORCEE(2)  D AH0 - V AO1 R - S EY2
+DIVORCES  D IH0 - V AO1 R - S IH0 Z
+DIVORCING  D IH0 - V AO1 R - S IH0 NG
+DIVULGE  D IH0 - V AH1 L JH
+DIVULGE(2)  D AY0 - V AH1 L JH
+DIVULGED  D IH0 - V AH1 L JH D
+DIVULGED(2)  D AY0 - V AH1 L JH D
+DIVULGING  D IH0 - V AH1 L - JH IH0 NG
+DIVULGING(2)  D AY0 - V AH1 L - JH IH0 NG
+DIVVIED  D IH1 - V IY0 D
+DIVVY  D IH1 - V IY0
+DIWA  D IY1 - W AH0
+DIX  D IH1 K S
+DIXIE  D IH1 K - S IY0
+DIXIELAND  D IH1 K - S IY0 - L AE2 N D
+DIXON  D IH1 K - S AH0 N
+DIXON'S  D IH1 K - S AH0 N Z
+DIXONS  D IH1 K - S AH0 N Z
+DIXSON  D IH1 K - S AH0 N
+DIXVILLE  D IH1 K S - V IH0 L
+DIXY  D IH1 K - S IY0
+DIZON  D IH1 - Z AH0 N
+DIZZINESS  D IH1 - Z IY0 - N AH0 S
+DIZZY  D IH1 - Z IY0
+DIZZYING  D IH1 - Z IY0 - IH0 NG
+DJAKARTA  JH AH0 - K AA1 R - T AH0
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+DOWLAND  D AW1 - L AH0 N D
+DOWLEN  D AW1 - L AH0 N
+DOWLER  D AW1 - L ER0
+DOWLESS  D AW1 - L AH0 S
+DOWLING  D AW1 - L IH0 NG
+DOWN  D AW1 N
+DOWN'S  D AW1 N Z
+DOWNARD  D AW1 - N ER0 D
+DOWNBEAT  D AW0 N - B IY1 T
+DOWNCAST  D AW1 N - K AE2 S T
+DOWNDRAFT  D AW1 N - D R AE2 F T
+DOWNE  D AW1 N
+DOWNED  D AW1 N D
+DOWNEN  D AW1 - N AH0 N
+DOWNER  D AW1 - N ER0
+DOWNERS  D AW1 - N ER0 Z
+DOWNES  D AW1 N Z
+DOWNES'S  D AW1 N - Z IH0 Z
+DOWNEY  D AW1 - N IY0
+DOWNEY'S  D AW1 - N IY0 Z
+DOWNFALL  D AW1 N - F AO2 L
+DOWNGRADE  D AW1 N - G R EY1 D
+DOWNGRADED  D AW1 N - G R EY1 - D AH0 D
+DOWNGRADES  D AW1 N - G R EY1 D Z
+DOWNGRADING  D AW1 N - G R EY1 - D IH0 NG
+DOWNGRADINGS  D AW1 N - G R EY2 - D IH0 NG Z
+DOWNHAM  D AW1 N - HH AH0 M
+DOWNHILL  D AW1 N - HH IH1 L
+DOWNIE  D AW1 - N IY0
+DOWNING  D AW1 - N IH0 NG
+DOWNINGTOWN  D AW1 - N IH0 NG - T AW2 N
+DOWNLOAD  D AW1 N - L OW2 D
+DOWNLOADED  D AW1 N - L OW2 - D IH0 D
+DOWNLOADING  D AW1 N - L OW2 - D IH0 NG
+DOWNPAYMENT  D AW2 N - P EY1 - M AH0 N T
+DOWNPLAY  D AW1 N - P L EY2
+DOWNPLAYED  D AW1 N - P L EY2 D
+DOWNPLAYING  D AW1 N - P L EY2 - IH0 NG
+DOWNPLAYS  D AW1 N - P L EY2 Z
+DOWNPOUR  D AW1 N - P AO0 R
+DOWNPOURS  D AW1 N - P AO2 R Z
+DOWNRANGE  D AW1 N - R EY1 N JH
+DOWNRIGHT  D AW1 N - R AY2 T
+DOWNRIVER  D AW2 N - R IH1 - V ER0
+DOWNS  D AW1 N Z
+DOWNSCALE  D AW1 N - S K EY2 L
+DOWNSIDE  D AW1 N - S AY2 D
+DOWNSIDES  D AW1 N - S AY2 D Z
+DOWNSIZE  D AW1 N - S AY2 Z
+DOWNSIZED  D AW1 N - S AY2 Z D
+DOWNSIZING  D AW1 N - S AY2 - Z IH0 NG
+DOWNSIZINGS  D AW1 N - S AY2 - Z IH0 NG Z
+DOWNSTAGE  D AW1 N - S T EY2 JH
+DOWNSTAIRS  D AW1 N - S T EH1 R Z
+DOWNSTATE  D AW1 N - S T EY2 T
+DOWNSTREAM  D AW1 N - S T R IY1 M
+DOWNSWING  D AW1 N - S W IH2 NG
+DOWNTIME  D AW1 N - T AY2 M
+DOWNTOWN  D AW1 N - T AW1 N
+DOWNTOWNS  D AW1 N - T AW1 N Z
+DOWNTREND  D AW1 N - T R EH2 N D
+DOWNTRODDEN  D AW2 N - T R AA1 - D AH0 N
+DOWNTURN  D AW1 N - T ER2 N
+DOWNTURNS  D AW1 N - T ER2 N Z
+DOWNUM  D AW1 - N AH0 M
+DOWNWARD  D AW1 N - W ER0 D
+DOWNWARDLY  D AW1 N - W ER0 D - L IY0
+DOWNWARDS  D AW1 N - W ER0 D Z
+DOWNWIND  D AW0 N - W IH1 N D
+DOWNY  D AW1 - N IY0
+DOWRY  D AW1 - R IY0
+DOWSE  D AW1 S
+DOWSING  D AW1 - S IH0 NG
+DOWSMAN  D AW1 Z - M AH0 N
+DOWTY  D AW1 - T IY0
+DOXEY  D AA1 K - S IY0
+DOXIE  D AA1 K - S IY0
+DOXOLOGIES  D AA0 K - S AA1 - L AH0 - JH IY0 Z
+DOXOLOGY  D AA0 K - S AA1 - L AH0 - JH IY0
+DOXTATER  D AA1 K - S T EY0 - T ER0
+DOXY  D AA1 K - S IY0
+DOYAL  D OY0 - AA1 L
+DOYEL  D OY1 - AH0 L
+DOYEN  D OY1 - IH0 N
+DOYLE  D OY1 L
+DOYLE'S  D OY1 L Z
+DOYON  D OY1 - AH0 N
+DOZE  D OW1 Z
+DOZED  D OW1 Z D
+DOZEN  D AH1 - Z AH0 N
+DOZENS  D AH1 - Z AH0 N Z
+DOZES  D OW1 - Z IH0 Z
+DOZIER  D OW1 - Z IY0 - ER0
+DOZING  D OW1 - Z IH0 NG
+DQALPHA  D IY1 - K Y UW1 - AE1 L - F AH0
+DR  D R AY1 V
+DR(2)  D AA1 K - T ER0
+DR.  D R AY1 V
+DR.(2)  D AA1 K - T ER0
+DRAB  D R AE1 B
+DRABBED  D R AE1 B D
+DRABBLE  D R AE1 - B AH0 L
+DRABEK  D R AE1 - B IH0 K
+DRABENSTOTT  D R AH0 - B EH1 N - S T AH0 T
+DRABIK  D R AA1 - B IH0 K
+DRABINSKY  D R AH0 - B IH1 N - S K IY0
+DRABKIN  D R AE1 B - K IH2 N
+DRABS  D R AE1 B Z
+DRACE  D R EY1 S
+DRACH  D R AE1 CH
+DRACHENBERG  D R AE1 - K AH0 N - B ER0 G
+DRACHMA  D R AE1 K - M AH0
+DRACHMAS  D R AA1 K - M AH0 Z
+DRACKETT  D R AE1 - K IH0 T
+DRACO  D R EY1 - K OW0
+DRACO(2)  D R AE1 - K OW0
+DRACONIAN  D R EY0 - K OW1 - N IY0 - AH0 N
+DRACONIAN(2)  D R AH0 - K OW1 - N IY0 - AH0 N
+DRACULA  D R AE1 - K Y UW0 - L AH0
+DRAEGER  D R EH1 - G ER0
+DRAFFEN  D R AE1 - F AH0 N
+DRAFT  D R AE1 F T
+DRAFT'S  D R AE1 F T S
+DRAFTED  D R AE1 F - T IH0 D
+DRAFTEE  D R AE1 F - T IY1
+DRAFTEES  D R AE1 F - T IY1 Z
+DRAFTER  D R AE1 F - T ER0
+DRAFTERS  D R AE1 F - T ER0 Z
+DRAFTING  D R AE1 F - T IH0 NG
+DRAFTS  D R AE1 F T S
+DRAFTSMAN  D R AE1 F T S - M AH0 N
+DRAFTSMANSHIP  D R AE1 F T S - M AH0 N - SH IH2 P
+DRAFTSMEN  D R AE1 F T S - M AH0 N
+DRAFTY  D R AE1 F - T IY0
+DRAG  D R AE1 G
+DRAGAN  D R AA1 - G AH0 N
+DRAGE  D R EY1 JH
+DRAGER  D R EY1 - G ER0
+DRAGGED  D R AE1 G D
+DRAGGING  D R AE1 - G IH0 NG
+DRAGGY  D R AE1 - G IY0
+DRAGLINE  D R AE1 - G L AY2 N
+DRAGNET  D R AE1 G - N EH2 T
+DRAGNETS  D R AE1 G - N EH2 T S
+DRAGO  D R AA1 - G OW0
+DRAGON  D R AE1 - G AH0 N
+DRAGON'S  D R AE1 - G AH0 N Z
+DRAGONAIR  D R AE1 - G AH0 - N EH2 R
+DRAGONE  D R AH0 - G OW1 N
+DRAGONHEAD  D R AE1 - G AH0 N - HH EH2 D
+DRAGONHEART  D R AE1 - G AH0 N - HH AA2 R T
+DRAGONS  D R AE1 - G AH0 N Z
+DRAGOO  D R AA1 - G UW0
+DRAGOVICH  D R AE1 - G AH0 - V IH0 CH
+DRAGS  D R AE1 G Z
+DRAHEIM  D R AE1 - HH AY0 M
+DRAHOS  D R EY1 - HH OW0 Z
+DRAHUSCHAK  D R AE1 - HH AH0 - SH AE0 K
+DRAHUSCHAK(2)  D R AH0 - HH UW1 - SH AH0 K
+DRAIN  D R EY1 N
+DRAINAGE  D R EY1 - N AH0 JH
+DRAINAGE(2)  D R EY1 - N IH0 JH
+DRAINE  D R EY1 N
+DRAINED  D R EY1 N D
+DRAINER  D R EY1 - N ER0
+DRAINERS  D R EY1 - N ER0 Z
+DRAINING  D R EY1 - N IH0 NG
+DRAINS  D R EY1 N Z
+DRAKE  D R EY1 K
+DRAKEFORD  D R AE1 K - F AO0 R D
+DRAKES  D R EY1 K S
+DRAKOS  D R EY1 - K OW0 Z
+DRALLE  D R EY1 L
+DRAM  D R AE1 M
+DRAM(2)  D IY1 - R AE2 M
+DRAMA  D R AA1 - M AH0
+DRAMAMINE  D R AE1 - M AH0 - M IY2 N
+DRAMAS  D R AA1 - M AH0 Z
+DRAMATIC  D R AH0 - M AE1 - T IH0 K
+DRAMATICALLY  D R AH0 - M AE1 - T IH0 K - L IY0
+DRAMATICALLY(2)  D R AH0 - M AE1 - T IH0 - K AH0 - L IY0
+DRAMATIST  D R AA1 - M AH0 - T IH0 S T
+DRAMATIZATION  D R AE2 - M AH0 - T AH0 - Z EY1 - SH AH0 N
+DRAMATIZATIONS  D R AE2 - M AH0 - T AH0 - Z EY1 - SH AH0 N Z
+DRAMATIZE  D R AA1 - M AH0 - T AY2 Z
+DRAMATIZE(2)  D R AE1 - M AH0 - T AY2 Z
+DRAMATIZED  D R AE1 - M AH0 - T AY2 Z D
+DRAMATIZES  D R AE1 - M AH0 - T AY2 - Z IH0 Z
+DRAMATIZING  D R AE1 - M AH0 - T AY2 - Z IH0 NG
+DRAMS  D R AE1 M Z
+DRAMS(2)  D IY1 - R AE2 M Z
+DRANE  D R EY1 N
+DRANEY  D R EY1 - N IY0
+DRANG  D R AE1 NG
+DRANK  D R AE1 NG K
+DRANSFIELD  D R AE1 N S - F IY2 L D
+DRAPE  D R EY1 P
+DRAPEAU  D R AH0 - P OW1
+DRAPED  D R EY1 P T
+DRAPER  D R EY1 - P ER0
+DRAPERIES  D R EY1 - P ER0 - IY0 Z
+DRAPERY  D R EY1 - P ER0 - IY0
+DRAPES  D R EY1 P S
+DRAPING  D R EY1 - P IH0 NG
+DRAPKIN  D R AE1 P - K IH0 N
+DRASNER  D R AE1 S - N ER0
+DRASTIC  D R AE1 - S T IH0 K
+DRASTICALLY  D R AE1 - S T IH0 K - L IY0
+DRAUGHN  D R AO1 N
+DRAUGHON  D R AO1 - AH0 N
+DRAUGHT  D R AE1 F T
+DRAUGHTS  D R AE1 F T S
+DRAUS  D R AO1 Z
+DRAVECKY  D R AH0 - V EH1 - K IY0
+DRAVES  D R EY1 V Z
+DRAVIS  D R AE1 - V IH0 S
+DRAVO  D R AE1 - V OW0
+DRAVO'S  D R AE1 - V OW0 Z
+DRAW  D R AO1
+DRAWBACK  D R AO1 - B AE2 K
+DRAWBACKS  D R AO1 - B AE2 K S
+DRAWBAUGH  D R AO1 - B AO2
+DRAWBRIDGE  D R AO1 - B R IH2 JH
+DRAWDOWN  D R AO1 - D AW2 N
+DRAWDOWNS  D R AO1 - D AW2 N Z
+DRAWDY  D R AO1 - D IY0
+DRAWER  D R AO1 R
+DRAWERS  D R AO1 R Z
+DRAWING  D R AO1 - IH0 NG
+DRAWINGS  D R AO1 - IH0 NG Z
+DRAWL  D R AO1 L
+DRAWLED  D R AO1 L D
+DRAWLS  D R AO1 L Z
+DRAWN  D R AO1 N
+DRAWS  D R AO1 Z
+DRAY  D R EY1
+DRAYER  D R EY1 - ER0
+DRAYTON  D R EY1 - T AH0 N
+DRAYTON'S  D R EY1 - T AH0 N Z
+DREAD  D R EH1 D
+DREADED  D R EH1 - D IH0 D
+DREADFUL  D R EH1 D - F AH0 L
+DREADFULLY  D R EH1 D - F AH0 - L IY0
+DREADING  D R EH1 - D IH0 NG
+DREADNOUGHT  D R EH1 D - N AO2 T
+DREADS  D R EH1 D Z
+DREAM  D R IY1 M
+DREAMED  D R IY1 M D
+DREAMER  D R IY1 - M ER0
+DREAMERS  D R IY1 - M ER0 Z
+DREAMING  D R IY1 - M IH0 NG
+DREAMLAND  D R IY1 M - L AE2 N D
+DREAMLIKE  D R IY1 M - L AY2 K
+DREAMS  D R IY1 M Z
+DREAMT  D R EH1 M T
+DREAMWORKS  D R IY1 M - W ER2 K S
+DREAMWORKS'  D R IY1 M - W ER2 K S
+DREAMWORLD  D R IY1 M - W ER2 L D
+DREAMY  D R IY1 - M IY0
+DREARINESS  D R IY1 - R IY0 - N AH0 S
+DREARY  D R IH1 - R IY0
+DREBSKY  D R EH1 B S - K IY0
+DRECHSEL  D R EH1 K - S AH0 L
+DRECHSLER  D R EH1 K - S AH0 - L ER0
+DRECHSLER(2)  D R EH1 K S - L ER0
+DRED  D R EH1 D
+DREDD  D R EH1 D
+DREDGE  D R EH1 JH
+DREDGED  D R EH1 JH D
+DREDGES  D R EH1 - JH AH0 Z
+DREDGES(2)  D R EH1 - JH IH0 Z
+DREDGING  D R EH1 - JH IH0 NG
+DREES  D R IY1 Z
+DREESE  D R IY1 Z
+DREESSEN  D R IY1 - S AH0 N
+DREGER  D R EH1 - G ER0
+DREGS  D R EH1 G Z
+DREHER  D R EH1 R
+DREIBELBIS  D R AY1 - B IH0 L - B IH0 S
+DREIER  D R AY1 - ER0
+DREIGHTON  D R AY1 - T IH0 N
+DREILING  D R AY1 - L IH0 NG
+DREIS  D R IY1 Z
+DREISBACH  D R AY1 S - B AA2 K
+DREMAN  D R IY1 - M AH0 N
+DRENCH  D R EH1 N CH
+DRENCHED  D R EH1 N CH T
+DRENCHING  D R EH1 N - CH IH0 NG
+DRENNAN  D R EH1 - N AH0 N
+DRENNEN  D R EH1 - N AH0 N
+DRENNING  D R EH1 - N IH0 NG
+DRENNON  D R EH1 - N AH0 N
+DRENTH  D R EH1 N TH
+DREPUNG  D R EY1 - P AH2 NG
+DREPUNG(2)  D R EY2 - P AO1 NG
+DRESBACH  D R EH1 S - B AA2 K
+DRESCH  D R EH1 SH
+DRESCHER  D R EH1 - SH ER0
+DRESDEN  D R EH1 Z - D IH0 N
+DRESDNER  D R EH1 Z D - N ER0
+DRESDNER'S  D R EH1 Z D - N ER0 Z
+DRESEN  D R IY1 - Z AH0 N
+DRESHER  D R EH1 - SH ER0
+DRESNER  D R EH1 Z - N ER0
+DRESS  D R EH1 S
+DRESSAGE  D R EH0 - S AA1 ZH
+DRESSED  D R EH1 S T
+DRESSEL  D R EH1 - S AH0 L
+DRESSEN  D R EH1 - S AH0 N
+DRESSER  D R EH1 - S ER0
+DRESSER'S  D R EH1 - S ER0 Z
+DRESSERS  D R EH1 - S ER0 Z
+DRESSES  D R EH1 - S AH0 Z
+DRESSES(2)  D R EH1 - S IH0 Z
+DRESSIER  D R EH1 - S IY0 - ER0
+DRESSING  D R EH1 - S IH0 NG
+DRESSINGS  D R EH1 - S IH0 NG Z
+DRESSLER  D R EH1 S - L ER0
+DRESSMAKER  D R EH1 S - M EY2 - K ER0
+DRESSMAKERS  D R EH1 S - M EY2 - K ER0 Z
+DRESSMAKING  D R EH1 S - M EY2 - K IH0 NG
+DRESSY  D R EH1 - S IY0
+DREW  D R UW1
+DREWERY  D R UW1 - ER0 - IY0
+DREWES  D R UW1 Z
+DREWETT  D R UW1 - IH0 T
+DREWRY  D R UW1 - R IY0
+DREWS  D R UW1 Z
+DREXEL  D R EH1 K - S AH0 L
+DREXEL'S  D R EH1 K - S AH0 L Z
+DREXLER  D R EH1 K S - L ER0
+DREY  D R EY1
+DREYER  D R EY1 - ER0
+DREYFUS  D R AY1 - F AH0 S
+DREYFUS'S  D R EY1 - F AH0 - S IH0 Z
+DREYFUS(2)  D R EY1 - F AH0 S
+DREYFUSS  D R EY1 - F AH0 S
+DRIBBED  D R IH1 B D
+DRIBBLE  D R IH1 - B AH0 L
+DRIBBLED  D R IH1 - B AH0 L D
+DRIBBLING  D R IH1 - B AH0 L - IH0 NG
+DRIBBLING(2)  D R IH1 - B L IH0 NG
+DRIBS  D R IH1 B Z
+DRIED  D R AY1 D
+DRIEHAUS  D R IY1 - HH AW2 S
+DRIER  D R AY1 - ER0
+DRIES  D R AY1 Z
+DRIESSEN  D R IY1 - S AH0 N
+DRIEST  D R AY1 - AH0 S T
+DRIEVER  D R IY1 - V ER0
+DRIFT  D R IH1 F T
+DRIFTED  D R IH1 F - T AH0 D
+DRIFTED(2)  D R IH1 F - T IH0 D
+DRIFTER  D R IH1 F - T ER0
+DRIFTERS  D R IH1 F - T ER0 Z
+DRIFTING  D R IH1 F - T IH0 NG
+DRIFTNET  D R IH1 F T - N EH2 T
+DRIFTS  D R IH1 F T S
+DRIFTWOOD  D R IH1 F T - W UH2 D
+DRIGGERS  D R IH1 - G ER0 Z
+DRIGGS  D R IH1 G Z
+DRILL  D R IH1 L
+DRILLBIT  D R IH1 L - B IH2 T
+DRILLED  D R IH1 L D
+DRILLER  D R IH1 - L ER0
+DRILLERS  D R IH1 - L ER0 Z
+DRILLING  D R IH1 - L IH0 NG
+DRILLING'S  D R IH1 - L IH0 NG Z
+DRILLS  D R IH1 L Z
+DRINA  D IY1 - N AH0
+DRINA'S  D IY1 - N AH0 Z
+DRINAS  D IY1 - N AH0 Z
+DRING  D R IH1 NG
+DRINK  D R IH1 NG K
+DRINKABLE  D R IH1 N - K AH0 - B AH0 L
+DRINKARD  D R IH1 NG - K ER0 D
+DRINKER  D R IH1 NG - K ER0
+DRINKER'S  D R IH1 NG - K ER0 Z
+DRINKERS  D R IH1 NG - K ER0 Z
+DRINKING  D R IH1 NG - K IH0 NG
+DRINKS  D R IH1 NG K S
+DRINKWATER  D R IH1 NG - K W AO2 - T ER0
+DRINKWINE  D R IH1 NG - K W AY2 N
+DRINNON  D R IH1 - N AH0 N
+DRIP  D R IH1 P
+DRIPPED  D R IH1 P T
+DRIPPING  D R IH1 - P IH0 NG
+DRIPPS  D R IH1 P S
+DRIPS  D R IH1 P S
+DRISCOLL  D R IH1 S - K AH0 L
+DRISKELL  D R IH1 S - K AH0 L
+DRISKILL  D R IH1 - S K IH0 L
+DRIVABLE  D R AY1 - V AH0 - B AH0 L
+DRIVE  D R AY1 V
+DRIVE'S  D R AY1 V Z
+DRIVEL  D R IH1 - V AH0 L
+DRIVEN  D R IH1 - V AH0 N
+DRIVER  D R AY1 - V ER0
+DRIVER'S  D R AY1 - V ER0 Z
+DRIVERLESS  D R AY1 - V ER0 - L IH0 S
+DRIVERS  D R AY1 - V ER0 Z
+DRIVERS'  D R AY1 - V ER0 Z
+DRIVES  D R AY1 V Z
+DRIVEWAY  D R AY1 V - W EY2
+DRIVEWAYS  D R AY1 V - W EY2 Z
+DRIVING  D R AY1 - V IH0 NG
+DRIZZLE  D R IH1 - Z AH0 L
+DRIZZLING  D R IH1 - Z AH0 L - IH0 NG
+DRIZZLING(2)  D R IH1 Z - L IH0 NG
+DRIZZLY  D R IH1 Z - L IY0
+DROBKOV  D R AO1 B - K AO0 V
+DROBKOV(2)  D R AO1 B - K AO0 F
+DROBNY  D R AA1 B - N IY0
+DRODDY  D R AA1 - D IY0
+DROEGE  D R OW1 JH
+DROESSLER  D R OW1 - S AH0 - L ER0
+DROESSLER(2)  D R OW1 S - L ER0
+DROGE  D R OW1 JH
+DROGOUL  D R OW0 - G UW1 L
+DROGOUL'S  D R OW0 - G UW1 L Z
+DROGUE  D R OW1 G
+DROHAN  D R OW1 - AH0 N
+DROKE  D R OW1 K
+DROLET  D R OW1 - L IH0 T
+DROLL  D R OW1 L
+DROLLINGER  D R OW1 - L IH0 - NG ER0
+DROMEDARY  D R AA1 - M AH0 - D EH2 - R IY0
+DROMER  D R OW1 - M ER0
+DROMEY  D R OW1 - M IY0
+DROMGOOLE  D R AA1 M - G UW2 L
+DROMGOOLES  D R AA0 M - G UW1 L Z
+DROMI  D R AA1 - M IY0
+DROMOMANIA  D R OW2 - M OW0 - M EY1 - N IY0 - AH0
+DROMOMANIA(2)  D R OW2 - M OW0 - M EY1 - N Y AH0
+DROMON  D R OW1 - M AH0 N
+DRONE  D R OW1 N
+DRONED  D R OW1 N D
+DRONES  D R OW1 N Z
+DRONET  D R OW1 - N IH0 T
+DRONEY  D R OW1 - N IY0
+DRONING  D R OW1 - N IH0 NG
+DROOL  D R UW1 L
+DROOLING  D R UW1 - L IH0 NG
+DROOP  D R UW1 P
+DROOPED  D R UW1 P T
+DROOPING  D R UW1 - P IH0 NG
+DROOPY  D R UW1 - P IY0
+DROP  D R AA1 P
+DROP(2)  D R AO1 P
+DROPKIN  D R AA1 P - K IH0 N
+DROPLET  D R AA1 - P L AH0 T
+DROPLETS  D R AA1 - P L AH0 T S
+DROPOFF  D R AA1 - P AO2 F
+DROPOUT  D R AA1 P - AW2 T
+DROPOUTS  D R AA1 P - AW2 T S
+DROPPED  D R AA1 P T
+DROPPER  D R AA1 - P ER0
+DROPPERS  D R AA1 - P ER0 Z
+DROPPING  D R AA1 - P IH0 NG
+DROPPINGS  D R AA1 - P IH0 NG Z
+DROPS  D R AA1 P S
+DROPSY  D R AA1 P - S IY0
+DROSER  D R OW1 - Z ER0
+DROSS  D R AO1 S
+DROST  D R AA1 S T
+DROSTE  D R OW1 S T
+DROTAR  D R OW1 - T ER0
+DROUGHT  D R AW1 T
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+DUNKIN'  D AH1 NG - K IH0 N
+DUNKIRK  D AH1 N - K ER0 K
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+DUNNAVANT  D AH1 - N AH0 - V AH0 N T
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+DUNNED  D AH1 N D
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+EMERYVILLE  EH1 - M ER0 - IY0 - V IH2 L
+EMETIC  IH0 - M EH1 - T IH0 K
+EMFINGER  EH1 M - F IH0 - NG ER0
+EMGE  EH1 M JH
+EMHART  EH1 M - HH AA2 R T
+EMICK  EH1 - M IH0 K
+EMIG  EH1 - M IH0 G
+EMIGH  EH1 - M AY0
+EMIGRANT  EH1 - M AH0 - G R AH0 N T
+EMIGRANTS  EH1 - M AH0 - G R AH0 N T S
+EMIGRATE  EH1 - M AH0 - G R EY2 T
+EMIGRATED  EH1 - M AH0 - G R EY2 - T IH0 D
+EMIGRATES  EH1 - M AH0 - G R EY2 T S
+EMIGRATING  EH1 - M AH0 - G R EY2 - T IH0 NG
+EMIGRATION  EH2 - M AH0 - G R EY1 - SH AH0 N
+EMIGRATIONS  EH2 - M AH0 - G R EY1 - SH AH0 N Z
+EMIGRE  EH1 - M AH0 - G R EY2
+EMIGRES  EH1 - M AH0 - G R EY2 Z
+EMIL  EH0 - M IY1 L
+EMILE  EY0 - M IY1 L
+EMILIA  AH0 - M IY1 - L IY0 - AH0
+EMILIE  EH1 - M AH0 - L IY0
+EMILIO  AH0 - M IY1 - L IY0 - OW0
+EMILO  EH0 - M IY1 - L OW0
+EMILO'S  EH0 - M IY1 - L OW0 Z
+EMILY  EH1 - M IH0 - L IY0
+EMILY'S  EH1 - M IH0 - L IY0 Z
+EMINA  EH0 - M IY1 - N AH0
+EMINASE  EH2 - M IH0 - N AA1 - S IY0
+EMINENCE  EH1 - M AH0 - N AH0 N S
+EMINENCES  EH1 - M AH0 - N AH0 N - S IH0 Z
+EMINENT  EH1 - M AH0 - N AH0 N T
+EMINENTLY  EH1 - M AH0 - N AH0 N T - L IY0
+EMIR  IH0 - M IH1 R
+EMIR(2)  EY0 - M IH1 R
+EMIRATE  EH1 - M ER0 - AH0 T
+EMIRATE(2)  EH1 - M ER0 - EY2 T
+EMIRATES  EH1 - M ER0 - AH0 T S
+EMIRATES'  EH1 - M ER0 - AH0 T S
+EMIRATES'(2)  EH1 - M ER0 - EY2 T S
+EMIRATES(2)  EH1 - M ER0 - EY2 T S
+EMISON  EH1 - M IH0 - S AH0 N
+EMISSARIES  EH1 - M AH0 - S EH2 - R IY0 Z
+EMISSARY  EH1 - M AH0 - S EH2 - R IY0
+EMISSION  IH0 - M IH1 - SH AH0 N
+EMISSIONS  IH0 - M IH1 - SH AH0 N Z
+EMIT  IH0 - M IH1 T
+EMITS  IH0 - M IH1 T S
+EMITTED  IH0 - M IH1 - T AH0 D
+EMITTED(2)  IH0 - M IH1 - T IH0 D
+EMITTING  IH0 - M IH1 - T IH0 NG
+EMLER  EH1 M - L ER0
+EMLEY  EH1 M - L IY0
+EMLING  EH1 M - L IH0 NG
+EMLYN  IH0 M - L IH1 N
+EMLYNNE  IH0 M - L AY1 N
+EMMA  EH1 - M AH0
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+EMMANUEL  IH0 - M AE1 - N Y UW0 - AH0 L
+EMMAUS  EH1 - M AW0 S
+EMME  EH1 M
+EMMEL  EH1 - M AH0 L
+EMMELINE  EH1 - M AH0 - L AY2 N
+EMMENDORFER  EH1 - M IH0 N - D AO0 R - F ER0
+EMMER  EH1 - M ER0
+EMMERICH  EH1 - M ER0 - IH0 K
+EMMERLING  EH1 - M ER0 - L IH0 NG
+EMMERSON  EH1 - M ER0 - S AH0 N
+EMMERT  EH1 - M ER0 T
+EMMERY  EH1 - M ER0 - IY0
+EMMET  EH1 - M IH0 T
+EMMETT  EH1 - M IH0 T
+EMMI  EH1 - M IY0
+EMMICK  EH1 - M IH0 K
+EMMIE  EH1 - M IY0
+EMMINGER  EH1 - M IH0 - NG ER0
+EMMIS  EH1 - M IH0 S
+EMMIT  EH1 - M IH0 T
+EMMITT  EH1 - M IH0 T
+EMMONS  EH1 - M AH0 N Z
+EMMOTT  EH1 - M AH0 T
+EMMY  EH1 - M IY0
+EMMY'S  EH1 - M IY0 Z
+EMMYS  EH1 - M IY0 Z
+EMOGENE  EH1 - M AH0 - G IY0 N
+EMOND  EH1 - M AH0 N D
+EMORY  EH1 - M ER0 - IY0
+EMORY'S  EH1 - M ER0 - IY0 Z
+EMOTION  IH0 - M OW1 - SH AH0 N
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+EMOTIONAL  IH0 - M OW1 - SH AH0 - N AH0 L
+EMOTIONAL(2)  IY1 - M OW0 - SH AH0 - N AH0 L
+EMOTIONALISM  IH0 - M OW1 - SH AH0 N - AH0 - L IH2 - Z AH0 M
+EMOTIONALISM(2)  IY1 - M OW0 - SH AH0 N - AH0 - L IH2 - Z AH0 M
+EMOTIONALLY  IH0 - M OW1 SH - N AH0 - L IY0
+EMOTIONALLY(2)  IY1 - M OW0 SH - N AH0 - L IY0
+EMOTIONS  IH0 - M OW1 - SH AH0 N Z
+EMOTIONS(2)  IY1 - M OW0 - SH AH0 N Z
+EMPANEL  IH0 M - P AE1 - N AH0 L
+EMPANELED  IH0 M - P AE1 - N AH0 L D
+EMPANELING  EH0 M - P AE1 - N AH0 - L IH0 NG
+EMPANELING(2)  EH0 M - P AE1 N - L IH0 NG
+EMPATH  EH1 M - P AE2 TH
+EMPATHETIC  EH2 M - P AH0 - TH EH1 - T IH0 K
+EMPATHIZE  EH1 M - P AH0 - TH AY2 Z
+EMPATHY  EH1 M - P AH0 - TH IY0
+EMPEROR  EH1 M - P ER0 - ER0
+EMPEROR'S  EH1 M - P ER0 - ER0 Z
+EMPERORS  EH1 M - P ER0 - ER0 Z
+EMPEY  EH1 M - P IY0
+EMPHASES  EH1 M - F AH0 - S IY2 Z
+EMPHASIS  EH1 M - F AH0 - S AH0 S
+EMPHASIS(2)  EH1 M - F AH0 - S IH0 S
+EMPHASIZE  EH1 M - F AH0 - S AY2 Z
+EMPHASIZED  EH1 M - F AH0 - S AY2 Z D
+EMPHASIZES  EH1 M - F AH0 - S AY2 - Z AH0 Z
+EMPHASIZES(2)  EH1 M - F AH0 - S AY2 - Z IH0 Z
+EMPHASIZING  EH1 M - F AH0 - S AY2 - Z IH0 NG
+EMPHATIC  EH0 M - F AE1 - T IH0 K
+EMPHATICALLY  EH0 M - F AE1 - T IH0 K - L IY0
+EMPHATICALLY(2)  EH0 M - F AE1 - T IH0 - K AH0 - L IY0
+EMPHYSEMA  EH2 M - F AH0 - Z IY1 - M AH0
+EMPIE  EH1 M - P IY0
+EMPIRE  EH1 M - P AY0 - ER0
+EMPIRE'S  EH1 M - P AY0 - ER0 Z
+EMPIRES  EH1 M - P AY0 - ER0 Z
+EMPIRICAL  EH2 M - P IH1 - R IH0 - K AH0 L
+EMPIRICALLY  EH0 M - P IH1 - R IH0 - K AH0 - L IY0
+EMPIRICALLY(2)  EH0 M - P IH1 - R IH0 K - L IY0
+EMPIRICISM  EH0 M - P IH1 - R AH0 - S IH2 - Z AH0 M
+EMPIRICIST  IH0 M - P IH1 - R AH0 - S AH0 S T
+EMPLACEMENT  IH0 M - P L EY1 S - M AH0 N T
+EMPLACEMENTS  IH0 M - P L EY1 S - M AH0 N T S
+EMPLOY  EH0 M - P L OY1
+EMPLOY(2)  IH0 M - P L OY1
+EMPLOYABLE  EH0 M - P L OY1 - AH0 - B AH0 L
+EMPLOYED  EH0 M - P L OY1 D
+EMPLOYED(2)  IH0 M - P L OY1 D
+EMPLOYEE  EH0 M - P L OY1 - IY0
+EMPLOYEE'S  EH0 M - P L OY1 - IY0 Z
+EMPLOYEE'S(2)  IH0 M - P L OY1 - IY0 Z
+EMPLOYEE(2)  IH0 M - P L OY1 - IY0
+EMPLOYEES  EH0 M - P L OY1 - IY0 Z
+EMPLOYEES'  EH0 M - P L OY1 - IY0 Z
+EMPLOYEES(2)  IH0 M - P L OY1 - IY0 Z
+EMPLOYER  EH0 M - P L OY1 - ER0
+EMPLOYER'S  EH0 M - P L OY1 - ER0 Z
+EMPLOYER'S(2)  IH0 M - P L OY1 - ER0 Z
+EMPLOYER(2)  IH0 M - P L OY1 - ER0
+EMPLOYERS  EH0 M - P L OY1 - ER0 Z
+EMPLOYERS'  EH0 M - P L OY1 - ER0 Z
+EMPLOYERS'(2)  IH0 M - P L OY1 - ER0 Z
+EMPLOYERS(2)  IH0 M - P L OY1 - ER0 Z
+EMPLOYING  EH0 M - P L OY1 - IH0 NG
+EMPLOYING(2)  IH0 M - P L OY1 - IH0 NG
+EMPLOYMENT  EH0 M - P L OY1 - M AH0 N T
+EMPLOYMENT(2)  IH0 M - P L OY1 - M AH0 N T
+EMPLOYMENTS  EH0 M - P L OY1 - M AH0 N T S
+EMPLOYMENTS(2)  IH0 M - P L OY1 - M AH0 N T S
+EMPLOYS  EH0 M - P L OY1 Z
+EMPLOYS(2)  IH0 M - P L OY1 Z
+EMPORIA  EH0 M - P AO1 - R IY0 - AH0
+EMPORIUM  EH2 M - P AO1 - R IY0 - AH0 M
+EMPOWER  IH0 M - P AW1 - ER0
+EMPOWERED  IH0 M - P AW1 - ER0 D
+EMPOWERING  IH0 M - P AW1 - ER0 - IH0 NG
+EMPOWERMENT  IH0 M - P AW1 - ER0 - M AH0 N T
+EMPOWERS  IH0 M - P AW1 - ER0 Z
+EMPRESA  EH0 M - P R EH1 - S AH0
+EMPRESAS  EH0 M - P R EH1 - S AH0 Z
+EMPRESS  EH1 M - P R EH0 S
+EMPRISE  EH0 M - P R AY1 Z
+EMPSON  EH1 M P - S AH0 N
+EMPT  EH1 M P T
+EMPT(2)  EH1 M T
+EMPTED  EH1 M P - T IH0 D
+EMPTED(2)  EH1 M - T IH0 D
+EMPTIED  EH1 M P - T IY0 D
+EMPTIED(2)  EH1 M - T IY0 D
+EMPTIER  EH1 M P - T IY0 - ER0
+EMPTIER(2)  EH1 M - T IY0 - ER0
+EMPTIES  EH1 M P - T IY0 Z
+EMPTIES(2)  EH1 M - T IY0 Z
+EMPTINESS  EH1 M P - T IY0 - N AH0 S
+EMPTINESS(2)  EH1 M - T IY0 - N AH0 S
+EMPTING  EH1 M P - T IH0 NG
+EMPTING(2)  EH1 M - T IH0 NG
+EMPTION  EH1 M P - SH AH0 N
+EMPTIVE  EH1 M P - T IH0 V
+EMPTOR  EH1 M P - T ER0
+EMPTS  EH1 M P T S
+EMPTY  EH1 M P - T IY0
+EMPTY(2)  EH1 M - T IY0
+EMPTYING  EH1 M P - T IY0 - IH0 NG
+EMPTYING(2)  EH1 M - T IY0 - IH0 NG
+EMRICH  EH1 M - R IH0 K
+EMRICK  EH1 M - R IH0 K
+EMRY  EH1 M - R IY0
+EMSLIE  EH1 M - S AH0 - L IY0
+EMSWILER  EH1 M Z - W AY2 - L ER0
+EMU  IY1 - M Y UW2
+EMUIL  EH1 - M Y UW0 - IH2 L
+EMUIL'S  EH1 - M Y UW0 - IH2 L Z
+EMULATE  EH1 - M Y AH0 - L EY2 T
+EMULATED  EH1 - M Y AH0 - L EY2 - T IH0 D
+EMULATING  EH1 - M Y AH0 - L EY2 - T IH0 NG
+EMULATION  EH2 - M Y AH0 - L EY1 - SH AH0 N
+EMULEX  EH1 - M Y UW0 - L AH0 K S
+EMULSIFIER  IH0 - M AH1 L - S AH0 - F AY2 - ER0
+EMULSION  IH0 - M AH1 L - SH AH0 N
+EN  EH1 N
+ENA  EH1 - N AH0
+ENABLE  EH0 - N EY1 - B AH0 L
+ENABLE(2)  IH0 N - EY1 - B AH0 L
+ENABLED  EH0 - N EY1 - B AH0 L D
+ENABLED(2)  IH0 N - EY1 - B AH0 L D
+ENABLER  EH0 - N EY1 - B AH0 L - ER0
+ENABLER(2)  EH0 - N EY1 - B L ER0
+ENABLER(3)  IH0 N - EY1 - B L ER0
+ENABLER(4)  IH0 N - EY1 - B AH0 L - ER0
+ENABLES  EH0 - N EY1 - B AH0 L Z
+ENABLES(2)  IH0 N - EY1 - B AH0 L Z
+ENABLING  EH0 - N EY1 - B AH0 L - IH0 NG
+ENABLING(2)  IH0 N - EY1 - B AH0 L - IH0 NG
+ENABLING(3)  IH0 N - EY1 - B L IH0 NG
+ENACT  IH0 - N AE1 K T
+ENACTED  EH0 - N AE1 K - T AH0 D
+ENACTING  EH0 - N AE1 K - T IH0 NG
+ENACTMENT  EH0 - N AE1 K T - M AH0 N T
+ENACTMENT(2)  EH0 - N AE1 K - M AH0 N T
+ENACTMENTS  EH2 - N AE1 K T - M AH0 N T S
+ENACTMENTS(2)  EH2 - N AE1 K - M AH0 N T S
+ENACTMENTS(3)  EH2 - N AE1 K - M AH0 N S
+ENACTS  IH2 - N AE1 K T S
+ENAMEL  IH0 - N AE1 - M AH0 L
+ENAMELED  IH0 - N AE1 - M AH0 L D
+ENAMELS  IH0 - N AE1 - M AH0 L Z
+ENAMOR  EH0 - N AE1 - M ER0
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+ENASA  EY0 - N AA1 - S AH0
+ENBERG  EH1 N - B ER0 G
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+ENCAMPED  IH0 N - K AE1 M P T
+ENCAMPMENT  IH0 N - K AE1 M P - M IH0 N T
+ENCAMPMENTS  IH0 N - K AE1 M P - M IH0 N T S
+ENCAPSULATE  EH0 N - K AE1 P - S AH0 - L EY2 T
+ENCAPSULATED  EH0 N - K AE1 P - S AH0 - L EY2 - T IH0 D
+ENCAPSULATING  EH0 N - K AE1 P - S AH0 - L EY2 - T IH0 NG
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+ENCEPHALOPATHY  EH0 N - S EH2 - F AH0 - L AO1 - P AH0 - TH IY0
+ENCHANT  EH0 N - CH AE1 N T
+ENCHANTED  EH0 N - CH AE1 N - T IH0 D
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+ENCISO  IH0 N - S IY1 - S OW0
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+ENCLOSING  EH0 N - K L OW1 - Z IH0 NG
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+ENCLOSURES  IH0 N - K L OW1 - ZH ER0 Z
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+ENCODING  EH0 N - K OW1 - D IH0 NG
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+ENCOMPASSED  EH0 N - K AH1 M - P AH0 S T
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+ENCOR  EH1 N - K AO2 R
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+ENCOUNTERED  IH0 N - K AW1 N - T ER0 D
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+ENCOUNTERS(2)  IH0 N - K AW1 - N ER0 Z
+ENCOURAGE  EH0 N - K ER1 - IH0 JH
+ENCOURAGE(2)  IH0 N - K ER1 - AH0 JH
+ENCOURAGED  EH0 N - K ER1 - IH0 JH D
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+ENCOURAGEMENT  EH0 N - K ER1 - IH0 JH - M AH0 N T
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+ENCOURAGING  EH0 N - K ER1 - IH0 - JH IH0 NG
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+ENCROACH  IH0 N - K R OW1 CH
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+ENCROACHES  IH0 N - K R OW1 - CH IH0 Z
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+ENCRUST  EH0 N - K R AH1 S T
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+ENCRUSTING  EH0 N - K R AH1 - S T IH0 NG
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+ENCRYPTED  EH0 N - K R IH1 P - T IH0 D
+ENCRYPTED(2)  IH0 N - K R IH1 P - T IH0 D
+ENCRYPTION  EH0 N - K R IH1 P - SH AH0 N
+ENCUMBER  EH0 N - K AH1 M - B ER0
+ENCUMBERED  EH0 N - K AH1 M - B ER0 D
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+ENCYCLOPEDIA  IH0 N - S AY2 - K L AH0 - P IY1 - D IY0 - AH0
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+END  EH1 N D
+ENDAKA  EH0 N - D AA1 - K AH0
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+ENDANGERMENT  EH0 N - D EY1 N - JH ER0 - M AH0 N T
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+ENDE  EH1 N D
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+ENDEAVOR  IH0 N - D EH1 - V ER0
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+ENDEAVORED  IH0 N - D EH1 - V ER0 D
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+ENDEAVORS  IH0 N - D EH1 - V ER0 Z
+ENDEAVOUR  IH0 N - D EH1 - V ER0
+ENDEAVOUR'S  IH0 N - D EH1 - V ER0 Z
+ENDED  EH1 N - D AH0 D
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+ENDERLE  EH1 N - D ER0 - AH0 L
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+ENDEVCO  EH0 N - D EH1 V - K OW0
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+ENDGAMES  EH1 N D - G EY0 M Z
+ENDICOTT  EH1 N - D IH0 - K AA2 T
+ENDING  EH1 N - D IH0 NG
+ENDINGS  EH1 N - D IH0 NG Z
+ENDIVE  EH1 N - D IH0 V
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+ENTERPRISE'S(2)  EH1 N - T ER0 - P R AY2 - Z IH0 Z
+ENTERPRISE'S(3)  EH1 - N ER0 - P R AY2 - Z AH0 Z
+ENTERPRISE'S(4)  EH1 - N ER0 - P R AY2 - Z IH0 Z
+ENTERPRISE(2)  EH1 - N ER0 - P R AY2 Z
+ENTERPRISES  EH1 N - T ER0 - P R AY2 - Z IH0 Z
+ENTERPRISES'  EH1 N - T ER0 - P R AY2 - Z IH0 Z
+ENTERPRISES'(2)  EH1 - N ER0 - P R AY2 - Z IH0 Z
+ENTERPRISES(2)  EH1 - N ER0 - P R AY2 - Z IH0 Z
+ENTERPRISING  EH1 N - T ER0 - P R AY2 - Z IH0 NG
+ENTERPRISING(2)  EH1 - N ER0 - P R AY2 - Z IH0 NG
+ENTERRA  EH0 N - T EH1 - R AH0
+ENTERS  EH1 N - T ER0 Z
+ENTERS(2)  EH1 - N ER0 Z
+ENTERTAIN  EH2 N - T ER0 - T EY1 N
+ENTERTAIN(2)  EH2 - N ER0 - T EY1 N
+ENTERTAINED  EH2 N - T ER0 - T EY1 N D
+ENTERTAINED(2)  EH2 - N ER0 - T EY1 N D
+ENTERTAINER  EH2 N - T ER0 - T EY1 - N ER0
+ENTERTAINER'S  EH2 N - T ER0 - T EY1 - N ER0 Z
+ENTERTAINER'S(2)  EH2 - N ER0 - T EY1 - N ER0 Z
+ENTERTAINER(2)  EH2 - N ER0 - T EY1 - N ER0
+ENTERTAINERS  EH2 N - T ER0 - T EY1 - N ER0 Z
+ENTERTAINERS(2)  EH2 - N ER0 - T EY1 - N ER0 Z
+ENTERTAINING  EH2 N - T ER0 - T EY1 - N IH0 NG
+ENTERTAINING(2)  EH2 - N ER0 - T EY1 - N IH0 NG
+ENTERTAINMENT  EH2 N - T ER0 - T EY1 N - M AH0 N T
+ENTERTAINMENT'S  EH2 N - T ER0 - T EY1 N - M AH0 N T S
+ENTERTAINMENT'S(2)  EH2 - N ER0 - T EY1 N - M AH0 N T S
+ENTERTAINMENT(2)  EH2 - N ER0 - T EY1 N - M AH0 N T
+ENTERTAINMENTS  EH2 N - T ER0 - T EY1 N - M AH0 N T S
+ENTERTAINMENTS(2)  EH2 - N ER0 - T EY1 N - M AH0 N T S
+ENTERTAINS  EH2 N - T ER0 - T EY1 N Z
+ENTERTAINS(2)  EH2 - N ER0 - T EY1 N Z
+ENTEX  EH1 N - T EH2 K S
+ENTHRAL  EH0 N - TH R AO1 L
+ENTHRALLED  EH0 N - TH R AO1 L D
+ENTHUSE  IH0 N - TH UW1 Z
+ENTHUSED  IH0 N - TH UW1 Z D
+ENTHUSIASM  IH0 N - TH UW1 - Z IY0 - AE2 - Z AH0 M
+ENTHUSIASMS  IH0 N - TH UW1 - Z IY0 - AE2 - Z AH0 M Z
+ENTHUSIAST  EH0 N - TH UW1 - Z IY0 - AE2 S T
+ENTHUSIASTIC  IH0 N - TH UW2 - Z IY0 - AE1 - S T IH0 K
+ENTHUSIASTICALLY  IH0 N - TH UW2 - Z IY0 - AE1 - S T IH0 K - L IY0
+ENTHUSIASTS  EH0 N - TH UW1 - Z IY0 - AE2 S T S
+ENTHUSIASTS(2)  EH0 N - TH UW1 - Z IY0 - AE2 S S
+ENTHUSIASTS(3)  EH0 N - TH UW1 - Z IY0 - AE2 S
+ENTICE  IH0 N - T AY1 S
+ENTICED  IH0 N - T AY1 S T
+ENTICEMENT  IH0 N - T AY1 S - M AH0 N T
+ENTICEMENTS  IH0 N - T AY1 S - M AH0 N T S
+ENTICING  EH0 N - T AY1 - S IH0 NG
+ENTIN  EH1 N - T IH0 N
+ENTIRE  IH0 N - T AY1 - ER0
+ENTIRELY  IH0 N - T AY1 - ER0 - L IY0
+ENTIRETY  IH0 N - T AY1 - ER0 - T IY0
+ENTITIES  EH1 N - T IH0 - T IY0 Z
+ENTITIES'  EH1 N - T IH0 - T IY0 Z
+ENTITLE  EH0 N - T AY1 - T AH0 L
+ENTITLE(2)  IH0 N - T AY1 - T AH0 L
+ENTITLED  EH0 N - T AY1 - T AH0 L D
+ENTITLEMENT  EH0 N - T AY1 - T AH0 L - M AH0 N T
+ENTITLEMENTS  EH0 N - T AY1 - T AH0 L - M AH0 N T S
+ENTITLES  EH0 N - T AY1 - T AH0 L Z
+ENTITLING  EH0 N - T AY1 - T AH0 L - IH0 NG
+ENTITLING(2)  EH0 N - T AY1 T - L IH0 NG
+ENTITY  EH1 N - T AH0 - T IY0
+ENTITY'S  EH1 N - T AH0 - T IY0 Z
+ENTITY(2)  EH1 N - T IH0 - T IY0
+ENTLER  EH1 N T - L ER0
+ENTOFFEN  EH1 N - T AH0 - F AH0 N
+ENTOFFEN'S  EH1 N - T AH0 - F AH0 N Z
+ENTOMB  EH0 N - T UW1 M
+ENTOMBED  EH0 N - T UW1 M D
+ENTOMBMENT  IH0 N - T UW1 M - M AH0 N T
+ENTOMOLOGIST  EH2 N - T AH0 - M AA1 - L AH0 - JH AH0 S T
+ENTOMOLOGISTS  EH2 N - T AH0 - M AA1 - L AH0 - JH AH0 S T S
+ENTOMOLOGISTS(2)  EH2 N - T AH0 - M AA1 - L AH0 - JH AH0 S S
+ENTOMOLOGISTS(3)  EH2 N - T AH0 - M AA1 - L AH0 - JH AH0 S
+ENTOMOLOGY  EH2 N - T AH0 - M AA1 - L AH0 - JH IY0
+ENTOURAGE  AA2 N - T UH0 - R AA1 ZH
+ENTOURAGE(2)  AA2 N - T ER0 - AA1 ZH
+ENTRAIL  EH1 N - T R AH0 L
+ENTRAILS  EH1 N - T R AH0 L Z
+ENTRANCE  EH1 N - T R AH0 N S
+ENTRANCED  IH0 N - T R AE1 N S T
+ENTRANCES  EH1 N - T R AH0 N - S AH0 Z
+ENTRANT  EH1 N - T R AH0 N T
+ENTRANTS  EH1 N - T R AH0 N T S
+ENTRAP  IH0 N - T R AE1 P
+ENTRAPMENT  IH0 N - T R AE1 P - M AH0 N T
+ENTRAPPED  IH0 N - T R AE1 P T
+ENTRE  AA1 N - T R EY0
+ENTRE(2)  AA1 N - T R AH0
+ENTREATIES  EH0 N - T R IY1 - T IY0 Z
+ENTREATY  EH0 N - T R IY1 - T IY0
+ENTREE  AA1 N - T R EY2
+ENTREES  AA1 N - T R EY2 Z
+ENTREGROWTH  EH1 N - T R AH0 - G R OW0 TH
+ENTREKIN  EH1 N - T R IH0 - K IH0 N
+ENTRENCH  EH0 N - T R EH1 N CH
+ENTRENCHED  EH0 N - T R EH1 N CH T
+ENTRENCHED(2)  IH0 N - T R EH1 N CH T
+ENTRENCHES  EH0 N - T R EH1 N - CH IH0 Z
+ENTRENCHING  EH0 N - T R EH1 N - CH IH0 NG
+ENTRENCHMENT  EH0 N - T R EH1 N CH - M AH0 N T
+ENTREPRENEUR  AA2 N - T R AH0 - P R AH0 - N ER1
+ENTREPRENEUR'S  AA2 N - T R AH0 - P R AH0 - N ER1 Z
+ENTREPRENEUR(2)  AA2 N - T R AH0 - P R AH0 - N UH1 R
+ENTREPRENEURIAL  AA2 N - T R AH0 - P R AH0 - N ER1 - IY0 - AH0 L
+ENTREPRENEURIALISM  EH2 N - T R AH0 - P R AH0 - N UW2 - R IY1 - AH0 - L IH2 - Z AH0 M
+ENTREPRENEURS  AA2 N - T R AH0 - P R AH0 - N ER1 Z
+ENTREPRENEURSHIP  AA2 N - T R AH0 - P R AH0 - N ER1 - SH IH0 P
+ENTRIES  EH1 N - T R IY0 Z
+ENTRIKIN  EH1 N - T R IH0 - K IH0 N
+ENTRINGER  EH1 N - T ER0 - IH0 - NG ER0
+ENTROPY  EH1 N - T R AH0 - P IY0
+ENTRUST  EH0 N - T R AH1 S T
+ENTRUSTED  EH0 N - T R AH1 - S T IH0 D
+ENTRUSTING  EH0 N - T R AH1 - S T IH0 NG
+ENTRY  EH1 N - T R IY0
+ENTRYWAY  EH1 N - T R IY0 - W EY0
+ENTSMINGER  EH1 N T - S AH0 - M IH0 - NG ER0
+ENTWINE  EH0 N - T W AY1 N
+ENTWINED  EH0 N - T W AY1 N D
+ENTWISLE  EH1 N - T W AY0 - AH0 L
+ENTWISTLE  IH0 N T - W IH1 - S AH0 L
+ENTZ  EH1 N T S
+ENTZMINGER  EH1 N T S - M IH0 - NG ER0
+ENUMERATE  IH0 - N UW1 - M ER0 - EY2 T
+ENUMERATED  IH0 - N UW1 - M ER0 - EY2 - T IH0 D
+ENUMERATES  IH0 - N UW1 - M ER0 - EY2 T S
+ENUMERATION  IH0 - N UW2 - M ER0 - EY1 - SH AH0 N
+ENUNCIATE  IH0 - N AH1 N - S IY0 - EY2 T
+ENUNCIATE(2)  IY0 - N AH1 N - S IY0 - EY2 T
+ENUNCIATED  IH0 - N AH1 N - S IY0 - EY2 - T IH0 D
+ENUNCIATING  IH0 - N AH1 N - S IY0 - EY2 - T IH0 NG
+ENVELOP  IH0 N - V EH1 - L AH0 P
+ENVELOPE  EH1 N - V AH0 - L OW2 P
+ENVELOPED  EH0 N - V EH1 - L AH0 P T
+ENVELOPES  EH1 N - V AH0 - L OW2 P S
+ENVELOPING  IH0 N - V EH1 - L AH0 - P IH0 NG
+ENVELOPS  IH0 N - V EH1 - L AH0 P S
+ENVIABLE  EH1 N - V IY0 - AH0 - B AH0 L
+ENVIED  EH1 N - V IY0 D
+ENVIOUS  EH1 N - V IY0 - AH0 S
+ENVIOUSLY  EH1 N - V IY0 - AH0 S - L IY0
+ENVIRODYNE  EH0 N - V AY1 - R OW0 - D AY2 N
+ENVIRONIC  EH2 N - V AY0 - R AO1 - N IH0 K
+ENVIRONICS  EH2 N - V AY0 - R AO1 - N IH0 K S
+ENVIRONMENT  IH0 N - V AY1 - R AH0 N - M AH0 N T
+ENVIRONMENT'S  IH0 N - V AY1 - R AH0 N - M AH0 N T S
+ENVIRONMENTAL  IH0 N - V AY2 - R AH0 N - M EH1 N - T AH0 L
+ENVIRONMENTAL(2)  IH0 N - V AY2 - R AH0 N - M EH1 - N AH0 L
+ENVIRONMENTALISM  EH0 N - V AY1 - R AH0 N - M EH2 N - T AH0 - L IH2 - Z AH0 M
+ENVIRONMENTALISM(2)  EH0 N - V AY1 - R AH0 N - M EH2 - N AH0 - L IH2 - Z AH0 M
+ENVIRONMENTALIST  IH0 N - V AY2 - R AH0 N - M EH1 N - T AH0 - L IH0 S T
+ENVIRONMENTALIST(2)  IH0 N - V AY2 - R AH0 N - M EH1 - N AH0 - L IH0 S T
+ENVIRONMENTALISTS  EH0 N - V AY1 - R AH0 N - M EH2 N - T AH0 - L IH0 S T S
+ENVIRONMENTALISTS'  IH0 N - V AY2 - R AH0 N - M EH1 N - T AH0 - L IH0 S T S
+ENVIRONMENTALISTS'(2)  EH0 N - V AY2 - R AH0 N - M EH1 - N AH0 - L IH0 S T S
+ENVIRONMENTALISTS(2)  EH0 N - V AY1 - R AH0 N - M EH2 N - T AH0 - L IH0 S S
+ENVIRONMENTALISTS(3)  EH0 N - V AY1 - R AH0 N - M EH2 - N AH0 - L IH0 S T S
+ENVIRONMENTALISTS(4)  EH0 N - V AY1 - R AH0 N - M EH2 - N AH0 - L IH0 S S
+ENVIRONMENTALISTS(5)  EH0 N - V AY1 - R AH0 N - M EH2 N - T AH0 - L IH0 S
+ENVIRONMENTALISTS(6)  EH0 N - V AY1 - R AH0 N - M EH2 - N AH0 - L IH0 S
+ENVIRONMENTALLY  IH0 N - V AY2 - R AH0 N - M EH1 N - T AH0 - L IY0
+ENVIRONMENTALLY(2)  IH0 N - V AY2 - R AH0 N - M EH1 - N AH0 - L IY0
+ENVIRONMENTS  IH0 N - V AY1 - R AH0 N - M AH0 N T S
+ENVIRONS  IH0 N - V AY1 - R AH0 N Z
+ENVIROPACT  IH0 N - V AY1 - R OW0 - P AE2 K T
+ENVIROSAFE  IH0 N - V AY1 - R OW0 - S EY2 F
+ENVIROTEST  IH2 N - V AY1 - R OW0 - T EH2 S T
+ENVISAGE  EH0 N - V IH1 - Z IH0 JH
+ENVISAGED  EH0 N - V IH1 - Z IH0 JH D
+ENVISAGES  EH0 N - V IH1 - Z IH0 - JH IH0 Z
+ENVISION  EH0 N - V IH1 - ZH AH0 N
+ENVISIONED  EH0 N - V IH1 - ZH AH0 N D
+ENVISIONING  EH0 N - V IH1 - ZH AH0 N - IH0 NG
+ENVISIONS  EH0 N - V IH1 - ZH AH0 N Z
+ENVOS  EH1 N - V OW0 S
+ENVOY  EH1 N - V OY0
+ENVOY(2)  AA1 N - V OY0
+ENVOYS  EH1 N - V OY0 Z
+ENVOYS(2)  AA1 N - V OY0 Z
+ENVY  EH1 N - V IY0
+ENWRIGHT  IH0 N W - R AY1 T
+ENYART  EH1 - N Y AA0 R T
+ENYEART  EH1 - N Y ER0 T
+ENZ  EH1 N Z
+ENZO  EH1 N - Z OW0
+ENZON  EH1 N - Z AA0 N
+ENZOR  EH1 N - Z ER0
+ENZYMATIC  EH2 N - Z AY0 - M AE1 - T IH0 K
+ENZYME  EH1 N - Z AY2 M
+ENZYMES  EH1 N - Z AY2 M Z
+EOCENE  IY1 - AH0 - S IY2 N
+EOFF  EY1 - AO0 F
+EOHIPPUS  IY2 - OW0 - HH IH1 - P AH0 S
+EOLANDE  EY2 - OW0 - L AA1 N - D IY0
+EON  IY1 - AH0 N
+EON(2)  IY1 - AA0 N
+EONS  IY1 - AH0 N Z
+EOS  IY1 - AA0 S
+EOS'S  IY1 - AA0 - S AH0 Z
+EPCOT  EH1 P - K AA0 T
+EPEDA  EH0 - P EY1 - D AH0
+EPEDA'S  EH0 - P EY1 - D AH0 Z
+EPES  IY1 P S
+EPHEDRINE  IH0 - F EH1 D - R IH0 N
+EPHEMERAL  IH0 - F EH1 - M ER0 - AH0 L
+EPHLIN  EH1 - F L IH0 N
+EPHRAIM  IY1 - F R AH0 M
+EPHRON  EH1 - F R AH0 N
+EPIC  EH1 - P IH0 K
+EPIC'S  EH1 - P IH0 K S
+EPICENTER  EH1 - P AH0 - S EH2 N - T ER0
+EPICS  EH1 - P IH0 K S
+EPICURE  EH1 - P IH0 - K Y UH2 R
+EPICUREAN  EH2 - P AH0 - K Y UH0 - R IY1 - AH0 N
+EPICUREAN(2)  EH2 - P AH0 - K Y UH1 - R IY0 - AH0 N
+EPIDEMIC  EH2 - P AH0 - D EH1 - M IH0 K
+EPIDEMIC(2)  EH2 - P IH0 - D EH1 - M IH0 K
+EPIDEMICS  EH2 - P AH0 - D EH1 - M IH0 K S
+EPIDEMIOLOGICAL  EH2 - P AH0 - D IY0 - M IY0 - AH0 - L AA1 - JH IH0 - K AH0 L
+EPIDEMIOLOGIST  EH2 - P AH0 - D IY0 - M IY0 - AA1 - L AH0 - JH IH0 S T
+EPIDEMIOLOGISTS  EH2 - P AH0 - D IY0 - M IY0 - AA1 - L AH0 - JH IH0 S T S
+EPIDEMIOLOGISTS(2)  EH2 - P AH0 - D IY0 - M IY0 - AA1 - L AH0 - JH IH0 S S
+EPIDEMIOLOGISTS(3)  EH2 - P AH0 - D IY0 - M IY0 - AA1 - L AH0 - JH IH0 S
+EPIDEMIOLOGY  EH2 - P AH0 - D EH2 - M IY0 - AA1 - L AH0 - JH IY0
+EPIDERMAL  EH2 - P AH0 - D ER1 - M AH0 L
+EPIDERMIS  EH2 - P AH0 - D ER1 - M AH0 S
+EPIDURAL  EH2 - P AH0 - D ER1 - AH0 L
+EPIGENETIC  EH2 - P AH0 - JH AH0 - N EH1 - T IH0 K
+EPIGRAM  EH1 - P AH0 - G R AE2 M
+EPIGRAPHIC  EH2 - P AH0 - G R AE1 - F IH0 K
+EPILEPSIES  EH1 - P AH0 - L EH2 P - S IY0 Z
+EPILEPSY  EH1 - P AH0 - L EH2 P - S IY0
+EPILEPTIC  EH2 - P AH0 - L EH1 P - T IH0 K
+EPILOGUE  EH1 - P AH0 - L AO2 G
+EPIPHANY  IH0 - P IH1 - F AH0 - N IY0
+EPISCOPAL  IH0 - P IH1 S - K AH0 - P AH0 L
+EPISCOPALIAN  IH0 - P IH2 S - K AH0 - P EY1 - L IY0 - AH0 N
+EPISCOPALIAN(2)  IH0 - P IH2 S - K AH0 - P EY1 - L Y AH0 N
+EPISCOPALIANS  IH0 - P IH2 S - K AH0 - P EY1 - L IY0 - AH0 N Z
+EPISCOPALIANS(2)  IH0 - P IH2 S - K AH0 - P EY1 - L Y AH0 N Z
+EPISCOPO  IH0 - P IH0 S - K OW1 - P OW0
+EPISODE  EH1 - P AH0 - S OW2 D
+EPISODE(2)  EH1 - P IH0 - S OW2 D
+EPISODES  EH1 - P AH0 - S OW2 D Z
+EPISODES(2)  EH1 - P IH0 - S OW2 D Z
+EPISODIC  EH2 - P AH0 - S AA1 - D IH0 K
+EPISTEME  EH1 - P IH0 - S T IY2 M
+EPISTEMOLOGY  IH0 - P IH2 - S T AH0 - M AA1 - L AH0 - JH IY0
+EPISTLE  IH0 - P IH1 - S AH0 L
+EPISTOLARY  IH0 - P IH1 - S T AH0 - L EH2 - R IY0
+EPITAPH  EH1 - P AH0 - T AE2 F
+EPITAPHS  EH1 - P AH0 - T AE2 F S
+EPITHELIAL  EH0 - P IH0 - TH EH1 - L Y AH0 L
+EPITHET  EH1 - P AH0 - TH EH2 T
+EPITHETS  EH1 - P AH0 - TH EH2 T S
+EPITOME  IH0 - P IH1 - T AH0 - M IY0
+EPITOMIZE  IH0 - P IH1 - T AH0 - M AY2 Z
+EPITOMIZED  IH0 - P IH1 - T AH0 - M AY2 Z D
+EPITOMIZES  IH0 - P IH1 - T AH0 - M AY2 - Z IH0 Z
+EPITOPE  EH1 - P IH0 - T OW2 P
+EPLER  EH1 P - L ER0
+EPLEY  EH1 P - L IY0
+EPLIN  EH1 P - L IH0 N
+EPLING  EH1 - P L IH0 NG
+EPOCH  EH1 - P AH0 K
+EPOCH(2)  IY1 - P AH0 K
+EPOCHAL  EH1 - P AH0 - K AH0 L
+EPOCHS  EH1 - P AH0 K S
+EPOCHS(2)  IY1 - P AH0 K S
+EPOGEN  EH1 - P AH0 - JH EH0 N
+EPOXY  IH0 - P AA1 K - S IY0
+EPP  EH1 P
+EPPARD  EH1 - P ER0 D
+EPPEL  EH1 - P AH0 L
+EPPERLY  EH1 - P ER0 - L IY0
+EPPERS  EH1 - P ER0 Z
+EPPERSON  EH1 - P ER0 - S AH0 N
+EPPES  EH1 P S
+EPPICH  EH1 - P IH0 CH
+EPPING  EH1 - P IH0 NG
+EPPINGER  EH1 - P IH0 - NG ER0
+EPPLE  EH1 - P AH0 L
+EPPLER  EH1 P - L ER0
+EPPLEY  EH1 P - L IY0
+EPPNER  EH1 P - N ER0
+EPPOLITO  EH0 - P OW0 - L IY1 - T OW0
+EPPS  EH1 P S
+EPROM  EH1 - P R AH0 M
+EPROMS  EH1 - P R AH0 M Z
+EPSCO  EH1 P - S K OW0
+EPSILON  EH1 P - S AH0 - L AA2 N
+EPSOM  EH1 P - S AH0 M
+EPSOMITE  EH1 P - S AH0 - M AY2 T
+EPSON  EH1 P - S AH0 N
+EPSTEIN  EH1 P - S T IY2 N
+EPSTEIN(2)  EH1 P - S T AY2 N
+EPTING  EH1 P - T IH0 NG
+EQUABLE  EH1 - K W AH0 - B AH0 L
+EQUAL  IY1 - K W AH0 L
+EQUALED  IY1 - K W AH0 L D
+EQUALING  IY1 - K W AH0 L - IH0 NG
+EQUALITY  IH0 - K W AA1 - L AH0 - T IY0
+EQUALIZATION  IY2 - K W AH0 - L IH0 - Z EY1 - SH AH0 N
+EQUALIZE  IY1 - K W AH0 - L AY2 Z
+EQUALIZED  IY1 - K W AH0 - L AY2 Z D
+EQUALIZER  IY1 - K W AH0 - L AY2 - Z ER0
+EQUALIZING  IY1 - K W AH0 - L AY2 - Z IH0 NG
+EQUALLY  IY1 - K W AH0 - L IY0
+EQUALS  IY1 - K W AH0 L Z
+EQUANIMITY  IY2 - K W AH0 - N IH1 - M IH0 - T IY0
+EQUATE  IH0 - K W EY1 T
+EQUATED  IH0 - K W EY1 - T IH0 D
+EQUATES  IH0 - K W EY1 T S
+EQUATING  IH0 - K W EY1 - T IH0 NG
+EQUATION  IH0 - K W EY1 - ZH AH0 N
+EQUATIONS  IH0 - K W EY1 - ZH AH0 N Z
+EQUATOR  IH0 - K W EY1 - T ER0
+EQUATORIAL  IY2 - K W AH0 - T AO1 - R IY0 - AH0 L
+EQUESTRIAN  IH0 - K W EH1 S - T R IY0 - AH0 N
+EQUIANGULAR  IY2 - K W AH0 - AE1 NG - G Y AH0 - L ER0
+EQUIBANK  EH1 - K W AH0 - B AE2 NG K
+EQUICOR  EH1 - K W IH2 - K AO2 R
+EQUIFAX  EH1 - K W IH0 - F AE2 K S
+EQUILIBRIA  IY2 - K W AH0 - L IH1 - B R IY0 - AH0
+EQUILIBRIUM  IY2 - K W AH0 - L IH1 - B R IY0 - AH0 M
+EQUILINK  EH1 - K W AH0 L - IH2 NG K
+EQUIMARK  EH1 - K W IH0 - M AA2 R K
+EQUINE  IY1 - K W AY2 N
+EQUINOX  IY1 - K W AH0 - N AA2 K S
+EQUION  EH1 - K W IY0 - AA0 N
+EQUIP  IH0 - K W IH1 P
+EQUIPMENT  IH0 - K W IH1 P - M AH0 N T
+EQUIPMENT'S  IH0 - K W IH1 P - M AH0 N T S
+EQUIPMENTS  IH0 - K W IH1 P - M AH0 N T S
+EQUIPPED  IH0 - K W IH1 P T
+EQUIPPING  IH0 - K W IH1 - P IH0 NG
+EQUIPS  IH0 - K W IH1 P S
+EQUITABLE  EH1 - K W AH0 - T AH0 - B AH0 L
+EQUITABLE'S  EH1 - K W AH0 - T AH0 - B AH0 L Z
+EQUITABLE(2)  EH1 - K W IH0 - T AH0 - B AH0 L
+EQUITABLY  EH1 - K W IH0 - T AH0 - B L IY0
+EQUITAS  EH1 - K W AH0 - T AH0 S
+EQUITATION  EH2 - K W AH0 - T EY1 - SH AH0 N
+EQUITEC  EH1 - K W AH0 - T EH2 K
+EQUITEX  EH1 - K W AH0 - T EH2 K S
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+ERRA  EH1 - R AH0
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+ESSES  EH1 - S IH0 Z
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+ETHNOGRAPHIC  EH2 TH - N AH0 - G R AE1 - F IH0 K
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+ETHNOMUSICOLOGIST  EH0 TH - N AH0 - M Y UW2 - Z AH0 - K AA1 - L AH0 - JH IH0 S T
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+ETHOLOGY  IH0 - TH AA1 - L AH0 - JH IY0
+ETHOS  IY1 - TH AA0 S
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+ETHYOL  EH1 - TH AY0 - AA0 L
+ETIENNE  EH1 - T IY0 - EH0 N
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+ETIOLOGY  IY2 - T IY0 - AA1 - L AH0 - JH IY0
+ETIOLOGY(2)  IY2 - T IY2 - AA1 - L AH0 - JH IY0
+ETIQUETTE  EH1 - T AH0 - K AH0 T
+ETLING  EH1 T - L IH0 NG
+ETNA  EH1 T - N AH0
+ETON  IY1 - T AH0 N
+ETOPS  IY1 - T AA0 P S
+ETRUSCAN  IH0 - T R AH1 S - K AH0 N
+ETRUSCANS  IH0 - T R AH1 S - K AH0 N Z
+ETSTY  EH1 T - S T IY0
+ETSU  EH1 T - S UW0
+ETTA  EH1 - T AH0
+ETTER  EH1 - T ER0
+ETTERS  EH1 - T ER0 Z
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+ETTINGER  EH1 - T IH0 - NG ER0
+ETTINGER'S  EH1 - T IH0 - NG ER0 Z
+ETTLINGER  EH1 T - L IH0 - NG ER0
+ETTY  EH1 - T IY0
+ETUDES  EY1 - T UW2 D Z
+ETYMOLOGICAL  EH2 - T AH0 - M AH0 - L AA1 - JH AH0 - K AH0 L
+ETYMOLOGY  EH2 - T AH0 - M AA1 - L AH0 - JH IY0
+ETYMOLOGY(2)  EH2 - T IH0 - M AA1 - L AH0 - JH IY0
+ETZEL  EH1 T - Z AH0 L
+ETZEL'S  EH1 T - Z AH0 L Z
+ETZIONI  EH2 T - S IY2 - OW1 - N IY0
+ETZKORN  EH1 T - S K ER0 N
+ETZLER  EH1 T - S L ER0
+EUAN  Y UW1 - AH0 N
+EUBANK  Y UW1 - B AE0 NG K
+EUBANKS  Y UW1 - B AE0 NG K S
+EUCALYPTI  Y UW2 - K AH0 - L IH1 P - T AY0
+EUCALYPTI(2)  Y UW2 - K AH0 - L IH1 P - T IY0
+EUCALYPTUS  Y UW2 - K AH0 - L IH1 P - T AH0 S
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+EUCHRE  Y UW1 - K ER0
+EUCHRED  Y UW1 - K ER0 D
+EUCLEA  Y UW1 - K L IY0 - AH0
+EUCLID  Y UW1 - K L IH0 D
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+EUDORA  Y UW0 - D AO1 - R AH0
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+EUDOXIA  Y UW2 - D AA1 K - S IY0 - AH0
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+EUGENIA'S  Y UW2 - JH IY1 - N IY0 - AH0 Z
+EUGENIC  Y UW0 - JH EH1 - N IH0 K
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+EUGENIE  Y UW2 - JH IY1 - N IY0
+EUGENIO  Y UW2 - JH IY1 - N IY0 - OW0
+EUGENIO'S  Y UW2 - JH IY1 - N IY0 - OW0 Z
+EULA  Y UW1 - L AH0
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+EUNICE  Y UW1 - N AH0 S
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+EUPHEMISTIC  Y UW2 - F AH0 - M IH1 - S T IH0 K
+EUPHEMISTICALLY  Y UW2 - F AH0 - M IH1 - S T IH0 K - L IY0
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+EUPHORIC  Y UW0 - F AA1 - R IH0 K
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+EUROCHECK  Y UW1 - R AH0 - CH EH2 K
+EUROCHECKS  Y UW1 - R AH0 - CH EH2 K S
+EUROCOM  Y UW1 - R AH0 - K AH0 M
+EUROCOM(2)  Y UW1 - R OW0 - K AA0 M
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+EUROCRATS  Y UW1 - R AH0 - K R AE0 T S
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+EURODEBENTURES  Y UW2 - R OW0 - D AH0 - B EH1 N - CH ER0 Z
+EURODEBT  Y UW1 - R OW0 - D EH2 T
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+EURODISNEY(2)  Y UH1 - R OW0 - D IH2 Z - N IY0
+EURODOLLAR  Y UW1 - R OW0 - D AA2 - L ER0
+EURODOLLAR(2)  Y UH1 - R OW0 - D AO2 - L ER0
+EURODOLLARS  Y UW1 - R OW0 - D AA2 - L ER0 Z
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+EUROMARKET  Y UW1 - R OW0 - M AA2 R - K IH0 T
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+EUROMISSILE  Y UW2 - R OW0 - M IH1 - S AH0 L
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+EUROMONEY  Y UW1 - R OW0 - M AH2 - N IY0
+EURONOTE  Y UW1 - R AH0 - N OW2 T
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+EUROPEANS'  Y UH2 - R AH0 - P IY1 - AH0 N Z
+EUROPEENNE  Y UW1 - R OW0 - P IY2 N
+EUROPEWIDE  Y UH1 - R AH0 P - W AY1 D
+EUROPHILE  Y UH1 - R OW0 - F AY0 L
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+EUROPIUM  Y UH0 - R OW1 - P IY0 - AH0 M
+EUROSID  Y UW1 - R AH0 - S IH0 D
+EUROSTAR  Y UH1 - R OW0 - S T AA2 R
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+EUROTUNNEL  Y UW1 - R OW0 - T AH1 - N AH0 L
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+EUROYEN  Y UW1 - R OW0 - Y EH2 N
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+EUSEBIO  Y UW2 - S IY1 - B IY0 - OW0
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+EUTHANASIA(2)  Y UW2 - TH AH0 - N EY1 - ZH Y AH0
+EUTHANIZE  Y UW1 - TH AH0 - N AY2 Z
+EUTSEY  Y UW1 T - S IY0
+EUTSLER  Y UW1 T S - L ER0
+EV  EH1 V
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+EVA'S  EY1 - V AH0 Z
+EVA'S(2)  IY1 - V AH0 Z
+EVA(2)  IY1 - V AH0
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+EVACUATE(2)  IY0 - V AE1 - K Y AH0 - EY2 T
+EVACUATED  IH0 - V AE1 - K Y AH0 W - EY2 - T IH0 D
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+EVADED  IH0 - V EY1 - D IH0 D
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+EVADES(2)  IY0 - V EY1 D Z
+EVADING  IH0 - V EY1 - D IH0 NG
+EVADING(2)  IY0 - V EY1 - D IH0 NG
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+EVALUATED  IH0 - V AE1 L - Y UW0 - EY2 - T AH0 D
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+EXCLAIMS  IH0 K - S K L EY1 M Z
+EXCLAMATION  EH2 K - S K L AH0 - M EY1 - SH AH0 N
+EXCLAMATION-POINT  EH2 K - S K L AH0 - M EY1 - SH AH0 N - P OY1 N T
+EXCLAMATIONS  EH2 K - S K L AH0 - M EY1 - SH AH0 N Z
+EXCLUDABLE  IH0 K - S K L UW1 - D AH0 - B AH0 L
+EXCLUDE  IH0 K - S K L UW1 D
+EXCLUDED  IH0 K - S K L UW1 - D AH0 D
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+EXCLUDES  IH0 K - S K L UW1 D Z
+EXCLUDING  IH0 K - S K L UW1 - D IH0 NG
+EXCLUSION  IH0 K - S K L UW1 - ZH AH0 N
+EXCLUSIONARY  IH0 K - S K L UW1 - ZH AH0 N - EH2 - R IY0
+EXCLUSIONS  IH0 K - S K L UW1 - ZH AH0 N Z
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+EXCLUSIVES  IH0 K - S K L UW1 - S IH0 V Z
+EXCLUSIVITY  EH2 K - S K L UW2 - S IH1 - V AH0 - T IY0
+EXCO  EH1 K - S K OW0
+EXCOA  EH2 K - S K OW1 - AH0
+EXCOMMUNICATE  EH2 K S - K AH0 - M Y UW1 - N AH0 - K EY2 T
+EXCOMMUNICATED  EH2 K S - K AH0 - M Y UW1 - N AH0 - K EY2 - T AH0 D
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+EXCORIATE  EH0 K S - K AO1 - R IY0 - EY2 T
+EXCORIATED  EH0 K S - K AO1 - R IY0 - EY2 - T IH0 D
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+EXCORIATION  EH0 K S - K AO1 - R IY0 - EY2 - SH AH0 N
+EXCREMENT  EH1 K - S K R AH0 - M AH0 N T
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+EXCUSABLE  IH0 K - S K Y UW1 - Z AH0 - B AH0 L
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+EXEC  EH2 G - Z EH1 K
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+EXECUTE  EH1 K - S AH0 - K Y UW2 T
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+EXECUTING  EH1 K - S AH0 - K Y UW2 - T IH0 NG
+EXECUTION  EH2 K - S AH0 - K Y UW1 - SH AH0 N
+EXECUTIONER  EH2 K - S AH0 - K Y UW1 - SH AH0 N - ER0
+EXECUTIONER'S  EH2 K - S AH0 - K Y UW1 - SH AH0 N - ER0 Z
+EXECUTIONERS  EH2 K - S AH0 - K Y UW1 - SH AH0 N - ER0 Z
+EXECUTIONS  EH2 K - S AH0 - K Y UW1 - SH AH0 N Z
+EXECUTIVE  IH0 G - Z EH1 - K Y AH0 - T IH0 V
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+EXECUTIVES  IH0 G - Z EH1 - K Y AH0 - T IH0 V Z
+EXECUTIVES'  EH0 G - Z EH1 - K Y AH0 - T IH0 V Z
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+EXECUTOR  IH0 G - Z EH1 - K Y AH0 - T ER0
+EXECUTORS  IH0 G - Z EH1 - K Y AH0 - T ER0 Z
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+EXEMPLIFIED  IH0 G - Z EH1 M - P L AH0 - F AY2 D
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+EXEMPLIFY  IH0 G - Z EH1 M - P L AH0 - F AY2
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+EXERCISABLE  EH1 K - S ER0 - S AY2 - Z AH0 - B AH0 L
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+EXERCISES  EH1 K - S ER0 - S AY2 - Z AH0 Z
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+EXHIBITED  IH0 G - Z IH1 - B AH0 - T AH0 D
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+EXHIBITIONISTS(3)  EH2 K - S AH0 - B IH1 - SH AH0 N - AH0 S
+EXHIBITIONS  EH2 K - S AH0 - B IH1 - SH AH0 N Z
+EXHIBITOR  IH0 G - Z IH1 - B AH0 - T ER0
+EXHIBITORS  IH0 G - Z IH1 - B AH0 - T ER0 Z
+EXHIBITS  IH0 G - Z IH1 - B AH0 T S
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+EXHILARATION  IH0 G - Z IH2 - L ER0 - EY1 - SH AH0 N
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+EXHUME  EH0 K S - HH Y UW1 M
+EXHUMED  EH0 K S - HH Y UW1 M D
+EXHUMES  EH0 K S - HH Y UW1 M Z
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+EXIGENCY  EH2 K - S IH1 - JH AH0 N - S IY0
+EXIGENT  EH1 K - S IH0 - JH AH0 N T
+EXIGENTS  EH1 K - S IH0 - JH AH0 N T S
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+EXISTENT  EH0 G - Z IH1 - S T AH0 N T
+EXISTENTIAL  EH2 K - S IH0 - S T EH1 N - CH AH0 L
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+EXONERATED  IH0 G - Z AA1 - N ER0 - EY2 - T IH0 D
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+EXONERATING  IH0 G - Z AA1 - N ER0 - EY2 - T IH0 NG
+EXONERATION  IH0 G - Z AA0 - N ER0 - EY1 - SH AH0 N
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+EXPANSION(2)  IH0 K - S P AE1 N - CH AH0 N
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+EXPECTATIONS  EH2 K - S P EH0 K - T EY1 - SH AH0 N Z
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+EXPLORATORY  IH0 K - S P L AO1 - R AH0 - T AO2 - R IY0
+EXPLORE  IH0 K - S P L AO1 R
+EXPLORED  IH0 K - S P L AO1 R D
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+EXPLORES  IH0 K - S P L AO1 R Z
+EXPLORING  IH0 K - S P L AO1 - R IH0 NG
+EXPLOSION  IH0 K - S P L OW1 - ZH AH0 N
+EXPLOSIONS  IH0 K - S P L OW1 - ZH AH0 N Z
+EXPLOSIVE  IH0 K - S P L OW1 - S IH0 V
+EXPLOSIVELY  EH2 K - S P L OW1 - S IH0 V - L IY0
+EXPLOSIVES  IH0 K - S P L OW1 - S IH0 V Z
+EXPLOSIVOS  EH2 K - S P L AH0 - S IY1 - V OW0 S
+EXPO  EH1 K - S P OW0
+EXPONENT  EH1 K - S P OW2 - N AH0 N T
+EXPONENTIAL  EH2 K - S P OW0 - N EH1 N - CH AH0 L
+EXPONENTIAL(2)  EH2 K - S P OW0 - N EH1 N - SH AH0 L
+EXPONENTIALLY  EH2 K - S P OW0 - N EH1 N - SH AH0 - L IY0
+EXPONENTIALLY(2)  EH2 K - S P OW0 - N EH1 N - CH AH0 - L IY0
+EXPONENTS  IH0 K - S P OW1 - N AH0 N T S
+EXPORT  EH1 K - S P AO0 R T
+EXPORTABLE  EH0 K - S P AO1 R - T AH0 - B AH0 L
+EXPORTED  IH0 K - S P AO1 R - T AH0 D
+EXPORTER  IH0 K - S P AO1 R - T ER0
+EXPORTERS  IH0 K - S P AO1 R - T ER0 Z
+EXPORTERS'  EH2 K - S P AO1 R - T ER0 Z
+EXPORTING  IH0 K - S P AO1 R - T IH0 NG
+EXPORTS  EH1 K - S P AO0 R T S
+EXPOS  EH1 K - S P OW0 Z
+EXPOSE  IH0 K - S P OW1 Z
+EXPOSED  IH0 K - S P OW1 Z D
+EXPOSES  IH0 K - S P OW1 - Z IH0 Z
+EXPOSING  IH0 K - S P OW1 - Z IH0 NG
+EXPOSITION  EH2 K - S P AH0 - Z IH1 - SH AH0 N
+EXPOSITIONS  EH2 K - S P AH0 - Z IH1 - SH AH0 N Z
+EXPOSITO  EH0 K - S P AH0 - S AY1 - T OW0
+EXPOSITO(2)  EH0 K - S P AH0 - Z IY1 - T OW0
+EXPOSURE  IH0 K - S P OW1 - ZH ER0
+EXPOSURES  IH0 K - S P OW1 - ZH ER0 Z
+EXPOUND  IH0 K - S P AW1 N D
+EXPOUNDED  IH0 K - S P AW1 N - D AH0 D
+EXPOUNDING  IH0 K - S P AW1 N - D IH0 NG
+EXPOUNDS  IH0 K - S P AW1 N D Z
+EXPRESS  IH0 K - S P R EH1 S
+EXPRESS'  IH0 K - S P R EH1 S
+EXPRESS'S  IH0 K - S P R EH1 - S IH0 Z
+EXPRESSED  IH0 K - S P R EH1 S T
+EXPRESSES  IH0 K - S P R EH1 - S AH0 Z
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+EXPRESSING  IH0 K - S P R EH1 - S IH0 NG
+EXPRESSION  IH0 K - S P R EH1 - SH AH0 N
+EXPRESSIONISM  IH0 K - S P R EH1 - SH AH0 N - IH2 - Z AH0 M
+EXPRESSIONIST  IH0 K - S P R EH1 - SH AH0 N - AH0 S T
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+EXPRESSLY  EH0 K - S P R EH1 S - L IY0
+EXPRESSO  IH0 K - S P EH1 - S OW0
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+EXPRESSWAY  IH0 K - S P R EH1 S - W EY2
+EXPROPRIATE  EH0 K S - P R OW1 - P R IY0 - EY2 T
+EXPROPRIATED  EH0 K S - P R OW1 - P R IY0 - EY2 - T IH0 D
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+EXTEND  IH0 K - S T EH1 N D
+EXTENDABLE  EH2 K - S T EH1 N - D AH0 - B AH0 L
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+EXTENDIBLE  EH2 K - S T EH1 N - D IH0 - B AH0 L
+EXTENDING  IH0 K - S T EH1 N - D IH0 NG
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+EXTENSION  IH0 K - S T EH1 N - SH AH0 N
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+EXTENUATE  IH0 K - S T EH1 - N Y UW0 - EY2 T
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+EXTERIOR  IH0 K - S T IH1 - R IY0 - ER0
+EXTERIORS  EH0 K - S T IH1 - R IY0 - ER0 Z
+EXTERMINATE  IH0 K - S T ER1 - M AH0 - N EY2 T
+EXTERMINATED  IH0 K - S T ER1 - M AH0 - N EY2 - T IH0 D
+EXTERMINATES  IH0 K - S T ER1 - M AH0 - N EY2 T S
+EXTERMINATING  IH0 K - S T ER1 - M AH0 - N EY2 - T IH0 NG
+EXTERMINATION  IH0 K - S T ER2 - M AH0 - N EY1 - SH AH0 N
+EXTERMINATOR  IH0 K - S T ER1 - M AH0 - N EY2 - T ER0
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+EXTINGUISH  IH0 K - S T IH1 NG - G W IH0 SH
+EXTINGUISHED  IH0 K - S T IH1 NG - G W IH0 SH T
+EXTINGUISHER  IH0 K - S T IH1 NG - G W IH0 - SH ER0
+EXTINGUISHERS  IH0 K - S T IH1 NG - G W IH0 - SH ER0 Z
+EXTINGUISHING  IH0 K - S T IH1 NG - G W IH0 - SH IH0 NG
+EXTINGUISHMENT  IH0 K - S T IH1 NG - G W IH0 SH - M AH0 N T
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+EXTOL  IH0 K - S T OW1 L
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+EXTOLLING  IH0 K - S T OW1 - L IH0 NG
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+EXTRACT  IH0 K - S T R AE1 K T
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+EXTRACTED  IH0 K - S T R AE1 K - T AH0 D
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+EXTRACTIONS  IH0 K - S T R AE1 K - SH AH0 N Z
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+EXTRATERRITORIAL  EH2 K - S T R AH0 - T EH2 - R IH0 - T AO1 - R IY0 - AH0 L
+EXTRATERRITORIALITY  EH2 K - S T R AH0 - T EH2 - R AH0 - T AO2 - R IY0 - AE1 - L AH0 - T IY0
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+FIN  F IH1 N
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+G  JH IY1
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+GALLUP  G AE1 - L AH0 P
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+GALVANIC  G AE0 L - V AE1 - N IH0 K
+GALVANIZE  G AE1 L - V AH0 - N AY2 Z
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+HAPPENED  HH AE1 - P AH0 N D
+HAPPENING  HH AE1 - P AH0 - N IH0 NG
+HAPPENING(2)  HH AE1 P - N IH0 NG
+HAPPENINGS  HH AE1 - P AH0 - N IH0 NG Z
+HAPPENINGS(2)  HH AE1 P - N IH0 NG Z
+HAPPENS  HH AE1 - P AH0 N Z
+HAPPENSTANCE  HH AE1 - P AH0 N - S T AE2 N S
+HAPPIER  HH AE1 - P IY0 - ER0
+HAPPIEST  HH AE1 - P IY0 - AH0 S T
+HAPPILY  HH AE1 - P AH0 - L IY0
+HAPPINESS  HH AE1 - P IY0 - N AH0 S
+HAPPY  HH AE1 - P IY0
+HAPSBURG  HH AE1 P S - B ER0 G
+HAQ  HH AE1 K
+HAQ'S  HH AE1 K S
+HAQUE  HH AE1 K
+HARA  HH EH1 - R AH0
+HARA-KIRI  HH AA1 - R IH0 - K IH1 - R IY0
+HARADA  HH AA0 - R AA1 - D AH0
+HARADIM  HH AH0 - R AE1 - D IH2 M
+HARADIM(2)  HH AH0 - R AE2 - D IY1 M
+HARAHAN  HH AE1 - R AH0 - HH AE2 N
+HARALD  HH AA1 - R AH0 L D
+HARALDA  HH AA0 - R AA1 L - D AH0
+HARALSON  HH AE1 - R AH0 L - S AH0 N
+HARAN  HH AE1 - R AH0 N
+HARANGUE  HH ER0 - AE1 NG
+HARANGUED  HH ER0 - AE1 NG D
+HARANGUES  HH ER0 - AE1 NG Z
+HARANGUING  HH ER0 - AE1 - NG IH0 NG
+HARARE  HH ER0 - AA1 - R IY0
+HARASS  HH ER0 - AE1 S
+HARASSED  HH ER0 - AE1 S T
+HARASSER  HH ER0 - AE1 - S ER0
+HARASSERS  HH ER0 - AE1 - S ER0 Z
+HARASSING  HH ER0 - AE1 - S IH0 NG
+HARASSMENT  HH ER0 - AE1 S - M AH0 N T
+HARASZTI  HH ER0 - AE1 - S T IY0
+HARAWAY  HH AA1 - R AH0 - W EY0
+HARB  HH AA1 R B
+HARBACH  HH AA1 R - B AA2 K
+HARBAUGH  HH AA1 R - B AO2
+HARBECK  HH AA1 R - B EH2 K
+HARBER  HH AA1 R - B ER0
+HARBERT  HH AA1 R - B ER0 T
+HARBERTS  HH AA1 R - B ER0 T S
+HARBESON  HH AA1 R - B IH0 - S AH0 N
+HARBIN  HH AA1 R - B IH0 N
+HARBINGER  HH AA1 R - B IH0 N - JH ER0
+HARBINGERS  HH AA1 R - B IH0 NG - ER0 Z
+HARBINSON  HH AA1 R - B IH0 N - S AH0 N
+HARBISON  HH AA1 R - B IH0 - S AH0 N
+HARBOLD  HH AA1 R - B OW2 L D
+HARBOR  HH AA1 R - B ER0
+HARBOR'S  HH AA1 R - B ER0 Z
+HARBORED  HH AA1 R - B ER0 D
+HARBORING  HH AA1 R - B ER0 - IH0 NG
+HARBORS  HH AA1 R - B ER0 Z
+HARBORSIDE  HH AA1 R - B ER0 - S AY2 D
+HARBOUR  HH AA1 R - B ER0
+HARBUCK  HH AA1 R - B AH0 K
+HARBURY  HH AA1 R - B ER0 - IY0
+HARC  HH AA1 R K
+HARCLERODE  HH AA1 R - K AH0 - L ER0 - OW0 D
+HARCLERODE(2)  HH AA1 R K - L ER0 - OW0 D
+HARCOURT  HH AA1 R - K AO2 R T
+HARCOURT'S  HH AA1 R - K ER0 T S
+HARCROW  HH AA1 R - K R OW0
+HARCUM  HH AA1 R - K AH0 M
+HARD  HH AA1 R D
+HARDACRE  HH AA1 R - D EY2 - K ER0
+HARDAGE  HH AA1 R - D IH0 JH
+HARDART  HH AA1 R - D AA2 R T
+HARDAWAY  HH AA1 R D - AH0 - W EY2
+HARDBACK  HH AA1 R D - B AE2 K
+HARDBALL  HH AA1 R D - B AO2 L
+HARDBOARD  HH AA1 R D - B AO2 R D
+HARDCASTLE  HH AA1 R D - K AE2 - S AH0 L
+HARDCORE  HH AA1 R D - K AO1 R
+HARDCOVER  HH AA1 R D - K AH2 - V ER0
+HARDEBECK  HH AA1 R D - B EH0 K
+HARDEE  HH AA1 R - D IY1
+HARDEE'S  HH AA1 R - D IY1 Z
+HARDEGREE  HH AA0 R - D IH0 - G R IY1
+HARDEMAN  HH AA1 R D - M AH0 N
+HARDEN  HH AA1 R - D AH0 N
+HARDEN'S  HH AA1 R - D AH0 N Z
+HARDENBROOK  HH AA1 R - D AH0 N - B R UH2 K
+HARDENED  HH AA1 R - D AH0 N D
+HARDENER  HH AA1 R - D AH0 N - ER0
+HARDENING  HH AA1 R - D AH0 N - IH0 NG
+HARDENING(2)  HH AA1 R D - N IH0 NG
+HARDENS  HH AA1 R - D AH0 N Z
+HARDER  HH AA1 R - D ER0
+HARDERS  HH AA1 R - D ER0 Z
+HARDEST  HH AA1 R - D AH0 S T
+HARDESTY  HH AA1 R - D AH0 - S T IY0
+HARDEY  HH AA1 R - D IY0
+HARDGOOD  HH AA1 R D - G UH2 D
+HARDGOODS  HH AA1 R D - G UH2 D Z
+HARDGRAVE  HH AA1 R D - G R EY2 V
+HARDGROVE  HH AA1 R D - G R OW2 V
+HARDHEAD  HH AA1 R D - HH EH2 D
+HARDHEADED  HH AA1 R D - HH EH2 - D IH0 D
+HARDICK  HH AA1 R - D IH0 K
+HARDIE  HH AA1 R - D IY0
+HARDIER  HH AA1 R - D IY0 - ER0
+HARDIGREE  HH AA0 R - D IH0 - G R IY1
+HARDIMAN  HH AA1 R - D IH0 - M AH0 N
+HARDIMON  HH AA1 R - D IH0 - M AA0 N
+HARDIN  HH AA1 R - D IH0 N
+HARDING  HH AA1 R - D IH0 NG
+HARDING'S  HH AA1 R - D IH0 NG S
+HARDINGER  HH AA1 R - D IH0 - NG ER0
+HARDISON  HH AA1 R - D IH0 S - AH0 N
+HARDISTER  HH AA1 R - D IH0 - S T ER0
+HARDISTY  HH AA1 R - D IH0 - S T IY0
+HARDLINE  HH AA1 R D - L AY2 N
+HARDLINER  HH AA1 R D - L AY2 - N ER0
+HARDLINERS  HH AA1 R D - L AY2 - N ER0 Z
+HARDLY  HH AA1 R D - L IY0
+HARDMAN  HH AA1 R D - M AH0 N
+HARDNESS  HH AA1 R D - N AH0 S
+HARDNETT  HH AA1 R D - N IH0 T
+HARDPRESSED  HH AA1 R D - P R EH2 S T
+HARDRICK  HH AA1 R D - R IH0 K
+HARDS  HH AA1 R D Z
+HARDSCRABBLE  HH AA1 R D - S K R AE2 - B AH0 L
+HARDSHIP  HH AA1 R D - SH IH0 P
+HARDSHIPS  HH AA1 R D - SH IH0 P S
+HARDT  HH AA1 R T
+HARDTKE  HH AA1 R D - K IY0
+HARDWARE  HH AA1 R D - W EH2 R
+HARDWAY  HH AA1 R D - W EY2
+HARDWICK  HH AA1 R D - W IH2 K
+HARDWICKE  HH AA1 R D - W IH0 K
+HARDWIN  HH AA1 R D - W IH0 N
+HARDWOOD  HH AA1 R D - W UH2 D
+HARDWOODS  HH AA1 R D - W UH2 D Z
+HARDWORK  HH AA1 R D - W ER2 K
+HARDWORKING  HH AA1 R D - W ER2 - K IH0 NG
+HARDY  HH AA1 R - D IY0
+HARDY'S  HH AA1 R - D IY0 Z
+HARDYMON  HH AA1 R - D IY0 - M AA2 N
+HARE  HH EH1 R
+HARE'S  HH EH1 R Z
+HAREBRAINED  HH EH1 R - B R EY2 N D
+HARELSON  HH AE1 - R IH0 L - S AH0 N
+HAREM  HH EH1 - R AH0 M
+HAREN  HH EH1 - R AH0 N
+HARER  HH EH1 - R ER0
+HARES  HH EH1 R Z
+HAREWOOD  HH EH1 R - W UH2 D
+HARFF  HH AA1 R F
+HARFORD  HH AA1 R - F ER0 D
+HARGADON  HH AA0 R - G AA0 - D AO1 N
+HARGAN  HH AA1 R - G AH0 N
+HARGARTEN  HH AA1 R - G AA0 R - T AH0 N
+HARGENS  HH AA1 R - G AH0 N Z
+HARGER  HH AA1 R - G ER0
+HARGETT  HH AA1 R - JH IH0 T
+HARGIS  HH AA1 R - G IH0 S
+HARGRAVE  HH AA1 R - G R EY2 V
+HARGRAVES  HH AA1 R - G R EY2 V Z
+HARGREAVES  HH AA1 R - G R IY2 V Z
+HARGROVE  HH AA1 R - G R OW2 V
+HARGUS  HH AA1 R - G AH0 S
+HARI  HH AA1 - R IY0
+HARIG  HH AE1 - R IH0 G
+HARIMA  HH EH0 - R IY1 - M AH0
+HARING  HH EH1 - R IH0 NG
+HARIRI  HH ER0 - IH1 - R IY0
+HARIS  HH AA1 - R IY0 S
+HARIS(2)  HH EH1 - R IH0 S
+HARITOS  HH EH0 - R IY1 - T OW0 S
+HARIZ  HH EH1 - R IH0 Z
+HARJO  HH AA1 R - JH OW0
+HARJU  HH AA1 - R Y UW0
+HARK  HH AA1 R K
+HARKAVY  HH AA1 R - K AH0 - V IY0
+HARKE  HH AA1 R K
+HARKEN  HH AA1 R - K AH0 N
+HARKER  HH AA1 R - K ER0
+HARKEY  HH AA1 R - K IY0
+HARKIN  HH AA1 R - K IH0 N
+HARKIN'S  HH AA1 R - K IH0 N Z
+HARKING  HH AA1 R - K IH0 NG
+HARKINS  HH AA1 R - K IH0 N Z
+HARKLEROAD  HH AA1 R K - L ER0 - OW0 D
+HARKLESS  HH AA1 R K - L AH0 S
+HARKNESS  HH AA1 R K - N AH0 S
+HARKRADER  HH AA1 R - K R AH0 - D ER0
+HARKRIDER  HH AA1 R K - R AY2 - D ER0
+HARKS  HH AA1 R K S
+HARL  HH AA1 R L
+HARLACHER  HH AA1 R - L AH0 - K ER0
+HARLAN  HH AA1 R - L AH0 N
+HARLAND  HH AA1 R - L AH0 N D
+HARLE  HH AA1 - R AH0 L
+HARLEM  HH AA1 R - L AH0 M
+HARLEM'S  HH AA1 R - L AH0 M Z
+HARLEMAN  HH AA1 - R AH0 L - M AH0 N
+HARLEQUIN  HH AA1 R - L AH0 - K W AH0 N
+HARLESS  HH AA1 R - L IH0 S
+HARLEY  HH AA1 R - L IY0
+HARLEY'S  HH AA1 R - L IY0 Z
+HARLEYSVILLE  HH AA1 R - L IY0 Z - V IH2 L
+HARLIN  HH AA1 R - L IH0 N
+HARLIN'S  HH AA1 R - L IH0 N Z
+HARLING  HH AA1 R - L IH0 NG
+HARLINGEN  HH AA1 R - L IH0 - NG AH0 N
+HARLISON  HH AA1 R - L IH0 - S AH0 N
+HARLOFF  HH AA1 R - L AO0 F
+HARLOT  HH AA1 R - L AH0 T
+HARLOW  HH AA1 R - L OW0
+HARM  HH AA1 R M
+HARM'S  HH AA1 R M Z
+HARMAN  HH AA1 R - M AH0 N
+HARMATA  HH AA0 R - M AA1 - T AH0
+HARMATTAN  HH AA2 R - M AH0 - T AE1 N
+HARMED  HH AA1 R M D
+HARMEL  HH AA1 R - M AH0 L
+HARMENING  HH AA1 R - M AH0 - N IH0 NG
+HARMER  HH AA1 R - M ER0
+HARMES  HH AA1 R M Z
+HARMETZ  HH AA1 R - M EH2 T S
+HARMEYER  HH AA1 R - M AY2 - ER0
+HARMFUL  HH AA1 R M - F AH0 L
+HARMFULNESS  HH AA1 R M - F AH0 L - N AH0 S
+HARMING  HH AA1 R - M IH0 NG
+HARMISON  HH AA1 R - M IH0 - S AH0 N
+HARMLESS  HH AA1 R M - L AH0 S
+HARMLESSLY  HH AA1 R M - L AH0 S - L IY0
+HARMON  HH AA1 R - M AH0 N
+HARMON'S  HH AA1 R - M AH0 N Z
+HARMONIA  HH AA0 R - M OW1 - N IY0 - AH0
+HARMONIC  HH AA0 R - M AA1 - N IH0 K
+HARMONICA  HH AA0 R - M AA1 - N IH0 - K AH0
+HARMONICS  HH AA0 R - M AA1 - N IH0 K S
+HARMONIE  HH AA1 R - M AH0 - N IY0
+HARMONIES  HH AA1 R - M AH0 - N IY0 Z
+HARMONIOUS  HH AA0 R - M OW1 - N IY0 - AH0 S
+HARMONIOUSLY  HH AA0 R - M OW1 - N IY0 - AH0 S - L IY0
+HARMONIUM  HH AA0 R - M OW1 - N IY0 - AH0 M
+HARMONIZATION  HH AA2 R - M AH0 - N IH0 - Z EY1 - SH AH0 N
+HARMONIZE  HH AA1 R - M AH0 - N AY2 Z
+HARMONIZED  HH AA1 R - M AH0 - N AY2 Z D
+HARMONIZING  HH AA1 R - M AH0 - N AY2 - Z IH0 NG
+HARMONY  HH AA1 R - M AH0 - N IY0
+HARMS  HH AA1 R M Z
+HARMSEN  HH AA1 R M - S AH0 N
+HARN  HH AA1 R N
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+HARNAGE  HH AA1 R - N IH0 JH
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+HARNE  HH AA1 R N
+HARNED  HH AA1 R N D
+HARNER  HH AA1 R - N ER0
+HARNESS  HH AA1 R - N AH0 S
+HARNESS(2)  HH AA1 R - N IH0 S
+HARNESSED  HH AA1 R - N AH0 S T
+HARNESSES  HH AA1 R - N AH0 - S AH0 Z
+HARNESSES(2)  HH AA1 R - N AH0 - S IH0 Z
+HARNESSING  HH AA1 R - N AH0 - S IH0 NG
+HARNETT  HH AA1 R - N IH0 T
+HARNEY  HH AA1 R - N IY0
+HARNISCH  HH AA1 R - N IH0 SH
+HARNISCHFEGER  HH AA1 R - N IH0 SH - F EH2 - G ER0
+HARNISCHFEGER'S  HH AA1 R - N IH0 SH - F EH2 - G ER0 Z
+HARNISH  HH AA1 R - N IH0 SH
+HARNOIS  HH AA0 R N - W AA1
+HARO  HH AA1 - R OW0
+HAROLD  HH EH1 - R AH0 L D
+HAROLD'S  HH EH1 - R AH0 L D Z
+HAROLDSON  HH AE1 - R OW0 L D - S AH0 N
+HARP  HH AA1 R P
+HARPE  HH AA1 R P
+HARPED  HH AA1 R P T
+HARPEL  HH AA0 R - P EH1 L
+HARPENAU  HH AA1 R - P IH0 - N OW0
+HARPER  HH AA1 R - P ER0
+HARPER'S  HH AA1 R - P ER0 Z
+HARPERCOLLINS  HH AA1 R - P ER0 - K AO1 - L IH0 N Z
+HARPERS  HH AA1 R - P ER0 Z
+HARPHAM  HH AA1 R - F AH0 M
+HARPIN  HH AA0 R - P AE1 N
+HARPING  HH AA1 R - P IH0 NG
+HARPIST  HH AA1 R - P IH0 S T
+HARPISTS  HH AA1 R - P IH0 S T S
+HARPISTS(2)  HH AA1 R - P IH0 S S
+HARPISTS(3)  HH AA1 R - P IH0 S
+HARPLEY  HH AA1 R P - L IY0
+HARPO  HH AA1 R - P OW0
+HARPOLD  HH AA1 R - P OW2 L D
+HARPOLE  HH AA1 R - P OW2 L
+HARPOON  HH AA0 R - P UW1 N
+HARPOONS  HH AA0 R - P UW1 N Z
+HARPOOTLIAN  HH AA0 R - P UW1 T - L IY0 - AH0 N
+HARPS  HH AA1 R P S
+HARPSICHORD  HH AA1 R P - S AH0 - K AO2 R D
+HARPST  HH AA1 R P S T
+HARPSTER  HH AA1 R P - S T ER0
+HARQUEBUS  HH AA1 R - K W AH0 - B AH0 S
+HARR  HH AE1 R
+HARRAH  HH AE1 - R AH0
+HARRAH'S  HH EH1 - R AH0 Z
+HARRAL  HH AE1 - R AH0 L
+HARRALSON  HH AE1 - R AH0 L - S AH0 N
+HARRE  HH AE1 R
+HARREL  HH AE1 - R AH0 L
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+HARRELL  HH EH1 - R AH0 L
+HARRELL'S  HH AE1 - R AH0 L Z
+HARRELSON  HH EH1 - R IH0 L - S AH0 N
+HARREN  HH AE1 - R AH0 N
+HARRER  HH AA1 - R ER0
+HARRIED  HH EH1 - R IY0 D
+HARRIER  HH EH1 - R IY0 - ER0
+HARRIES  HH EH1 - R IY0 Z
+HARRIET  HH EH1 - R IY0 - AH0 T
+HARRIETTE  HH AE1 - R IY0 - EH0 T
+HARRIGAN  HH EH1 - R IH0 - G AH0 N
+HARRIGER  HH AE1 - R IH0 - G ER0
+HARRILL  HH AE1 - R AH0 L
+HARRIMAN  HH EH1 - R IH0 - M AH0 N
+HARRING  HH AE1 - R IH0 NG
+HARRINGTON  HH EH1 - R IH0 NG - T AH0 N
+HARRIOTT  HH AE1 - R IY0 - AH0 T
+HARRIS  HH EH1 - R IH0 S
+HARRIS'  HH EH1 - R IH0 S
+HARRIS'S  HH EH1 - R IH0 - S IH0 Z
+HARRISBURG  HH AE1 - R IH0 S - B ER0 G
+HARRISBURG'S  HH AE1 - R IH0 S - B ER0 G Z
+HARRISBURG'S(2)  HH EH1 - R IH0 S - B ER0 G Z
+HARRISBURG(2)  HH EH1 - R IH0 S - B ER0 G
+HARRISON  HH EH1 - R IH0 - S AH0 N
+HARRISON'S  HH EH1 - R IH0 - S AH0 N Z
+HARRISS  HH AE1 - R IH0 S
+HARRITY  HH AE1 - R IH0 - T IY0
+HARROD  HH EH1 - R AH0 D
+HARROD'S  HH EH1 - R AH0 D Z
+HARRODS  HH EH1 - R AH0 D Z
+HARROLD  HH EH1 - R AH0 L D
+HARRON  HH AE1 - R AH0 N
+HARROP  HH EH1 - R AH0 P
+HARROUN  HH ER0 - UW1 N
+HARROW  HH AE1 - R OW0
+HARROWER  HH AE1 - R OW0 - W ER0
+HARROWING  HH EH1 - R OW0 - IH0 NG
+HARRY  HH EH1 - R IY0
+HARRY'S  HH EH1 - R IY0 Z
+HARRYMAN  HH AE1 - R IY0 - M AH0 N
+HARSCH  HH AA1 R SH
+HARSCO  HH AA1 R - S K OW0
+HARSH  HH AA1 R SH
+HARSHA  HH AA1 R - SH AH0
+HARSHAM  HH AA1 R - SH AH0 M
+HARSHAW  HH AA1 R - SH AO2
+HARSHBARGER  HH AA1 R SH - B AA2 R - G ER0
+HARSHBERGER  HH AA1 R SH - B ER0 - G ER0
+HARSHER  HH AA1 R - SH ER0
+HARSHEST  HH AA1 R - SH AH0 S T
+HARSHFIELD  HH AA1 R SH - F IY2 L D
+HARSHLY  HH AA1 R SH - L IY0
+HARSHMAN  HH AA1 R SH - M AH0 N
+HARSHNESS  HH AA1 R SH - N AH0 S
+HARSTAD  HH AA1 R - S T AH0 D
+HARSTON  HH AA1 R - S T AH0 N
+HART  HH AA1 R T
+HART'S  HH AA1 R T S
+HARTE  HH AA1 R T
+HARTEL  HH AA1 R - T AH0 L
+HARTELL  HH AA1 R - T AH0 L
+HARTEN  HH AA1 R - T AH0 N
+HARTENSTEIN  HH AA1 R - T AH0 N - S T AY2 N
+HARTENSTEIN(2)  HH AA1 R - T AH0 N - S T IY2 N
+HARTER  HH AA1 R - T ER0
+HARTFIEL  HH AA1 R T - F IY2 L
+HARTFIELD  HH AA1 R T - F IY2 L D
+HARTFORD  HH AA1 R T - F ER0 D
+HARTFORD'S  HH AA1 R T - F ER0 D Z
+HARTGRAVES  HH AA1 R T - G R EY2 V Z
+HARTGROVE  HH AA1 R T - G R OW2 V
+HARTH  HH AA1 R TH
+HARTIG  HH AA1 R - T IH0 G
+HARTIGAN  HH AA1 R - T IH0 - G AH0 N
+HARTIN  HH AA1 R - T IH0 N
+HARTING  HH AA1 R - T IH0 NG
+HARTINGER  HH AA1 R - T IH0 - NG ER0
+HARTIS  HH AA1 R - T IH0 S
+HARTJE  HH AA1 R T - JH EY0
+HARTKE  HH AA1 R T - K IY0
+HARTKOPF  HH AA1 R T - K AO0 F
+HARTL  HH AA1 R - T AH0 L
+HARTLAGE  HH AA1 R T - L IH0 JH
+HARTLAND  HH AA1 R T - L AH0 N D
+HARTLAUB  HH AA1 R T - L AW2 B
+HARTLE  HH AA1 R - T AH0 L
+HARTLESS  HH AA1 R T - L AH0 S
+HARTLEY  HH AA1 R T - L IY0
+HARTLIEB  HH AA1 R T - L IY2 B
+HARTLINE  HH AA1 R T - L AY2 N
+HARTLING  HH AA1 R T - L IH0 NG
+HARTMAN  HH AA1 R T - M AH0 N
+HARTMANN  HH AA1 R T - M AH0 N
+HARTMARX  HH AA1 R T - M AA2 R K S
+HARTNELL  HH AA1 R T - N AH0 L
+HARTNER  HH AA1 R T - N ER0
+HARTNESS  HH AA1 R T - N AH0 S
+HARTNETT  HH AA1 R T - N IH0 T
+HARTNEY  HH AA1 R T - N IY0
+HARTOG  HH AA1 R - T AH0 G
+HARTON  HH AA1 R - T AH0 N
+HARTONG  HH AA1 R - T AO0 NG
+HARTRANFT  HH AA1 R - T R AH2 N F T
+HARTS  HH AA1 R T S
+HARTSELL  HH AA1 R T - S AH0 L
+HARTSFIELD  HH AA1 R T S - F IY2 L D
+HARTSHORN  HH AA1 R T S - HH AO2 R N
+HARTSHORNE  HH AA1 R - CH ER0 N
+HARTSOCK  HH AA1 R T - S AH0 K
+HARTSOE  HH AA1 R T - S OW0
+HARTSON  HH AA1 R T - S AH0 N
+HARTSOOK  HH AA1 R T - S UH0 K
+HARTSOUGH  HH AA1 R T - S AW0
+HARTSTEIN  HH AA1 R T - S T AY2 N
+HARTSTEIN(2)  HH AA1 R T - S T IY2 N
+HARTSVILLE  HH AA1 R T - S V IH0 L
+HARTT  HH AA1 R T
+HARTTER  HH AA1 R - T ER0
+HARTUNG  HH AA1 R - T AH0 NG
+HARTWELL  HH AA1 R T - W EH2 L
+HARTWICK  HH AA1 R T - W IH2 K
+HARTWIG  HH AA1 R T - W IH0 K
+HARTWOOD  HH AA1 R T - W UH2 D
+HARTY  HH AA1 R - T IY0
+HARTZ  HH AA1 R T S
+HARTZEL  HH AA1 R T - Z AH0 L
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+HEINZMAN  HH AY1 N Z - M AH0 N
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+HEISHMAN  HH IY1 - IH0 SH - M AH0 N
+HEISINGER  HH AY1 - S IH0 N - JH ER0
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+HEISMAN  HH AY1 S - M AH0 N
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+HEMINGER  HH EH1 - M IH0 - NG ER0
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+I  AY1
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+IMHOF  IH1 M - HH AH0 F
+IMHOFF  IH1 M - HH AO2 F
+IMIG  IH1 - M IH0 G
+IMITABLE  IH1 - M AH0 - T AH0 - B AH0 L
+IMITATE  IH1 - M AH0 - T EY2 T
+IMITATED  IH1 - M AH0 - T EY2 - T IH0 D
+IMITATES  IH1 - M AH0 - T EY2 T S
+IMITATING  IH1 - M AH0 - T EY2 - T IH0 NG
+IMITATION  IH2 - M AH0 - T EY1 - SH AH0 N
+IMITATIONS  IH2 - M IH0 - T EY1 - SH AH0 N Z
+IMITATIVE  IH1 - M AH0 - T EY2 - T IH0 V
+IMITATOR  IH1 - M AH0 - T EY2 - T ER0
+IMITATORS  IH1 - M IH0 - T EY2 - T ER0 Z
+IMLAY  IH0 M - L EY1
+IMLER  IH1 M - L ER0
+IMM  AY1 - EH1 - M EH1 M
+IMM(2)  IH1 M
+IMMACULATE  IH0 - M AE1 - K Y UW0 - L IH0 T S
+IMMACULATELY  IH0 - M AE1 - K Y AH0 - L AH0 T - L IY0
+IMMANENCE  IH1 - M AH0 - N AH0 N S
+IMMANENT  IH1 - M AH0 - N AH0 N T
+IMMANUEL  IH1 - M AH0 - N UH0 L
+IMMATERIAL  IH2 - M AH0 - T IH1 - R IY0 - AH0 L
+IMMATURE  IH2 - M AH0 - T Y UH1 R
+IMMATURITY  IH2 - M AH0 - CH UH1 - R IH0 - T IY0
+IMMEASURABLE  IH0 - M EH1 - ZH ER0 - AE2 - B AH0 L
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+IMMEDIATE  IH0 - M IY1 - D IY0 - AH0 T
+IMMEDIATELY  IH0 - M IY1 - D IY0 - AH0 T - L IY0
+IMMEL  IH1 - M AH0 L
+IMMEMORIAL  IH2 - M AH0 - M AO1 - R IY0 - AH0 L
+IMMENSE  IH0 - M EH1 N S
+IMMENSELY  IH0 - M EH1 N S - L IY0
+IMMERMAN  IH1 - M ER0 - M AH0 N
+IMMERSE  IH0 - M ER1 S
+IMMERSED  IH0 - M ER1 S T
+IMMERSION  IH0 - M ER1 - ZH AH0 N
+IMMIGRANT  IH1 - M AH0 - G R AH0 N T
+IMMIGRANT'S  IH1 - M AH0 - G R AH0 N T S
+IMMIGRANTS  IH1 - M AH0 - G R AH0 N T S
+IMMIGRANTS'  IH1 - M IH0 - G R AH0 N T S
+IMMIGRATE  IH1 - M AH0 - G R EY2 T
+IMMIGRATED  IH1 - M AH0 - G R EY2 - T IH0 D
+IMMIGRATION  IH2 - M AH0 - G R EY1 - SH AH0 N
+IMMINENCE  IH1 - M AH0 - N AH0 N S
+IMMINENT  IH1 - M AH0 - N AH0 N T
+IMMINENTLY  IH1 - M AH0 - N AH0 N T - L IY0
+IMMISCIBLE  IH0 - M IH1 - S AH0 - B AH0 L
+IMMOBILE  IH0 - M OW1 - B AH0 L
+IMMOBILE(2)  IH0 - M OW1 - B AY2 L
+IMMOBILE(3)  IH0 - M OW1 - B IY2 L
+IMMOBILITY  IH2 - M OW0 - B IH1 - L IH0 - T IY0
+IMMOBILIZE  IH0 - M OW1 - B AH0 - L AY2 Z
+IMMOBILIZED  IH0 - M OW1 - B AH0 - L AY2 Z D
+IMMOBILIZING  IH0 - M OW1 - B AH0 - L AY2 - Z IH0 NG
+IMMORAL  IH0 - M AO1 - R AH0 L
+IMMORALITY  IH2 - M ER0 - AE1 - L IH0 - T IY0
+IMMORTAL  IH0 - M AO1 R - T AH0 L
+IMMORTALITY  IH2 - M AO0 R - T AE1 - L IH0 - T IY0
+IMMORTALIZE  IH0 - M AO1 R - T AH0 - L AY0 Z
+IMMORTALIZED  IH0 - M AO1 R - T AH0 - L AY0 Z D
+IMMORTALIZES  IH0 - M AO1 R - T AH0 - L AY0 - Z IH0 Z
+IMMORTALIZING  IH0 - M AO1 R - T AH0 - L AY0 - Z IH0 NG
+IMMORTALS  IH0 - M AO1 R - T AH0 L Z
+IMMOTILE  IH0 - M OW1 - T AH0 L
+IMMOVABLE  IH0 - M UW1 - V AH0 - B AH0 L
+IMMULOGIC  IH1 - M Y UW0 - L AA2 - JH IH0 K
+IMMUNE  IH0 - M Y UW1 N
+IMMUNETECH  IH1 - M Y UW0 N - T EH2 K
+IMMUNEX  IH1 - M Y UW0 - N EH0 K S
+IMMUNITIES  IH0 - M Y UW1 - N IH0 - T IY0 Z
+IMMUNITY  IH0 - M Y UW1 - N AH0 - T IY0
+IMMUNITY(2)  IH0 - M Y UW1 - N IH0 - T IY0
+IMMUNIZATION  IH2 - M Y UW0 - N AH0 - Z EY1 - SH AH0 N
+IMMUNIZATIONS  IH2 - M Y UW0 - N AH0 - Z EY1 - SH AH0 N Z
+IMMUNIZE  IH1 - M Y UW0 - N AY2 Z
+IMMUNIZED  IH1 - M Y AH0 - N AY2 Z D
+IMMUNIZES  IH1 - M Y AH0 - N AY2 - Z IH0 Z
+IMMUNIZING  IH1 - M Y AH0 - N AY2 - Z IH0 NG
+IMMUNO  IH0 - M Y UW1 - N OW0
+IMMUNODEFICIENCY  IH2 - M Y UW0 - N OW0 - D IH2 - F IH1 - SH AH0 N - S IY0
+IMMUNOLOGICAL  IH2 - M Y UW0 - N AH0 - L AA1 - JH IH0 - K AH0 L
+IMMUNOLOGIST  IH2 - M Y UW0 - N AA1 - L AH0 - JH IH0 S T
+IMMUNOLOGY  IH2 - M Y UW0 - N AA1 - L AH0 - JH IY0
+IMMUNOMEDIC  IH1 - M Y UW0 - N OW0 - M EH2 - D IH0 K
+IMMUNOMEDICS  IH1 - M Y UW0 - N OW0 - M EH2 - D IH0 K S
+IMMUNOTHERAPY  IH2 - M Y UW0 - N OW0 - TH EH1 - R AH0 - P IY0
+IMMUTABLE  IH0 - M Y UW1 - T AH0 - B AH0 L
+IMNET  IH1 M - N EH2 T
+IMO  AY1 - M OW0
+IMO(2)  AY1 - EH1 - M OW1
+IMOGEN  IH1 - M AH0 - G AH0 N
+IMOGENE  IH1 - M AH0 - JH IY2 N
+IMONDI  IH0 - M OW1 N - D IY0
+IMONDI(2)  IH0 - M AA1 N - D IY0
+IMP  IH1 M P
+IMPACT  IH0 M - P AE1 K T
+IMPACT(2)  IH1 M - P AE0 K T
+IMPACTED  IH1 M - P AE2 K - T IH0 D
+IMPACTED(2)  IH0 M - P AE1 K - T IH0 D
+IMPACTING  IH0 M - P AE1 K - T IH0 NG
+IMPACTS  IH0 M - P AE1 K T S
+IMPACTS(2)  IH1 M - P AE0 K T S
+IMPACTS(3)  IH0 M - P AE1 K S
+IMPACTS(4)  IH1 M - P AE0 K S
+IMPAIR  IH0 M - P EH1 R
+IMPAIRED  IH0 M - P EH1 R D
+IMPAIRING  IH0 M - P EH1 - R IH0 NG
+IMPAIRMENT  IH0 M - P EH1 R - M AH0 N T
+IMPAIRMENTS  IH0 M - P EH1 R - M AH0 N T S
+IMPAIRS  IH0 M - P EH1 R Z
+IMPALA  IH0 M - P AA1 - L AH0
+IMPALED  IH0 M - P EY1 L D
+IMPANEL  IH0 M - P AE1 - N AH0 L
+IMPANELED  IH0 M - P AE1 - N AH0 L D
+IMPART  IH0 M - P AA1 R T
+IMPARTED  IH0 M - P AA1 R - T IH0 D
+IMPARTIAL  IH0 M - P AA1 R - SH AH0 L
+IMPARTIALITY  IH0 M - P AA2 R - SH IY0 - AE1 - L IH0 - T IY0
+IMPARTIALLY  IH0 M - P AA1 R - SH AH0 - L IY0
+IMPARTING  IH0 M - P AA1 R - T IH0 NG
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+IMPASSABLE  IH0 M - P AE1 - S AH0 - B AH0 L
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+IMPASSE(2)  IH1 M - P AE2 S
+IMPASSION  IH0 M - P AE1 - SH AH0 N
+IMPASSIONED  IH0 M - P AE1 - SH AH0 N D
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+IMPATIENCE  IH0 M - P EY1 - SH AH0 N S
+IMPATIENS  IH0 M - P EY1 - SH AH0 N Z
+IMPATIENT  IH0 M - P EY1 - SH AH0 N T
+IMPATIENTLY  IH0 M - P EY1 - SH AH0 N T - L IY0
+IMPEACH  IH0 M - P IY1 CH
+IMPEACHABLE  IH0 M - P IY1 - CH AH0 - B AH0 L
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+IMPEACHING  IH0 M - P IY1 - CH IH0 NG
+IMPEACHMENT  IH0 M - P IY1 CH - M AH0 N T
+IMPEACHMENTS  IH0 M - P IY1 CH - M AH0 N T S
+IMPECCABLE  IH0 M - P EH1 - K AH0 - B AH0 L
+IMPECCABLY  IH0 M - P EH1 - K AH0 - B L IY0
+IMPEDANCE  IH0 M - P IY1 - D AH0 N S
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+IMPEDIMENT  IH0 M - P EH1 - D AH0 - M AH0 N T
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+IMPEDING  IH0 M - P IY1 - D IH0 NG
+IMPEL  IH0 M - P EH1 L
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+IMPENDING  IH0 M - P EH1 N - D IH0 NG
+IMPENETRABLE  IH0 M - P EH1 - N AH0 - T R AH0 - B AH0 L
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+IMPERATIVES  IH0 M - P EH1 - R AH0 - T IH0 V Z
+IMPERATO  IH0 M - P ER0 - AA1 - T OW0
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+IMPERFECTIONS  IH2 M - P ER0 - F EH1 K - SH AH0 N Z
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+IMPERIA  IH0 M - P IY1 - R IY0 - AH0
+IMPERIAL  IH0 M - P IH1 - R IY0 - AH0 L
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+IMPERIALE  IH0 M - P ER0 - IY0 - AA1 - L IY0
+IMPERIALISM  IH0 M - P IH1 - R IY0 - AH0 - L IH2 - Z AH0 M
+IMPERIALIST  IH0 M - P IH1 - R IY0 - AH0 - L IH0 S T
+IMPERIALISTIC  IH0 M - P IY2 - R IY0 - AH0 - L IH1 - S T IH0 K
+IMPERIALISTS  IH0 M - P IH1 - R IY0 - AH0 - L IH0 S T S
+IMPERIALISTS(2)  IH0 M - P IH1 - R IY0 - AH0 - L IH0 S S
+IMPERIALISTS(3)  IH0 M - P IH1 - R IY0 - AH0 - L IH0 S
+IMPERIL  IH0 M - P EH1 - R AH0 L
+IMPERILED  IH0 M - P EH1 - R AH0 L D
+IMPERILING  IH0 M - P EH1 - R AH0 - L IH0 NG
+IMPERILS  IH0 M - P EH1 - R AH0 L Z
+IMPERIOUS  IH0 M - P IH1 - R IY0 - AH0 S
+IMPERMISSIBLE  IH2 M - P ER0 - M IH1 - S IH0 - B AH0 L
+IMPERSONAL  IH0 M - P ER1 - S AH0 - N AH0 L
+IMPERSONALITY  IH0 M - P ER2 - S AH0 - N AE1 - L AH0 - T IY0
+IMPERSONATE  IH0 M - P ER1 - S AH0 - N EY2 T
+IMPERSONATED  IH0 M - P ER1 - S AH0 - N EY2 - T IH0 D
+IMPERSONATING  IH0 M - P ER1 - S AH0 - N EY2 - T IH0 NG
+IMPERSONATION  IH2 M - P ER0 - S AH0 - N EY1 - SH AH0 N
+IMPERSONATOR  IH0 M - P ER1 - S AH0 - N EY0 - T ER0
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+IMPERTINENT  IH0 M - P ER1 - T AH0 - N AH0 N T
+IMPERVIOUS  IH0 M - P ER1 - V IY0 - AH0 S
+IMPETUOUS  IH0 M - P EH1 - CH W AH0 S
+IMPETUS  IH1 M - P AH0 - T AH0 S
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+IMPINGES  IH0 M - P IH1 N - JH IH0 Z
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+IMPLEMENT  IH1 M - P L AH0 - M AH0 N T
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+IMPLY  IH0 M - P L AY1
+IMPLYING  IH0 M - P L AY1 - IH0 NG
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+IMPONDERABLES  IH0 M - P AA1 N - D ER0 - AH0 - B AH0 L Z
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+IMPORTATION  IH2 M - P AO0 R - T EY1 - SH AH0 N
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+IMPORTING  IH0 M - P AO1 R - T IH0 NG
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+IMPOSE  IH0 M - P OW1 Z
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+IMPOSING  IH0 M - P OW1 - Z IH0 NG
+IMPOSITION  IH2 M - P AH0 - Z IH1 - SH AH0 N
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+IMPOTENT  IH1 M - P AH0 - T AH0 N T
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+IMPOUNDMENTS  IH0 M - P AW1 N D - M AH0 N T S
+IMPOVERISH  IH0 M - P AA1 - V R IH0 SH
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+IMPRACTICABLE  IH0 M - P R AE1 K - T IH0 - K AH0 - B AH0 L
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+IMPREGNATION  IH0 M - P R EH1 G - N EY1 - SH AH0 N
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+IMPRISONMENT  IH0 M - P R IH1 - Z AH0 N - M AH0 N T
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+IMPROPRIETY  IH2 M - P R AH0 - P R AY1 - AH0 - T IY0
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+IMPROVES  IH0 M - P R UW1 V Z
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+IMPROVISED  IH1 M - P R AH0 - V AY2 Z D
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+IMPRUDENCE  IH0 M - P R UW1 - D AH0 N S
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+IMPSON  IH1 M P - S AH0 N
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+IMPUGNED  IH0 M - P Y UW1 N D
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+IMPULSE  IH1 M - P AH0 L S
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+IMPULSES  IH1 M - P AH0 L - S IH0 Z
+IMPULSES(2)  IH0 M - P AH1 L - S IH0 Z
+IMPULSIVE  IH0 M - P AH1 L - S IH0 V
+IMPULSIVELY  IH0 M - P AH1 L - S IH0 V - L IY0
+IMPUNITY  IH0 M - P Y UW1 - N IH0 - T IY0
+IMPURE  IH0 M - P Y UH1 R
+IMPURITIES  IH0 M - P Y UH1 - R AH0 - T IY0 Z
+IMPURITY  IH0 M - P Y UH1 - R AH0 - T IY0
+IMPUTATION  IH2 M - P Y AH0 - T EY1 - SH AH0 N
+IMPUTE  IH0 M - P Y UW1 T
+IMPUTED  IH0 M - P Y UW1 - T IH0 D
+IMRE  IH1 - M R AH0
+IMREG  IH2 M - R EH1 G
+IMREG'S  IH2 M - R EH1 G Z
+IMRIE  IH1 - M ER0 - IY0
+IMUS  AY1 - M AH0 S
+IN  IH0 N
+IN(2)  IH1 N
+IN.  IH1 N
+IN.(2)  IH1 N CH
+INA  IY1 - N AH0
+INABILITY  IH2 N - AH0 - B IH1 - L IH0 - T IY0
+INABINET  IH0 N - AH0 - B IH1 - N IH0 T
+INACCESSIBILITY  IH2 N - AH0 K - S EH2 - S AH0 - B IH1 - L AH0 - T IY0
+INACCESSIBLE  IH2 N - AH0 K - S EH1 - S AH0 - B AH0 L
+INACCURACIES  IH0 N - AE1 - K Y ER0 - AE2 - S IY0 Z
+INACCURACY  IH0 N - AE1 - K Y ER0 - AH0 - S IY0
+INACCURATE  IH0 N - AE1 - K Y ER0 - AH0 T
+INACCURATELY  IH0 N - AE1 - K Y ER0 - AH0 T - L IY0
+INACOM  IH1 N - AH0 - K AA2 M
+INACOM(2)  AY1 - N AH0 - K AA2 M
+INACOMP  AY1 - N AH0 - K AA2 M P
+INACOMP(2)  IH1 N - AH0 - K AA2 M P
+INACTION  IH0 N - AE1 K - SH AH0 N
+INACTIVATE  IH0 N - AE1 K - T IH0 - V EY2 T
+INACTIVATED  IH0 N - AE1 K - T IH0 - V EY2 - T IH0 D
+INACTIVATION  IH0 N - AE2 K - T IH0 - V EY1 - SH AH0 N
+INACTIVE  IH0 N - AE1 K - T IH0 V
+INACTIVITY  IH0 N - AE0 K - T IH1 - V IH0 - T IY0
+INADEQUACIES  IH0 N - AE1 - D AH0 - K W AH0 - S IY0 Z
+INADEQUACY  IH0 N - AE1 - D IH0 - K W AH0 - S IY0
+INADEQUATE  IH0 N - AE1 - D AH0 - K W AH0 T
+INADEQUATE(2)  IH0 N - AE1 - D AH0 - K W EY2 T
+INADEQUATELY  IH0 N - AE1 - D AH0 - K W AH0 T - L IY0
+INADMISSIBLE  IH0 N - AH0 D - M IH1 - S AH0 - B AH0 L
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+INADVERTENCE  IH2 N - AH0 D - V ER1 - T AH0 N S
+INADVERTENCE(2)  IH2 N - AE0 D - V ER1 - T AH0 N S
+INADVERTENT  IH2 N - AH0 D - V ER1 - T AH0 N T
+INADVERTENT(2)  IH2 N - AE0 D - V ER1 - T AH0 N T
+INADVERTENTLY  IH2 N - AH0 D - V ER1 - T AH0 N T - L IY0
+INADVERTENTLY(2)  IH2 N - AE0 D - V ER1 - T AH0 N T - L IY0
+INADVISABLE  IH0 N - AH0 D - V AY1 - Z AH0 - B AH0 L
+INADVISABLE(2)  IH0 N - AE0 D - V AY1 - Z AH0 - B AH0 L
+INAEZ  IH2 N - AE1 Z
+INAEZ(2)  IH2 - N EY1 Z
+INALIENABLE  IH0 N - EY1 - L Y AH0 - N AH0 - B AH0 L
+INAMURA  IH2 - N AH0 - M UH1 - R AH0
+INANE  IH0 N - EY1 N
+INANIMATE  IH0 N - AE1 - N AH0 - M AH0 T
+INAPPLICABLE  IH0 N - AE1 - P L IH0 - K AH0 - B AH0 L
+INAPPROPRIATE  IH2 N - AH0 - P R OW1 - P R IY0 - IH0 T
+INAPPROPRIATELY  IH0 N - AH0 - P R AA1 - P R IY0 - AH0 T - L IY0
+INARTICULATE  IH0 N - AA0 R - T IH1 - K Y AH0 - L AH0 T
+INASMUCH  IH0 N - AE1 S - M AH0 K
+INATTENTION  IH0 N - AH0 - T EH1 N - CH AH0 N
+INATTENTIVE  IH2 N - AH0 - T EH1 N - T IH0 V
+INAUDIBLE  IH0 N - AO1 - D AH0 - B AH0 L
+INAUGURAL  IH0 - N AO1 - G ER0 - AH0 L
+INAUGURAL(2)  IH0 - N AO1 - G Y ER0 - AH0 L
+INAUGURATE  IH0 - N AO1 - G Y ER0 - IH0 T
+INAUGURATE(2)  IH0 - N AO1 - G Y ER0 - EY0 T
+INAUGURATED  IH0 - N AO1 - G ER0 - EY2 - T IH0 D
+INAUGURATED(2)  IH0 - N AO1 - G Y ER0 - EY2 - T IH0 D
+INAUGURATES  IH0 - N AO1 - G Y ER0 - IH0 T S
+INAUGURATING  IH0 - N AO1 - G Y ER0 - EY2 - T IH0 NG
+INAUGURATION  IH0 - N AO2 - G Y ER0 - EY1 - SH AH0 N
+INAUGURATIONS  IH0 - N AO2 - G Y ER0 - EY1 - SH AH0 N Z
+INAUSPICIOUS  IH0 N - AW2 - S P IH1 - SH IH0 S
+INBIO  IH0 N - B AY1 - OW0
+INBOARD  IH1 N - B AO2 R D
+INBODEN  IH1 N - B OW0 - D AH0 N
+INBODY  IH1 N - B AA0 - D IY0
+INBORN  IH1 N - B AO2 R N
+INBOUND  IH0 N - B AW1 N D
+INBOUND(2)  IH1 N - B AW0 N D
+INBRED  IH1 N - B R EH2 D
+INBREED  IH1 N - B R IY2 D
+INBREEDING  IH2 N - B R IY1 - D IH0 NG
+INC  IH1 NG K
+INC.  IH1 NG K
+INC.'S  IH1 NG K S
+INC.(2)  IH0 NG - K AO1 R - P AO0 - R EY0 - T AH0 D
+INCA  IH1 NG - K AH0
+INCALCULABLE  IH0 N - K AE1 L - K Y AH0 - L AH0 - B AH0 L
+INCANDESCENT  IH2 N - K AH0 N - D EH1 - S AH0 N T
+INCANT  IH0 N - K AE1 N T
+INCANTATION  IH0 N - K AE1 N - T EY1 - SH AH0 N
+INCANTATORY  IH0 N - K AE1 N - T AH0 - T AO2 - R IY0
+INCAPABLE  IH0 N - K EY1 - P AH0 - B AH0 L
+INCAPACITATE  IH0 N - K AH0 - P AE1 - S IH0 - T EY2 T
+INCAPACITATED  IH0 N - K AH0 - P AE1 - S IH0 - T EY2 - T IH0 D
+INCAPACITATING  IH0 N - K AH0 - P AE1 - S IH0 - T EY2 - T IH0 NG
+INCAPACITATION  IH0 N - K AH0 - P AE2 - S IH0 - T EY1 - SH AH0 N
+INCAPACITY  IH0 N - K AH0 - P AE1 - S AH0 - T IY0
+INCARCERATE  IH0 N - K AA1 R - S ER0 - EY2 T
+INCARCERATED  IH0 N - K AA1 R - S ER0 - EY2 - T IH0 D
+INCARCERATING  IH0 N - K AA1 R - S ER0 - EY2 - T IH0 NG
+INCARCERATION  IH0 N - K AA2 R - S ER0 - EY1 - SH AH0 N
+INCARNATE  IH0 N - K AA1 R - N AH0 T
+INCARNATE(2)  IH0 N - K AA1 R - N EY2 T
+INCARNATION  IH0 N - K AA1 R - N EY1 - SH AH0 N
+INCARNATIONS  IH0 N - K AA0 R - N EY1 - SH AH0 N Z
+INCAS  IH1 NG - K AH0 Z
+INCASE  IH0 N - K EY1 S
+INCATA  IH0 NG - K AA1 - T AH0
+INCATA'S  IH0 NG - K AA1 - T AH0 Z
+INCE  IH1 N S
+INCENDIARY  IH0 N - S EH1 N - D IY0 - EH0 - R IY0
+INCENSE  IH0 N - S EH1 N S
+INCENSE(2)  IH1 N - S EH2 N S
+INCENSED  IH1 N - S EH2 N S T
+INCENTIVE  IH0 N - S EH1 N - T IH0 V
+INCENTIVE(2)  IH0 N - S EH1 - N IH0 V
+INCENTIVES  IH0 N - S EH1 N - T IH0 V Z
+INCENTIVES(2)  IH0 N - S IH1 - N IH0 V Z
+INCEPTION  IH0 N - S EH1 P - SH AH0 N
+INCESSANT  IH0 N - S EH1 - S AH0 N T
+INCESSANTLY  IH0 N - S EH1 - S AH0 N T - L IY0
+INCEST  IH1 N - S EH2 S T
+INCESTUOUS  IH0 N - S EH1 - S CH W AH0 S
+INCH  IH1 N CH
+INCHCAPE  IH1 N - CH K EY2 P
+INCHED  IH1 N CH T
+INCHES  IH1 N - CH AH0 Z
+INCHES'  IH1 N - CH AH0 Z
+INCHES'(2)  IH1 N - CH IH0 Z
+INCHES(2)  IH1 N - CH IH0 Z
+INCHING  IH1 N - CH IH0 NG
+INCHON  IH1 N - CH AH0 N
+INCHON(2)  IH1 N - CH AA0 N
+INCIDENCE  IH1 N - S AH0 - D AH0 N S
+INCIDENCE(2)  IH1 N - S IH0 - D AH0 N S
+INCIDENCES  IH1 N - S AH0 - D AH0 N - S IH0 Z
+INCIDENT  IH1 N - S AH0 - D AH0 N T
+INCIDENTAL  IH2 N - S IH0 - D EH1 N - T AH0 L
+INCIDENTALLY  IH2 N - S IH0 - D EH1 N - T AH0 - L IY0
+INCIDENTALLY(2)  IH2 N - S IH0 - D EH1 N T - L IY0
+INCIDENTALS  IH2 N - S IH0 - D EH1 N - T AH0 L Z
+INCIDENTS  IH1 N - S AH0 - D AH0 N T S
+INCINERATE  IH0 N - S IH1 - N ER0 - EY2 T
+INCINERATED  IH0 N - S IH1 - N ER0 - EY2 - T IH0 D
+INCINERATING  IH0 N - S IH1 - N ER0 - EY2 - T IH0 NG
+INCINERATION  IH0 N - S IH1 - N ER0 - EY2 - SH AH0 N
+INCINERATOR  IH0 N - S IH1 - N ER0 - EY2 - T ER0
+INCINERATORS  IH0 N - S IH1 - N ER0 - EY2 - T ER0 Z
+INCIPIENT  IH0 N - S IH1 - P IY0 - AH0 N T
+INCIRLIK  IH0 N - S ER1 - L IH0 K
+INCISE  IH0 N - S AY1 Z
+INCISED  IH0 N - S AY1 Z D
+INCISION  IH0 N - S IH1 - ZH AH0 N
+INCISIONS  IH0 N - S IH1 - ZH AH0 N Z
+INCISIVE  IH0 N - S AY1 - S IH0 V
+INCISOR  IH0 N - S AY1 - Z ER0
+INCISORS  IH0 N - S AY1 - Z ER0 Z
+INCITE  IH0 N - S AY1 T
+INCITED  IH0 N - S AY1 - T IH0 D
+INCITEMENT  IH0 N - S AY1 T - M AH0 N T
+INCITEMENTS  IH0 N - S AY1 T - M AH0 N T S
+INCITES  IH0 N - S AY1 T S
+INCITING  IH0 N - S AY1 - T IH0 NG
+INCIVILITY  IH0 N - S IH0 - V IH1 - L IH0 - T IY0
+INCLEMENT  IH0 N - K L EH1 - M AH0 N T
+INCLEMENT(2)  IH1 N - K L IH0 - M AH0 N T
+INCLINATION  IH2 N - K L AH0 - N EY1 - SH AH0 N
+INCLINATIONS  IH2 N - K L AH0 - N EY1 - SH AH0 N Z
+INCLINE  IH0 N - K L AY1 N
+INCLINE(2)  IH1 N - K L AY0 N
+INCLINED  IH0 N - K L AY1 N D
+INCLINES  IH0 N - K L AY1 N Z
+INCLINES(2)  IH1 N - K L AY0 N Z
+INCLOSURE  IH0 N - K L OW1 - ZH ER0
+INCLUDE  IH0 N - K L UW1 D
+INCLUDED  IH0 N - K L UW1 - D AH0 D
+INCLUDED(2)  IH0 N - K L UW1 - D IH0 D
+INCLUDES  IH0 N - K L UW1 D Z
+INCLUDING  IH0 N - K L UW1 - D IH0 NG
+INCLUSION  IH0 N - K L UW1 - ZH AH0 N
+INCLUSIONS  IH0 N - K L UW1 - ZH AH0 N Z
+INCLUSIVE  IH0 N - K L UW1 - S IH0 V
+INCLUSIVENESS  IH0 N - K L UW1 - S IH0 V - N IH0 S
+INCLUSIVENESS(2)  IH0 N - K L UW1 - S IH0 V - N EH0 S
+INCO  IH2 N - K OW1
+INCO'S  IH1 NG - K OW0 Z
+INCOGNITO  IH0 N - K AO0 G - N IY1 - T OW0
+INCOHERENCE  IH0 N - K OW0 - HH IH1 - R AH0 N S
+INCOHERENT  IH0 N - K OW0 - HH IH1 - R AH0 N T
+INCOHERENTLY  IH0 N - K OW0 - HH IH1 - R AH0 N T - L IY0
+INCOM  IH1 NG - K AA0 M
+INCOME  IH1 N - K AH2 M
+INCOMES  IH1 N - K AH2 M Z
+INCOMING  IH1 N - K AH2 - M IH0 NG
+INCOMMUNICADO  IH2 N - K AH0 - M Y UW2 - N AH0 - K AA1 - D OW0
+INCOMPARABLE  IH0 N - K AA1 M - P ER0 - AH0 - B AH0 L
+INCOMPARABLY  IH0 N - K AA1 M - P ER0 - AH0 - B L IY0
+INCOMPATIBILITY  IH0 N - K AA2 M - P AH0 - T IH0 - B IH1 - L IH0 - T IY0
+INCOMPATIBLE  IH0 N - K AH0 M - P AE1 - T AH0 - B AH0 L
+INCOMPETENCE  IH0 N - K AA1 M - P AH0 - T AH0 N S
+INCOMPETENCY  IH0 N - K AA1 M - P AH0 - T AH0 N - S IY0
+INCOMPETENT  IH0 N - K AA1 M - P AH0 - T AH0 N T
+INCOMPETENTLY  IH0 N - K AA1 M - P AH0 - T AH0 N T - L IY0
+INCOMPETENTS  IH0 NG - K AA1 M - P AH0 - T AH0 N T S
+INCOMPLETE  IH0 N - K AH0 M - P L IY1 T
+INCOMPREHENSIBLE  IH0 NG - K AA2 M - P R AH0 - HH EH1 N - S IH0 - B AH0 L
+INCOMPRESSIBLE  IH0 N - K AH0 M - P R EH1 - S AH0 - B AH0 L
+INCONCEIVABLE  IH2 N - K AH0 N - S IY1 - V AH0 - B AH0 L
+INCONCLUSIVE  IH0 N - K AH0 N - K L UW1 - S IH0 V
+INCONCLUSIVELY  IH0 NG - K AA1 N - K L UW0 - S IH0 V - L IY0
+INCONGRUITY  IH2 NG - K AO0 NG - R UW1 - IH0 - T IY0
+INCONGRUOUS  IH0 NG - K AO1 NG - R UW0 - AH0 S
+INCONGRUOUSLY  IH0 NG - K AO1 NG - R UW0 - AH0 S - L IY0
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+INCONSISTENCIES  IH0 NG - K AA1 N - S IH0 - S T EH2 N - S IY0 Z
+INCONSISTENCY  IH2 N - K AH0 N - S IH1 - S T AH0 N - S IY0
+INCONSISTENT  IH2 N - K AH0 N - S IH1 - S T AH0 N T
+INCONSPICUOUS  IH0 NG - K AA1 N - S P IH0 - K W AH0 S
+INCONSTANCY  IH0 N - K AA1 N - S T AH0 N - S IY0
+INCONTINENCE  IH0 N - K AA1 N - T AH0 - N AH0 N S
+INCONTINENT  IH0 N - K AA1 N - T AH0 - N AH0 N T
+INCONTROVERTIBLE  IH0 NG - K AA2 N - T R OW0 - V ER1 - T IH0 - B AH0 L
+INCONVENIENCE  IH2 N - K AH0 N - V IY1 - N Y AH0 N S
+INCONVENIENCED  IH2 N - K AH0 N - V IY1 - N Y AH0 N S T
+INCONVENIENCES  IH2 N - K AH0 N - V IY1 - N Y AH0 N - S IH0 Z
+INCONVENIENT  IH2 N - K AH0 N - V IY1 - N Y AH0 N T
+INCOORDINATION  IH0 N - K OW1 - AO1 R - D AH0 N - EY1 - SH AH0 N
+INCORPORATE  IH0 N - K AO1 R - P ER0 - EY2 T
+INCORPORATED  IH0 N - K AO1 R - P ER0 - EY2 - T AH0 D
+INCORPORATED'S  IH0 N - K AO1 R - P ER0 - EY2 - T IH0 D Z
+INCORPORATED(2)  IH0 N - K AO1 R - P ER0 - EY2 - T IH0 D
+INCORPORATES  IH0 N - K AO1 R - P ER0 - EY2 T S
+INCORPORATING  IH0 N - K AO1 R - P ER0 - EY2 - T IH0 NG
+INCORPORATION  IH0 N - K AO2 R - P ER0 - EY1 - SH AH0 N
+INCORPORATION'S  IH0 N - K AO2 R - P ER0 - EY1 - SH AH0 N Z
+INCORPORATIONS  IH0 N - K AO2 R - P ER0 - EY1 - SH AH0 N Z
+INCORRECT  IH0 N - K ER0 - EH1 K T
+INCORRECTLY  IH0 N - K ER0 - EH1 K T - L IY0
+INCORRIGIBLE  IH0 N - K AA1 - R AH0 - JH AH0 - B AH0 L
+INCORVAIA  IH0 N - K AO0 R - V AA1 - Y AH0
+INCREASE  IH0 N - K R IY1 S
+INCREASE(2)  IH1 N - K R IY2 S
+INCREASED  IH0 N - K R IY1 S T
+INCREASED(2)  IH1 N - K R IY2 S T
+INCREASES  IH0 N - K R IY1 - S AH0 Z
+INCREASES(2)  IH0 N - K R IY1 - S IH0 Z
+INCREASES(3)  IH1 N - K R IY0 - S AH0 Z
+INCREASING  IH0 N - K R IY1 - S IH0 NG
+INCREASINGLY  IH0 N - K R IY1 - S IH0 NG - L IY0
+INCREASINGLY(2)  IH0 N - K R IY1 - S IH0 NG - G L IY0
+INCREDIBLE  IH0 N - K R EH1 - D AH0 - B AH0 L
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+INCREDULITY  IH2 N - K R AH0 - D UW1 - L IH0 - T IY0
+INCREDULOUS  IH0 N - K R EH1 - JH AH0 - L AH0 S
+INCREMENT  IH1 N - K R AH0 - M AH0 N T
+INCREMENTAL  IH2 N - K R AH0 - M EH1 N - T AH0 L
+INCREMENTAL(2)  IH2 N - K R AH0 - M EH1 - N AH0 L
+INCREMENTALISM  IH2 N - K R AH0 - M EH1 N - T AH0 - L IH0 Z M
+INCREMENTALISM(2)  IH2 N - K R AH0 - M EH1 - N AH0 - L IH0 Z M
+INCREMENTALLY  IH0 N - K R AH0 - M EH1 N - T AH0 - L IY0
+INCREMENTALLY(2)  IH0 N - K R AH0 - M EH1 - N AH0 - L IY0
+INCREMENTS  IH1 NG - K R AH0 - M AH0 N T S
+INCRIMINATE  IH0 N - K R IH1 - M AH0 - N EY2 T
+INCRIMINATING  IH0 N - K R IH1 - M AH0 - N EY2 - T IH0 NG
+INCRIMINATION  IH0 N - K R IH2 - M AH0 - N EY1 - SH AH0 N
+INCRUST  IH0 N - K R AH1 S T
+INCRUSTATION  IH2 N - K R AH0 - S T EY1 - SH AH0 N
+INCSTAR  IH1 NG K - S T AA2 R
+INCUBATE  IH1 N - K Y AH0 - B EY2 T
+INCUBATING  IH1 N - K Y AH0 - B EY2 - T IH0 NG
+INCUBATION  IH2 NG - K Y UW0 - B EY1 - SH AH0 N
+INCUBATOR  IH1 NG - K Y AH0 - B EY2 - T ER0
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+INCULCATE  IH1 NG - K AH0 L - K EY2 T
+INCULCATED  IH1 NG - K AH0 L - K EY2 - T AH0 D
+INCULCATES  IH1 NG - K AH0 L - K EY2 T S
+INCUMBENCY  IH0 N - K AH1 M - B AH0 N - S IY0
+INCUMBENT  IH0 N - K AH1 M - B AH0 N T
+INCUMBENT'S  IH0 N - K AH1 M - B AH0 N T S
+INCUMBENTS  IH0 N - K AH1 M - B AH0 N T S
+INCUR  IH0 N - K ER1
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+INCURRED  IH0 N - K ER1 D
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+INDECENCY  IH0 N - D IY1 - S AH0 N - S IY0
+INDECENT  IH0 N - D IY1 - S AH0 N T
+INDECISION  IH0 N - D IH0 - S IH1 - ZH AH0 N
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+INDEED  IH0 N - D IY1 D
+INDEFATIGABLE  IH2 N - D IH0 - F AE1 - T IH0 - G AH0 - B AH0 L
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+INDEFINABLE  IH0 N - D IH0 - F AY1 - N AH0 - B AH0 L
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+INDELIBLE  IH0 N - D EH1 - L IH0 - B AH0 L
+INDELIBLY  IH0 N - D EH1 - L AH0 - B L IY0
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+INDELICATO  IH0 N - D EH0 - L IY0 - K AA1 - T OW0
+INDEMNIFICATION  IH0 N - D EH2 M - N AH0 - F IH0 - K EY1 - SH AH0 N
+INDEMNIFIED  IH0 N - D EH1 M - N AH0 - F AY2 D
+INDEMNIFY  IH0 N - D EH1 M - N AH0 - F AY2
+INDEMNIFYING  IH0 N - D EH2 M - N IH0 - F AY1 - IH0 NG
+INDEMNITIES  IH0 N - D EH1 M - N IH0 - T IY0 Z
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+INDENT  IH0 N - D EH1 N T
+INDENTATION  IH0 N - D EH2 N - T EY1 - SH AH0 N
+INDENTURE  IH0 N - D EH1 N - CH ER0
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+INDEPENDENCE  IH2 N - D IH0 - P EH1 N - D AH0 N S
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+INDEPENDENT  IH2 N - D IH0 - P EH1 N - D AH0 N T
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+INDERAL  IH1 N - D ER0 - AH0 L
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+INDEX  IH1 N - D EH0 K S
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+INDEXATION  IH1 N - D EH2 K - S EY1 - SH AH0 N
+INDEXED  IH1 N - D EH0 K S T
+INDEXER  IH1 N - D EH2 K - S ER0
+INDEXERS  IH1 N - D EH2 K - S ER0 Z
+INDEXES  IH1 N - D EH0 K - S IH0 Z
+INDEXING  IH1 N - D EH0 K - S IH0 NG
+INDIA  IH1 N - D IY0 - AH0
+INDIA'S  IH1 N - D IY0 - AH0 Z
+INDIAN  IH1 N - D IY0 - AH0 N
+INDIAN'S  IH1 N - D IY0 - AH0 N Z
+INDIANA  IH2 N - D IY0 - AE1 - N AH0
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+INDIANAPOLIS  IH2 N - D IY0 - AH0 N - AE1 - P AH0 - L IH0 S
+INDIANAPOLIS'S  IH2 N - D IY0 - AH0 N - AE1 - P AH0 - L IH0 - S IH0 Z
+INDIANIAN  IH2 N - D IY0 - AE1 - N IY0 - AH0 N
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+INDIANOLA  IH1 N - D IY0 - AH0 - N OW1 - L AH0
+INDIANS  IH1 N - D IY0 - AH0 N Z
+INDIANS'  IH1 N - D IY0 - AH0 N Z
+INDIC  IH1 N - D IH0 K
+INDICATE  IH1 N - D AH0 - K EY2 T
+INDICATED  IH1 N - D AH0 - K EY2 - T AH0 D
+INDICATED(2)  IH1 N - D AH0 - K EY2 - T IH0 D
+INDICATES  IH1 N - D IH0 - K EY2 T S
+INDICATING  IH1 N - D AH0 - K EY2 - T IH0 NG
+INDICATION  IH2 N - D AH0 - K EY1 - SH AH0 N
+INDICATIONS  IH2 N - D AH0 - K EY1 - SH AH0 N Z
+INDICATIVE  IH0 N - D IH1 - K AH0 - T IH0 V
+INDICATOR  IH1 N - D AH0 - K EY2 - T ER0
+INDICATORS  IH1 N - D AH0 - K EY2 - T ER0 Z
+INDICES  IH1 N - D IH0 - S IY2 Z
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+INDICIA  IH0 N - D IH1 S - Y AH0
+INDICT  IH0 N - D AY1 T
+INDICTED  IH0 N - D AY1 - T AH0 D
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+INDICTING  IH0 N - D AY1 - T IH0 NG
+INDICTMENT  IH0 N - D AY1 T - M AH0 N T
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+INDIES  IH1 N - D IY0 Z
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+INDIFFERENCE(2)  IH0 N - D IH1 - F R AH0 N S
+INDIFFERENT  IH0 N - D IH1 - F R AH0 N T
+INDIFFERENT(2)  IH0 N - D IH1 - F ER0 - AH0 N T
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+INDIGENTS  IH1 N - D IH0 - JH AH0 N T S
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+INDIGNITY  IH0 N - D IH1 G - N AH0 - T IY0
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+INDIRECT  IH0 N - D ER0 - EH1 K T
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+INDISCREET  IH0 N - D IH0 - S K R IY1 T
+INDISCRETION  IH2 N - D IH0 - S K R EH1 - SH AH0 N
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+INDISCRIMINATE  IH0 N - D IH0 - S K R IH1 - M AH0 - N AH0 T
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+INDISTINCT  IH0 N - D IH0 - S T IH1 NG K T
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+INDITED  IH0 N - D AY1 - T IH0 D
+INDIUM  IH1 N - D IY0 - AH0 M
+INDIVIDUAL  IH2 N - D AH0 - V IH1 - JH AH0 - W AH0 L
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+INDIVIDUALIST  IH2 N - D IH0 - V IH0 - D UW1 - AH0 - L IH0 S T
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+INDIVIDUALISTS(3)  IH2 N - D AH0 - V IH1 - JH UW0 - AH0 - L IH0 S
+INDIVIDUALITY  IH0 N - D IH2 - V IH0 - JH UW0 - AE1 - L IH0 - T IY0
+INDIVIDUALIZE  IH2 N - D IH0 - V IH1 - JH UW0 - AH0 - L AY0 Z
+INDIVIDUALIZE(2)  IH2 N - D IH0 - V IH1 - JH AH0 - L AY0 Z
+INDIVIDUALIZED  IH2 N - D IH0 - V IH1 - JH UW0 - AH0 - L AY0 Z D
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+INDIVIDUALLY  IH2 N - D IH0 - V IH1 - JH UW0 - AH0 - L IY0
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+INDIVISIBLE  IH2 N - D IH0 - V IH1 - S IH0 - B AH0 L
+INDO  IH1 N - D OW0
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+INDOCTRINATED  IH0 N - D AA1 K - T R AH0 - N EY2 - T IH0 D
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+INDOLENT  IH1 N - D AH0 - L AH0 N T
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+INDOOR  IH1 N - D AO2 R
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+INDOSUEZ  IH1 N - D OW0 - S UW0 - EY1 Z
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+INDUCING  IH0 N - D UW1 - S IH0 NG
+INDUCT  IH0 N - D AH1 K T
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+INDUCTEE  IH0 N - D AH1 K - T IY1
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+INDUCTION  IH0 N - D AH1 K - SH AH0 N
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+INDULGE  IH0 N - D AH1 L JH
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+INDULGENCE  IH0 N - D AH1 L - JH AH0 N S
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+INDULGES  IH0 N - D AH1 L - JH IH0 Z
+INDULGING  IH0 N - D AH1 L - JH IH0 NG
+INDUS  IH1 N - D AH0 S
+INDUSTRI  IH0 N - D AH1 S - T R IY0
+INDUSTRIA  IH0 N - D AH1 S - T R IY0 - AH0
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+INDUSTRIALE  IH2 N - D AH0 S - T R IY0 - AA1 - L IY0
+INDUSTRIALI  IH0 N - D AH2 S - T R IY0 - AA1 - L IY0
+INDUSTRIALIST  IH0 N - D AH1 S - T R IY0 - AH0 - L IH0 S T
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+INDUSTRIALIZATION  IH0 N - D AH2 S - T R IY0 - AH0 - L IH0 - Z EY1 - SH AH0 N
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+INDUSTRIALIZING  IH0 N - D AH1 S - T R IY0 - AH0 - L AY2 - Z IH0 NG
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+INDUSTRIALS  IH0 N - D AH1 S - T R IY0 - AH0 L Z
+INDUSTRIALS'  IH0 N - D AH1 S - T R IY0 - AH0 L Z
+INDUSTRIE  IH1 N - D AH0 S - T R IY0
+INDUSTRIELLE  IH0 N - D AH2 S - T R IY0 - EH1 L
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+INDUSTRIER  IH1 N - D AH0 S - T R IY2 - ER0
+INDUSTRIES  IH1 N - D AH0 S - T R IY0 Z
+INDUSTRIES'  IH1 N - D AH0 S - T R IY0 Z
+INDUSTRIOUS  IH0 N - D AH1 S - T R IY0 - AH0 S
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+INDUSTRY'S  IH1 N - D AH0 S - T R IY0 Z
+INDUSTRYWIDE  IH1 N - D AH0 S - T R IY0 - W AY2 D
+INDY  IH1 N - D IY0
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+INEVITABLE  IH0 N - EH1 - V AH0 - T AH0 - B AH0 L
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+INEXACT  IH0 N - IH0 G - Z AE1 K T
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+MICROSYSTEMS  M AY1 - K R OW2 - S IH1 - S T AH0 M Z
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+MIRABITO  M IH0 - R AA0 - B IY1 - T OW0
+MIRACID  M IH2 - R AE1 - S AH0 D
+MIRACID'S  M IH2 - R AE1 - S AH0 D Z
+MIRACLE  M IH1 - R AH0 - K AH0 L
+MIRACLES  M IH1 - R AH0 - K AH0 L Z
+MIRACULOUS  M ER0 - AE1 - K Y AH0 - L AH0 S
+MIRACULOUSLY  M ER0 - AE1 - K Y AH0 - L AH0 S - L IY0
+MIRAD  M AH0 - R AE1 D
+MIRADA  M IH0 - R AA1 - D AH0
+MIRAGE  M ER0 - AA1 ZH
+MIRAGES  M ER0 - AA1 - ZH AH0 Z
+MIRAGLIA  M IH0 - R AE1 - G L IY0 - AH0
+MIRAK  M IH1 - R AE0 K
+MIRAMAR  M IH1 - R AH0 - M AA2 R
+MIRAMAX  M IH1 - R AH0 - M AE2 K S
+MIRAMAX'S  M IH1 - R AH0 - M AE2 K - S IH0 Z
+MIRAMONTES  M IH0 - R AA0 - M OW1 N - T EH0 S
+MIRANDA  M ER0 - AE1 N - D AH0
+MIRANDA'S  M ER0 - AE1 N - D AH0 Z
+MIRANDO  M IH0 - R AE1 N D - OW0
+MIRATEC  M IH1 - R AH0 - T EH2 K
+MIRE  M AY1 R
+MIRE(2)  M AY1 - ER0
+MIRED  M AY1 R D
+MIRELES  M IH0 - R EY1 - L EH0 S
+MIRELEZ  M IH0 - R EY1 - L EH0 Z
+MIRELL  M IH0 - R EH1 L
+MIRELLA  M IH0 - R EH1 - L AH0
+MIRELLE  M ER0 - EH1 L
+MIRENDA  M IH0 - R EH1 N - D AH0
+MIRES  M AY1 R Z
+MIRIAM  M IH1 - R IY0 - AH0 M
+MIRICK  M IH1 - R IH0 K
+MIRILLA  M IH0 - R IH1 - L AH0
+MIRKIN  M ER1 - K IH0 N
+MIRNA  M ER1 - N AH0
+MIRO  M IH1 - R OW0
+MIRO'S  M IH1 - R OW0 Z
+MIRO'S(2)  M IH0 - R OW1 Z
+MIRO(2)  M IH0 - R OW1
+MIRON  M IH0 - R AO1 N
+MIRONENKO  M IH2 - R OW0 - N EH1 NG - K OW0
+MIROSLAV  M IH1 - R AH0 - S L AA0 V
+MIRRA  M IH1 - R AH0
+MIRREN  M IH1 - R AH0 N
+MIRROR  M IH1 - R ER0
+MIRROR'S  M IH1 - R ER0 Z
+MIRRORED  M IH1 - R ER0 D
+MIRRORING  M IH1 - R ER0 - IH0 NG
+MIRRORS  M IH1 - R ER0 Z
+MIRSAD  M IH1 R - S AE2 D
+MIRSKY  M ER1 S - K IY0
+MIRTH  M ER1 TH
+MIRTI  M ER1 - T IY0
+MIRTI(2)  M ER1 - T IY2
+MIRTLE  M ER1 - T AH0 L
+MIRTO  M IH1 R - T OW0
+MIRV  M ER1 V
+MIRZA  M ER1 - Z AH0
+MIS  M IH1 S
+MISA  M IY1 - Z AH0
+MISA'S  M IY1 - Z AH0 Z
+MISADVENTURE  M IH0 S - AH0 D - V EH1 N - CH ER0
+MISADVENTURES  M IH0 S - AH0 D - V EH1 N - CH ER0 Z
+MISALLOCATE  M IH0 S - AE1 - L AH0 - K EY2 T
+MISALLOCATED  M IH0 S - AE1 - L AH0 - K EY2 - T IH0 D
+MISALLOCATION  M IH0 S - AE2 - L AH0 - K EY1 - SH AH0 N
+MISANTHROPE  M IH1 - S AH0 N - TH R OW2 P
+MISAPPLICATION  M IH0 S - AE2 - P L AH0 - K EY1 - SH AH0 N
+MISAPPLIED  M IH2 S - AH0 - P L AY1 D
+MISAPPLY  M IH0 S - AH0 - P L AY1
+MISAPPLYING  M IH0 S - AH0 - P L AY1 - IH0 NG
+MISAPPREHENSION  M IH0 S - AE2 - P R IY0 - HH EH1 N - SH AH0 N
+MISAPPROPRIATE  M IH0 S - AH0 - P R OW1 - P R IY0 - EY2 T
+MISAPPROPRIATED  M IH2 S - AH0 - P R OW1 - P R IY0 - EY2 - T IH0 D
+MISAPPROPRIATING  M IH2 S - AH0 - P R OW1 - P R IY0 - EY2 - T IH0 NG
+MISAPPROPRIATION  M IH2 S - AH0 - P R OW2 - P R IY0 - EY1 - SH AH0 N
+MISATER  M IH0 S - EY1 - T ER0
+MISAWA  M IH0 - S AA1 - W AH0
+MISBEGOTTEN  M IH2 S - B AH0 - G AA1 - T AH0 N
+MISBEHAVE  M IH2 S - B AH0 - HH EY1 V
+MISBEHAVE(2)  M IH2 S - B IY0 - HH EY1 V
+MISBEHAVED  M IH2 S - B AH0 - HH EY1 V D
+MISBEHAVED(2)  M IH2 S - B IY0 - HH EY1 V D
+MISBEHAVING  M IH2 S - B AH0 - HH EY1 - V IH0 NG
+MISBEHAVING(2)  M IH2 S - B IY0 - HH EY1 - V IH0 NG
+MISBEHAVIOR  M IH2 S - B AH0 - HH EY1 - V Y ER0
+MISBEHAVIOR(2)  M IH2 S - B IY0 - HH EY1 - V Y ER0
+MISBRENER  M IH1 S - B R EH2 - N ER0
+MISCALCULATE  M IH0 S - K AE1 L - K Y AH0 - L EY2 T
+MISCALCULATED  M IH0 S - K AE1 L - K Y AH0 - L EY2 - T IH0 D
+MISCALCULATION  M IH0 S - K AE1 L - K Y AH0 - L EY1 - SH AH0 N
+MISCALCULATIONS  M IH0 S - K AE1 L - K Y AH0 - L EY1 - SH AH0 N Z
+MISCARRIAGE  M IH0 S - K EH1 - R AH0 JH
+MISCARRIAGES  M IH0 S - K EH1 - R IH0 - JH IH0 Z
+MISCAST  M IH0 S - K AE1 S T
+MISCAVIGE  M IH0 S - K AE1 - V IH1 JH
+MISCAYUNA  M IH2 S - K AY0 - Y UW1 - N AH0
+MISCAYUNA'S  M IH2 S - K AY0 - Y UW1 - N AH0 Z
+MISCELLANEOUS  M IH2 - S AH0 - L EY1 - N IY0 - AH0 S
+MISCELLANY  M IH1 - S AH0 - L EY2 - N IY0
+MISCH  M IH1 SH
+MISCHA  M IH1 - SH AH0
+MISCHARACTERIZATION  M IH0 S - K AE2 - R AH0 K - T ER0 - AH0 - Z EY1 - SH AH0 N
+MISCHARACTERIZE  M IH0 S - K AE1 - R AH0 K - T ER0 - AY2 Z
+MISCHARACTERIZED  M IH0 S - K AE1 - R AH0 K - T ER0 - AY2 Z D
+MISCHARGE  M IH0 S - CH AA1 R JH
+MISCHARGED  M IH0 S - CH AA1 R JH D
+MISCHARGES  M IH0 S - CH AA1 R - JH IH0 Z
+MISCHARGING  M IH0 S - CH AA1 R - JH IH0 NG
+MISCHEL  M IH1 - SH AH0 L
+MISCHER  M IH1 - SH ER0
+MISCHIEF  M IH1 S - CH AH0 F
+MISCHIEVOUS  M IH1 S - CH AH0 - V AH0 S
+MISCHKE  M IH1 SH K
+MISCHLER  M IH1 - SH AH0 L - ER0
+MISCHLER(2)  M IH1 SH - L ER0
+MISCIBILITY  M IH2 S - IH0 - B IH1 - L IH0 - T IY0
+MISCIBLE  M IH1 - S AH0 - B AH0 L
+MISCIBLE(2)  M IH1 - S IH0 - B AH0 L
+MISCOMMUNICATION  M IH0 S - K AH0 - M Y UW2 - N AH0 - K EY1 - SH AH0 N
+MISCONCEIVE  M IH0 S - K AH0 N - S IY1 V
+MISCONCEIVED  M IH0 S - K AH0 N - S IY1 V D
+MISCONCEPTION  M IH0 S - K AH0 N - S EH1 P - SH AH0 N
+MISCONCEPTIONS  M IH0 S - K AH0 N - S EH1 P - SH AH0 N Z
+MISCONDUCT  M IH0 S - K AA1 N - D AH0 K T
+MISCONSTRUE  M IH0 S - K AH0 N - S T R UW1
+MISCONSTRUED  M IH2 S - K AH0 N - S T R UW1 D
+MISCOUNT  M IH1 S - K AW1 N T
+MISCREANT  M IH1 S - K R IY0 - AH0 N T
+MISCREANTS  M IH1 S - K R IY0 - AH0 N T S
+MISCREATION  M IH0 S - K R IY0 - EY1 - SH AH0 N
+MISCREATIONS  M IH2 S - K R IY0 - EY1 - SH AH0 N Z
+MISCUE  M IH1 S - K Y UW2
+MISCUES  M IH1 S - K Y UW2 Z
+MISDEED  M IH1 S - D IY1 D
+MISDEEDS  M IH0 S - D IY1 D Z
+MISDEMEANOR  M IH2 S - D AH0 - M IY1 - N ER0
+MISDEMEANORS  M IH2 S - D AH0 - M IY1 - N ER0 Z
+MISDIAGNOSE  M IH0 S - D AY2 - IH0 G - N OW1 Z
+MISDIAGNOSED  M IH0 S - D AY2 - IH0 G - N OW1 Z D
+MISDIAGNOSES  M IH0 S - D AY2 - IH0 G - N OW1 - S IY0 Z
+MISDIAGNOSES(2)  M IH0 S - D AY2 - IH0 G - N OW1 - S AH0 Z
+MISDIAGNOSIS  M IH0 S - D AY2 - IH0 G - N OW1 - S AH0 S
+MISDIRECT  M IH0 S - D IH0 - R EH1 K T
+MISDIRECTED  M IH0 S - D IH0 - R EH1 K - T IH0 D
+MISEK  M IH1 - S EH0 K
+MISENER  M IH1 - S IY0 - N ER0
+MISENHEIMER  M IH1 S - IH0 N - HH AY0 - M ER0
+MISER  M AY1 - Z ER0
+MISERABLE  M IH1 - Z ER0 - AH0 - B AH0 L
+MISERABLE(2)  M IH1 Z - R AH0 - B AH0 L
+MISERABLES  M IH1 - Z ER0 - AH0 - B AH0 L Z
+MISERABLES(2)  M IH1 Z - R AH0 - B AH0 L Z
+MISERABLES(3)  M IH2 - Z ER0 - AA1 B
+MISERABLY  M IH1 - Z ER0 - AH0 - B L IY0
+MISERABLY(2)  M IH1 Z - R AH0 - B L IY0
+MISERATION  M IH0 - Z ER0 - EY1 - SH AH0 N
+MISERIES  M IH1 - Z ER0 - IY0 Z
+MISERLY  M AY1 - Z ER0 - L IY0
+MISERY  M IH1 - Z ER0 - IY0
+MISES  M AY1 - Z IH0 Z
+MISFELDT  M IH1 S - F IH0 L T
+MISFIRE  M IH0 S - F AY1 - ER0
+MISFIT  M IH1 S - F IH2 T
+MISFITS  M IH1 S - F IH2 T S
+MISFORTUNE  M IH0 S - F AO1 R - CH AH0 N
+MISFORTUNES  M IH0 S - F AO1 R - CH AH0 N Z
+MISGIVE  M IH0 S - G IH1 V
+MISGIVING  M IH0 S - G IH1 - V IH0 NG
+MISGIVINGS  M IH0 S - G IH1 - V IH0 NG Z
+MISGOVERNMENT  M IH0 S - G AH1 - V ER0 N - M AH0 N T
+MISGUIDE  M IH0 S - G AY1 D
+MISGUIDED  M IH0 S - G AY1 - D IH0 D
+MISH  M IH1 SH
+MISHA  M IH1 - SH AH0
+MISHANDLE  M IH0 S - HH AE1 N - D AH0 L
+MISHANDLED  M IH0 S - HH AE1 N - D AH0 L D
+MISHANDLING  M IH0 S - HH AE1 N D - L IH0 NG
+MISHAP  M IH1 S - HH AE2 P
+MISHAPS  M IH1 S - HH AE2 P S
+MISHAWAKA  M IH2 - SH AH0 W - AO1 - K AH0
+MISHAWAUM  M IH1 - SH AH0 W - AA2 M
+MISHAWUM  M IH1 - SH AH0 W - AH2 M
+MISHEAR  M IH0 S - HH IY1 R
+MISHEARD  M IH2 S - HH ER1 D
+MISHKIN  M IY1 SH - K IY0 N
+MISHLER  M IH1 SH - L ER0
+MISHMASH  M IH1 SH - M AE2 SH
+MISHOE  M IY1 - SH UW0
+MISHRA  M IH1 - SH R AH0
+MISIAK  M IH1 - S IY0 - AE0 K
+MISIASZEK  M IH0 - S IY0 - AA1 - SH EH0 K
+MISIDENTIFICATION  M IH2 - S AY0 - D EH2 N - T IH0 - F IH0 - K EY1 - SH AH0 N
+MISIDENTIFICATION(2)  M IH2 - S AY0 - D EH2 - N IH0 - F IH0 - K EY1 - SH AH0 N
+MISIDENTIFIED  M IH0 - S AY0 - D EH1 N - T IH0 - F AY2 D
+MISIDENTIFIED(2)  M IH0 - S AY0 - D EH1 - N IH0 - F AY2 D
+MISIDENTIFY  M IH0 - S AY0 - D EH1 N - T AH0 - F AY2
+MISIDENTIFY(2)  M IH0 - S AY0 - D EH1 - N AH0 - F AY2
+MISIEWICZ  M IH1 S - AH0 - V IH0 CH
+MISIMPRESSION  M IH0 S - IH0 M - P R EH1 - SH AH0 N
+MISINFORM  M IH0 S - IH2 N - F AO1 R M
+MISINFORMATION  M IH2 S - IH0 N - F ER0 - M EY1 - SH AH0 N
+MISINFORMED  M IH0 S - IH0 N - F AO1 R M D
+MISINFORMING  M IH0 S - IH0 N - F AO1 R - M IH0 NG
+MISINTERPRET  M IH0 S - IH0 N - T ER1 - P R AH0 T
+MISINTERPRETATION  M IH0 S - IH0 N - T ER2 - P R AH0 - T EY1 - SH AH0 N
+MISINTERPRETED  M IH0 S - IH0 N - T ER1 - P R AH0 - T IH0 D
+MISINTERPRETING  M IH0 S - IH0 N - T ER1 - P R AH0 - T IH0 NG
+MISJUDGE  M IH0 S - JH AH1 JH
+MISJUDGED  M IH0 S - JH AH1 JH D
+MISJUDGES  M IH0 S - JH AH1 - JH IH0 Z
+MISJUDGMENT  M IH0 S - JH AH1 JH - M AH0 N T
+MISJUDGMENTS  M IH0 S - JH AH1 JH - M AH0 N T S
+MISKA  M IH1 S - K AH0
+MISKE  M IH1 S K
+MISKELL  M IH1 S - K AH0 L
+MISKITO  M IH0 S - K IY1 - T OW0
+MISKITOS  M IH0 S - K IY1 - T OW0 S
+MISKO  M IH1 S - K OW0
+MISLABEL  M IH0 S - L EY1 - B AH0 L
+MISLABELED  M IH0 S - L EY1 - B AH0 L D
+MISLABELING  M IH0 S - L EY1 - B AH0 L - IH0 NG
+MISLABELING(2)  M IH0 S - L EY1 - B L IH0 NG
+MISLAID  M IH0 S - L EY1 D
+MISLEAD  M IH0 S - L IY1 D
+MISLEADING  M IH0 S - L IY1 - D IH0 NG
+MISLEADINGLY  M IH0 S - L IY1 - D IH0 NG - L IY0
+MISLEADS  M IH0 S - L IY1 D Z
+MISLED  M IH0 S - L EH1 D
+MISMANAGE  M IH0 S - M AE1 - N IH0 JH
+MISMANAGED  M IH0 S - M AE1 - N IH0 JH D
+MISMANAGEMENT  M IH0 S - M AE1 - N IH0 JH - M AH0 N T
+MISMANAGING  M IH0 S - M AE1 - N IH0 - JH IH0 NG
+MISMATCH  M IH0 S - M AE1 CH
+MISMATCH(2)  M IH1 S - M AE2 CH
+MISMATCHED  M IH0 S - M AE1 CH T
+MISMATCHES  M IH0 S - M AE1 - CH IH0 Z
+MISNER  M IH1 Z - N ER0
+MISNOMER  M IH0 S - N OW1 - M ER0
+MISOGYNE  M IH1 - Z AH0 - JH IH0 N
+MISOGYNIST  M IH1 - Z AH0 - JH IH0 - N IH0 S T
+MISOGYNY  M IH1 - Z AH0 - JH IH0 - N IY0
+MISPERCEIVE  M IH0 - S P ER0 - S IY1 V
+MISPERCEIVES  M IH0 - S P ER0 - S IY1 V Z
+MISPERCEPTION  M IH2 S - P ER0 - S EH1 P - SH AH0 N
+MISPERCEPTIONS  M IH0 S - P ER0 - S EH1 P - SH AH0 N Z
+MISPLACE  M IH0 S - P L EY1 S
+MISPLACED  M IH0 S - P L EY1 S T
+MISPRICE  M IH0 S - P R AY1 S
+MISPRICED  M IH0 S - P R AY1 S T
+MISPRINT  M IH1 S - P R IH1 N T
+MISPRISION  M IH0 S - P R IH1 - ZH AH0 N
+MISPRONOUNCE  M IH0 S - P R AH0 - N AW1 N S
+MISPRONOUNCED  M IH0 S - P R AH0 - N AW1 N S T
+MISQUOTE  M IH0 S - K W OW1 T
+MISQUOTED  M IH0 S - K W OW1 - T IH0 D
+MISREAD  M IH0 S - R IY1 D
+MISREADING  M IH0 S - R IY1 - D IH0 NG
+MISREMEMBER  M IH0 S - R IY0 - M EH1 M - B ER0
+MISREMEMBERED  M IH0 S - R IY0 - M EH1 M - B ER0 D
+MISREPORT  M IH0 S - R IH0 - P AO1 R T
+MISREPORTED  M IH0 S - R IH0 - P AO1 R - T IH0 D
+MISREPRESENT  M IH0 S - R EH2 - P R AH0 - Z EH1 N T
+MISREPRESENTATION  M IH0 S - R EH2 - P R IH0 - Z EH0 N - T EY1 - SH AH0 N
+MISREPRESENTATIONS  M IH0 S - R EH2 - P R IH0 - Z EH0 N - T EY1 - SH AH0 N Z
+MISREPRESENTED  M IH2 S - R EH0 - P R IH0 - Z EH1 N - T IH0 D
+MISREPRESENTED(2)  M IH2 S - R EH0 - P R IH0 - Z EH1 - N IH0 D
+MISREPRESENTING  M IH0 S - R EH2 - P R AH0 - Z EH1 N - T IH0 NG
+MISREPRESENTING(2)  M IH0 S - R EH2 - P R AH0 - Z EH1 - N IH0 NG
+MISREPRESENTS  M IH0 S - R EH2 - P R AH0 - Z EH1 N T S
+MISREPRESENTS(2)  M IH0 S - R EH2 - P R AH0 - Z EH1 N S
+MISRULE  M IH0 S - R UW1 L
+MISS  M IH1 S
+MISSAL  M IH1 - S AH0 L
+MISSED  M IH1 S T
+MISSEL  M IH1 - S AH0 L
+MISSES  M IH1 - S AH0 Z
+MISSES(2)  M IH1 - S IH0 Z
+MISSETT  M IH1 - S AH0 T
+MISSEY  M IH1 - S IY0
+MISSHAPEN  M IH0 S - SH EY1 - P AH0 N
+MISSHAPEN(2)  M IH0 S - HH AE1 - P AH0 N
+MISSIE  M IH1 - S IY0
+MISSILDINE  M IH0 - S IY0 L - D IY1 - N IY0
+MISSILDINE(2)  M IH0 S - IH0 L - D AY1 N
+MISSILE  M IH1 - S AH0 L
+MISSILE'S  M IH1 - S AH0 L Z
+MISSILES  M IH1 - S AH0 L Z
+MISSILES'  M IH1 - S AH0 L Z
+MISSIMER  M IH1 - S IH0 - M ER0
+MISSING  M IH1 - S IH0 NG
+MISSION  M IH1 - SH AH0 N
+MISSION'S  M IH1 - SH AH0 N Z
+MISSIONARIES  M IH1 - SH AH0 N - EH2 - R IY0 Z
+MISSIONARY  M IH1 - SH AH0 N - EH2 - R IY0
+MISSIONS  M IH1 - SH AH0 N Z
+MISSISSAUGA  M IH2 - S IH0 - S AO1 - G AH0
+MISSISSIPPI  M IH2 - S IH0 - S IH1 - P IY0
+MISSISSIPPI'S  M IH2 - S IH0 - S IH1 - P IY0 Z
+MISSISSIPPIAN  M IH2 - S IH0 - S IH1 - P IY0 - AH0 N
+MISSISSIPPIANS  M IH2 - S IH0 - S IH1 - P IY0 - AH0 N Z
+MISSISSIPPIS  M IH2 - S IH0 - S IH1 - P IY0 Z
+MISSIVE  M IH1 - S IH0 V
+MISSLER  M IH1 S - L ER0
+MISSOULA  M IH0 - Z UW1 - L AH0
+MISSOURI  M AH0 - Z UH1 - R IY0
+MISSOURI'S  M AH0 - Z UH1 - R IY0 Z
+MISSOURI'S(2)  M AH0 - Z ER1 - AH0 Z
+MISSOURI(2)  M AH0 - Z ER1 - AH0
+MISSPEAK  M IH0 S - S P IY1 K
+MISSPEAK(2)  M IH0 - S P IY1 K
+MISSPELL  M IH0 S - S P EH1 L
+MISSPELL(2)  M IH0 - S P EH1 L
+MISSPELLED  M IH0 S - S P EH1 L D
+MISSPELLED(2)  M IH0 - S P EH1 L D
+MISSPELLING  M IH0 S - S P EH1 - L IH0 NG
+MISSPELLING(2)  M IH0 - S P EH1 - L IH0 NG
+MISSPEND  M IH0 S - S P EH1 N D
+MISSPEND(2)  M IH0 - S P EH1 N D
+MISSPENDING  M IH0 S - S P EH1 N - D IH0 NG
+MISSPENDING(2)  M IH0 - S P EH1 N - D IH0 NG
+MISSPENT  M IH0 S - S P EH1 N T
+MISSPENT(2)  M IH0 - S P EH1 N T
+MISSPOKE  M IH0 S - S P OW1 K
+MISSPOKE(2)  M IH0 - S P OW1 K
+MISSPOKEN  M IH0 S - S P OW1 - K AH0 N
+MISSPOKEN(2)  M IH0 - S P OW1 - K AH0 N
+MISSTATE  M IH0 S - S T EY1 T
+MISSTATE(2)  M IH0 - S T EY1 T
+MISSTATED  M IH0 S - S T EY1 - T IH0 D
+MISSTATED(2)  M IH0 - S T EY1 - T IH0 D
+MISSTATEMENT  M IH0 S - T EY1 T - M AH0 N T
+MISSTATEMENTS  M IH0 S - T EY1 T - M AH0 N T S
+MISSTATEMENTS(2)  M IH0 S - T EY1 T - M AH0 N S
+MISSTATES  M IH0 S - S T EY1 T S
+MISSTATES(2)  M IH0 - S T EY1 T S
+MISSTATING  M IH0 S - S T EY1 - T IH0 NG
+MISSTATING(2)  M IH0 - S T EY1 - T IH0 NG
+MISSTEP  M IH0 S - S T EH1 P
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+NATIONSBANC'S(2)  N EY1 - SH AH0 N Z - B AA2 NG K
+NATIONSBANC(2)  N EY1 - SH AH0 N Z - B AA2 NG K
+NATIONSBANK  N EY1 - SH AH0 N Z - B AE2 NG K
+NATIONSBANK'S  N EY1 - SH AH0 N Z - B AE2 NG K S
+NATIONWIDE  N EY1 - SH AH0 N - W AY1 D
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+NATIVE  N EY1 - T IH0 V
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+NATIVIDAD  N AH0 - T IH0 - V IH0 - D AA1 D
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+NATURAL(2)  N AE1 - CH R AH0 L
+NATURALISM  N AE1 - CH ER0 - AH0 - L IH2 - Z AH0 M
+NATURALISM(2)  N AE1 - CH R AH0 - L IH2 - Z AH0 M
+NATURALIST  N AE1 - CH ER0 - AH0 - L AH0 S T
+NATURALIST(2)  N AE1 - CH R AH0 - L AH0 S T
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+NATURALISTIC(2)  N AE2 - CH R AH0 - L IH1 - S T IH0 K
+NATURALISTS  N AE1 - CH ER0 - AH0 - L IH0 S T S
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+NATURALIZE  N AE1 - CH ER0 - AH0 - L AY2 Z
+NATURALIZE(2)  N AE1 - CH R AH0 - L AY2 Z
+NATURALIZED  N AE1 - CH ER0 - AH0 - L AY2 Z D
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+NATWEST  N AE2 T - W EH1 S T
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+NAUGATUCK  N AO1 - G AH0 - T AH2 K
+NAUGHT  N AO1 T
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+NAUSEATE  N AO1 - Z IY0 - EY2 T
+NAUSEATED  N AO1 - Z IY0 - EY2 - T AH0 D
+NAUSEATING  N AO1 - ZH IY0 - EY2 - T IH0 NG
+NAUSEOUS  N AO1 - SH AH0 S
+NAUSS  N AO1 S
+NAUTA  N AA0 - UW1 - T AH0
+NAUTICAL  N AO1 - T AH0 - K AH0 L
+NAUTILUS  N AO1 - T AH0 - L AH0 S
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+NAVA  N AA1 - V AH0
+NAVAJO  N AA1 - V AH0 - HH OW2
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+NAVAJOS  N AA1 - V AH0 - HH OW2 Z
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+NAVIN-CHANDRA  N AA1 - V IH2 N - CH AA1 N - D R AH0
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+NAZI  N AA1 T - S IY0
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+NECESSITATE  N AH0 - S EH1 - S AH0 - T EY2 T
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+PREDETERMINE  P R IY2 - D IH0 - T ER1 - M AH0 N
+PREDETERMINE(2)  P R IY2 - D IY0 - T ER1 - M AH0 N
+PREDETERMINED  P R IY2 - D IY0 - T ER1 - M IH0 N D
+PREDICAMENT  P R IH0 - D IH1 - K AH0 - M AH0 N T
+PREDICAMENT(2)  P R IY0 - D IH1 - K AH0 - M AH0 N T
+PREDICAMENTS  P R IH0 - D IH1 - K AH0 - M AH0 N T S
+PREDICATE  P R EH1 - D AH0 - K EY2 T
+PREDICATE(2)  P R EH1 - D IH0 - K AH0 T
+PREDICATED  P R EH1 - D AH0 - K EY2 - T IH0 D
+PREDICATES  P R EH1 - D AH0 - K EY2 T S
+PREDICATES(2)  P R EH1 - D IH0 - K AH0 T S
+PREDICT  P R IH0 - D IH1 K T
+PREDICT(2)  P R IY0 - D IH1 K T
+PREDICTABILITY  P R IH0 - D IH2 K - T AH0 - B IH1 - L IH0 - T IY0
+PREDICTABLE  P R IH0 - D IH1 K - T AH0 - B AH0 L
+PREDICTABLE(2)  P R IY0 - D IH1 K - T AH0 - B AH0 L
+PREDICTABLY  P R IH0 - D IH1 K - T AH0 - B L IY0
+PREDICTED  P R IH0 - D IH1 K - T IH0 D
+PREDICTED(2)  P R IY0 - D IH1 K - T AH0 D
+PREDICTED(3)  P R IY0 - D IH1 K - T IH0 D
+PREDICTING  P R IH0 - D IH1 K - T IH0 NG
+PREDICTING(2)  P R IY0 - D IH1 K - T IH0 NG
+PREDICTION  P R IY0 - D IH1 K - SH AH0 N
+PREDICTIONS  P R IY0 - D IH1 K - SH AH0 N Z
+PREDICTIVE  P R IH0 - D IH1 K - T IH0 V
+PREDICTIVE(2)  P R IY0 - D IH1 K - T IH0 V
+PREDICTOR  P R IH0 - D IH1 K - T ER0
+PREDICTORS  P R IH0 - D IH1 K - T ER0 Z
+PREDICTORS(2)  P R IY0 - D IH1 K - T ER0 Z
+PREDICTS  P R IH0 - D IH1 K T S
+PREDICTS(2)  P R IY0 - D IH1 K T S
+PREDICTS(3)  P R IH0 - D IH1 K S
+PREDICTS(4)  P R IY0 - D IH1 K S
+PREDILECTION  P R EH2 - D AH0 - L EH1 K - SH AH0 N
+PREDILECTIONS  P R EH2 - D AH0 - L EH1 K - SH AH0 N Z
+PREDISPOSE  P R IY2 - D IH0 - S P OW1 Z
+PREDISPOSED  P R IY2 - D IH0 - S P OW1 Z D
+PREDISPOSING  P R IY2 - D IH0 - S P OW1 - Z IH0 NG
+PREDISPOSITION  P R IY2 - D IH0 S - P AH0 - Z IH1 - SH AH0 N
+PREDISPOSITIONS  P R IY2 - D IH0 S - P AH0 - Z IH1 - SH AH0 N Z
+PREDMORE  P R EH1 D - M AO0 R
+PREDOMINANCE  P R IH0 - D AA1 - M AH0 - N AH0 N S
+PREDOMINANT  P R IH0 - D AA1 - M AH0 - N AH0 N T
+PREDOMINANTLY  P R IH0 - D AA1 - M AH0 - N AH0 N T - L IY0
+PREDOMINATE  P R IH0 - D AA1 - M AH0 - N EY2 T
+PREDOMINATE(2)  P R IH0 - D AA1 - M AH0 - N AH0 T
+PREDOMINATED  P R IH0 - D AA1 - M AH0 - N EY2 - T IH0 D
+PREDOMINATES  P R IH0 - D AA1 - M AH0 - N EY2 T S
+PREDOMINATING  P R IH0 - D AA1 - M AH0 - N EY2 - T IH0 NG
+PREE  P R IY1
+PREECE  P R IY1 S
+PREELECTION  P R IY0 - IH0 - L EH1 K - SH AH0 N
+PREEMINENCE  P R IY0 - EH1 - M AH0 - N AH0 N S
+PREEMINENT  P R IY0 - EH1 - M AH0 - N AH0 N T
+PREEMPT  P R IY1 - EH2 M P T
+PREEMPTED  P R IY0 - EH1 M P - T IH0 D
+PREEMPTING  P R IY0 - EH1 M P - T IH0 NG
+PREEMPTION  P R IY2 - EH1 M P - SH AH0 N
+PREEMPTIVE  P R IY0 - EH1 M P - T IH0 V
+PREEMPTIVELY  P R IY0 - EH1 M P - T IH0 V - L IY0
+PREEN  P R IY1 N
+PREENED  P R IY1 N D
+PREENING  P R IY1 - N IH0 NG
+PREEXIST  P R IY1 - IH0 G - Z IH1 S T
+PREEXISTED  P R IY1 - IH0 G - Z IH1 - S T IH0 D
+PREEXISTING  P R IY1 - IH0 G - Z IH1 - S T IH0 NG
+PREEXISTS  P R IY1 - IH0 G - Z IH1 S T S
+PREEXISTS(2)  P R IY1 - IH0 G - Z IH1 S S
+PREEXISTS(3)  P R IY1 - IH0 G - Z IH1 S
+PREFAB  P R IY1 - F AE1 B
+PREFABRICATE  P R IY0 - F AE1 - B R IH0 - K EY2 T
+PREFABRICATED  P R IY0 - F AE1 - B R IH0 - K EY2 - T IH0 D
+PREFABRICATION  P R IY2 - F AE2 - B R AH0 - K EY1 - SH AH0 N
+PREFABS  P R IY1 - F AE1 B Z
+PREFACE  P R EH1 - F AH0 S
+PREFACED  P R EH1 - F AH0 S T
+PREFECT  P R IY1 - F EH2 K T
+PREFECTURAL  P R IY0 - F EH1 K - CH ER0 - AH0 L
+PREFECTURE  P R IY1 - F EH2 K - CH ER0
+PREFER  P R AH0 - F ER1
+PREFER(2)  P R IH0 - F ER1
+PREFER(3)  P R IY0 - F ER1
+PREFERABLE  P R EH1 - F ER0 - AH0 - B AH0 L
+PREFERABLE(2)  P R EH1 - F R AH0 - B AH0 L
+PREFERABLY  P R EH1 - F ER0 - AH0 - B L IY0
+PREFERABLY(2)  P R EH1 - F R AH0 - B L IY0
+PREFERED  P R IH0 - F ER1 D
+PREFERENCE  P R EH1 - F ER0 - AH0 N S
+PREFERENCE(2)  P R EH1 - F R AH0 N S
+PREFERENCED  P R EH1 - F ER0 - AH0 N S T
+PREFERENCED(2)  P R EH1 - F R AH0 N S T
+PREFERENCES  P R EH1 - F ER0 - AH0 N - S IH0 Z
+PREFERENTIAL  P R EH2 - F ER0 - EH1 N - CH AH0 L
+PREFERENTIAL(2)  P R EH2 - F ER0 - EH1 N - SH AH0 L
+PREFERENTIALLY  P R EH2 - F ER0 - EH1 N - CH AH0 - L IY0
+PREFERENTIALLY(2)  P R EH2 - F ER0 - EH1 N - SH AH0 - L IY0
+PREFERRED  P R AH0 - F ER1 D
+PREFERRED(2)  P R IH0 - F ER1 D
+PREFERRED(3)  P R IY0 - F ER1 D
+PREFERREDS  P R IY0 - F ER1 - AH0 D Z
+PREFERRING  P R IH0 - F ER1 - IH0 NG
+PREFERS  P R AH0 - F ER1 Z
+PREFERS(2)  P R IH0 - F ER1 Z
+PREFERS(3)  P R IY0 - F ER1 Z
+PREFIX  P R IY1 - F IH0 K S
+PREFRONTAL  P R IY0 - F R AH1 N - T AH0 L
+PREGLER  P R EH1 G - L ER0
+PREGNANCIES  P R EH1 G - N AH0 N - S IY0 Z
+PREGNANCY  P R EH1 G - N AH0 N - S IY0
+PREGNANT  P R EH1 G - N AH0 N T
+PREGO  P R EY1 - G OW0
+PREHEIM  P R EH1 - HH AY0 M
+PREHISTORIC  P R IY2 - HH IH0 - S T AO1 - R IH0 K
+PREHN  P R EH1 N
+PREHOLIDAY  P R IY2 - HH AO1 - L IH0 - D EY0
+PREIGNITION  P R IY2 - AH0 G - N IH1 - SH AH0 N
+PREIS  P R IY1 Z
+PREISER  P R AY1 - S ER0
+PREISIG  P R AY1 - Z IH0 G
+PREISLER  P R AY1 - S AH0 - L ER0
+PREISLER(2)  P R AY1 S - L ER0
+PREISS  P R AY1 S
+PREJEAN  P R IY2 - JH IY1 N
+PREJUDGE  P R IY0 - JH AH1 JH
+PREJUDGED  P R IY0 - JH AH1 JH D
+PREJUDGMENT  P R IY0 - JH AH1 JH - M AH0 N T
+PREJUDICE  P R EH1 - JH AH0 - D IH0 S
+PREJUDICED  P R EH1 - JH AH0 - D AH0 S T
+PREJUDICES  P R EH1 - JH AH0 - D IH0 - S IH0 Z
+PREJUDICIAL  P R EH2 - JH AH0 - D IH1 - SH AH0 L
+PREJUDICING  P R EH1 - JH AH0 - D IH0 - S IH0 NG
+PREKINDERGARTEN  P R IY0 - K IH1 N - D ER0 - G AA2 - D AH0 N
+PRELATE  P R EH1 - L IH0 T
+PRELATE(2)  P R IY1 - L EY2 T
+PRELATES  P R EH1 - L IH0 T S
+PRELIM  P R IH0 - L IH1 M
+PRELIM(2)  P R IY0 - L IH1 M
+PRELIMINARIES  P R IH0 - L IH1 - M AH0 - N EH2 - R IY0 Z
+PRELIMINARIES(2)  P R IY0 - L IH1 - M AH0 - N EH2 - R IY0 Z
+PRELIMINARILY  P R IH0 - L IH2 - M AH0 - N EH1 - R IH0 - L IY0
+PRELIMINARY  P R IH0 - L IH1 - M AH0 - N EH2 - R IY0
+PRELIMINARY(2)  P R IY0 - L IH1 - M AH0 - N EH2 - R IY0
+PRELIMS  P R IY1 - L IH2 M Z
+PRELL  P R EH1 L
+PRELLWITZ  P R EH1 L - W IH0 T S
+PRELUDE  P R EY1 - L UW2 D
+PRELUDES  P R EY1 - L UW2 D Z
+PREM  P R EH1 M
+PREMADASA  P R IY2 - M AH0 - D AA1 - S AH0
+PREMARIN  P R EH1 - M ER0 - IH0 N
+PREMARITAL  P R IY0 - M EH1 - R AH0 - T AH0 L
+PREMARK  P R IY0 - M AA1 R K
+PREMARKET  P R IY1 - M AA1 R - K AH0 T
+PREMATURE  P R IY2 - M AH0 - CH UH1 R
+PREMATURELY  P R IY2 - M AH0 - CH UH1 R - L IY0
+PREMEDITATE  P R IY0 - M EH1 - D AH0 - T EY2 T
+PREMEDITATED  P R IY0 - M EH1 - D AH0 - T EY2 - T IH0 D
+PREMEDITATION  P R IY0 - M EH2 - D AH0 - T EY1 - SH AH0 N
+PREMIER  P R EH0 - M IH1 R
+PREMIER'S  P R EH0 - M IH1 R Z
+PREMIER'S(2)  P R IY0 - M IH1 R Z
+PREMIER(2)  P R IY0 - M IH1 R
+PREMIERE  P R EH0 - M IH1 R
+PREMIERED  P R EH0 - M IH1 R D
+PREMIERES  P R EH0 - M IH1 R Z
+PREMIERING  P R EH0 - M IH1 - R IH0 NG
+PREMIERS  P R EH0 - M IH1 R Z
+PREMIERSHIP  P R EH0 - M IH1 R - SH IH2 P
+PREMISE  P R EH1 - M IH0 S
+PREMISED  P R EH1 - M AH0 S T
+PREMISES  P R EH1 - M AH0 - S AH0 Z
+PREMIUM  P R IY1 - M IY0 - AH0 M
+PREMIUMS  P R IY1 - M IY0 - AH0 M Z
+PREMO  P R EH1 - M OW0
+PREMODERN  P R IY0 - M AO1 - D ER0 N
+PREMONITION  P R EH0 - M AH0 - N IH1 - SH AH0 N
+PREMONITORY  P R AH0 - M AH1 - N AH0 - T ER0 - IY0
+PRENATAL  P R IY0 - N EY1 - T AH0 L
+PRENDERGAST  P R EH1 N - D ER0 - G AE2 S T
+PRENGER  P R EH1 N - JH ER0
+PRENN  P R EH1 N
+PRENSA  P R EH1 N - S AH0
+PRENTICE  P R EH1 N - T IH0 S
+PRENTISS  P R EH1 N - T IH0 S
+PRENTNIEKS  P R EH1 N T - N IY0 - EH2 K S
+PRENUPTIAL  P R IY0 - N AH1 P - SH AH0 L
+PREOCCUPATION  P R IY0 - AA2 - K Y AH0 - P EY1 - SH AH0 N
+PREOCCUPATIONS  P R IY0 - AA2 - K Y AH0 - P EY1 - SH AH0 N Z
+PREOCCUPIED  P R IY0 - AA1 - K Y AH0 - P AY2 D
+PREOCCUPIES  P R IY0 - AA1 - K Y AH0 - P AY2 Z
+PREOCCUPY  P R IY0 - AA1 - K Y AH0 - P AY2
+PREORDAIN  P R IY2 - AO0 R - D EY1 N
+PREORDAINED  P R IY2 - AO0 R - D EY1 N D
+PREP  P R EH1 P
+PREPACKAGE  P R IY0 - P AE1 - K AH0 JH
+PREPACKAGED  P R IY0 - P AE1 - K AH0 JH D
+PREPAID  P R IY0 - P EY1 D
+PREPARATION  P R EH2 - P ER0 - EY1 - SH AH0 N
+PREPARATIONS  P R EH2 - P ER0 - EY1 - SH AH0 N Z
+PREPARATORY  P R IH0 - P EH1 - R AH0 - T AO2 - R IY0
+PREPARATORY(2)  P R EH1 - P R AH0 - T AO2 - R IY0
+PREPARE  P R IY0 - P EH1 R
+PREPARED  P R IY0 - P EH1 R D
+PREPAREDNESS  P R IY0 - P EH1 - R AH0 D - N AH0 S
+PREPARER  P R IY0 - P EH1 - R ER0
+PREPARERS  P R IY0 - P EH1 - R ER0 Z
+PREPARES  P R IY0 - P EH1 R Z
+PREPARES(2)  P ER0 - P EH1 R Z
+PREPARING  P R IY0 - P EH1 - R IH0 NG
+PREPARING(2)  P ER0 - P EH1 - R IH0 NG
+PREPAY  P R IY0 - P EY1
+PREPAYING  P R IY0 - P EY1 - IH0 NG
+PREPAYMENT  P R IY0 - P EY1 - M AH0 N T
+PREPAYMENTS  P R IY0 - P EY1 - M AH0 N T S
+PREPLANNING  P R IY0 - P L AE1 - N IH0 NG
+PREPONDERANCE  P R IY0 - P AA1 N - D R AH0 N S
+PREPOSTEROUS  P R IH0 - P AA1 - S T ER0 - AH0 S
+PREPOSTEROUS(2)  P R IH0 - P AA1 S - T R AH0 S
+PREPPED  P R EH1 P T
+PREPPIE  P R EH1 - P IY0
+PREPPING  P R EH1 - P IH0 NG
+PREPPY  P R EH1 - P IY0
+PRERECORD  P R IY2 - R IY0 - K AO1 R D
+PRERECORD(2)  P R IY2 - R IH0 - K AO1 R D
+PRERECORDED  P R IY2 - R IY0 - K AO1 R - D IH0 D
+PREREQUISITE  P R IY0 - R EH1 - K W AH0 - Z AH0 T
+PREREQUISITES  P R IY0 - R EH1 - K W AH0 - Z AH0 T S
+PREROGATIVE  P R IH0 - R AA1 - G AH0 - T IH0 V
+PREROGATIVE(2)  P ER1 - AA1 - G AH0 - T IH0 V
+PREROGATIVES  P R IH0 - R AA1 - G AH0 - T IH0 V Z
+PREROGATIVES(2)  P ER1 - AA1 - G AH0 - T IH0 V Z
+PRES  P R EH1 Z
+PRESAGE  P R EH1 - S IH0 JH
+PRESAGED  P R EH1 - S IH0 JH D
+PRESAGES  P R EH1 - S IH0 - JH IH0 Z
+PRESAGING  P R EH1 - S IH0 - JH IH0 NG
+PRESALE  P R IY1 - S EY2 L
+PRESARIO  P R IH0 - S AA1 - R IY0 - OW2
+PRESBY  P R EH1 S - B IY0
+PRESBY(2)  P R EH1 Z - B IY0
+PRESBYTERIAN  P R EH2 S - B IH0 - T IH1 - R IY0 - AH0 N
+PRESBYTERIAN(2)  P R EH2 Z - B IH0 - T IH1 - R IY0 - AH0 N
+PRESBYTERIANS  P R EH2 S - B IH0 - T IH1 - R IY0 - AH0 N Z
+PRESBYTERIANS(2)  P R EH2 Z - B IH0 - T IH1 - R IY0 - AH0 N Z
+PRESCHEL  P R EH1 - SH AH0 L
+PRESCHER  P R EH1 - SH ER0
+PRESCHOOL  P R IY0 - S K UW1 L
+PRESCHOOL(2)  P R IY1 - S K UW2 L
+PRESCHOOLER  P R IY1 - S K UW2 - L ER0
+PRESCHOOLERS  P R IY1 - S K UW2 - L ER0 Z
+PRESCHOOLS  P R IY0 - S K UW1 L Z
+PRESCHOOLS(2)  P R IY1 - S K UW2 L Z
+PRESCIENCE  P R IY1 - SH IY0 - AH0 N S
+PRESCIENT  P R EH1 - S IY0 - AH0 N T
+PRESCOT  P R EH1 - S K AH0 T
+PRESCOTT  P R EH1 - S K AA0 T
+PRESCRIBE  P R AH0 - S K R AY1 B
+PRESCRIBE(2)  P R IY0 - S K R AY1 B
+PRESCRIBED  P R IY0 - S K R AY1 B D
+PRESCRIBER  P R IY0 - S K R AY1 - B ER0
+PRESCRIBERS  P R IY0 - S K R AY1 - B ER0 Z
+PRESCRIBES  P R IY0 - S K R AY1 B Z
+PRESCRIBING  P R IY0 - S K R AY1 - B IH0 NG
+PRESCRIPTION  P R AH0 - S K R IH1 P - SH AH0 N
+PRESCRIPTIONS  P R AH0 - S K R IH1 P - SH AH0 N Z
+PRESENCE  P R EH1 - Z AH0 N S
+PRESENCES  P R EH1 - Z AH0 N - S IH0 Z
+PRESENT  P R EH1 - Z AH0 N T
+PRESENT(2)  P R IY0 - Z EH1 N T
+PRESENT(3)  P ER0 - Z EH1 N T
+PRESENTABLE  P R AH0 - Z EH1 N - T AH0 - B AH0 L
+PRESENTATION  P R EH2 - Z AH0 N - T EY1 - SH AH0 N
+PRESENTATIONS  P R EH2 - Z AH0 N - T EY1 - SH AH0 N Z
+PRESENTED  P R IY0 - Z EH1 N - T AH0 D
+PRESENTED(2)  P ER0 - Z EH1 N - T AH0 D
+PRESENTED(3)  P R IY0 - Z EH1 - N AH0 D
+PRESENTED(4)  P ER0 - Z EH1 - N AH0 D
+PRESENTER  P R EH1 - Z AH0 N - T ER0
+PRESENTER(2)  P R IY0 - Z EH1 N - T ER0
+PRESENTERS  P R EH1 - Z AH0 N - T ER0 Z
+PRESENTERS(2)  P R IY0 - Z EH1 N - T ER0 Z
+PRESENTING  P R IH0 - Z EH1 N - T IH0 NG
+PRESENTING(2)  P R IY0 - Z EH1 N - T IH0 NG
+PRESENTLY  P R EH1 - Z AH0 N T - L IY0
+PRESENTMENT  P R IY0 - Z EH1 N T - M AH0 N T
+PRESENTS  P R EH1 - Z AH0 N T S
+PRESENTS(2)  P R IY0 - Z EH1 N T S
+PRESERVATION  P R EH2 - Z ER0 - V EY1 - SH AH0 N
+PRESERVATIONIST  P R EH2 - Z ER0 - V EY1 - SH AH0 N - IH0 S T
+PRESERVATIONISTS  P R EH2 - Z ER0 - V EY1 - SH AH0 N - IH0 S T S
+PRESERVATIONISTS(2)  P R EH2 - Z ER0 - V EY1 - SH AH0 N - IH0 S S
+PRESERVATIONISTS(3)  P R EH2 - Z ER0 - V EY1 - SH AH0 N - IH0 S
+PRESERVATIVE  P R IY0 - Z ER1 - V AH0 - T IH0 V
+PRESERVATIVES  P R AH0 - Z ER1 - V AH0 - T IH0 V Z
+PRESERVE  P R AH0 - Z ER1 V
+PRESERVE(2)  P R IH0 - Z ER1 V
+PRESERVE(3)  P R IY0 - Z ER1 V
+PRESERVED  P R AH0 - Z ER1 V D
+PRESERVED(2)  P R IH0 - Z ER1 V D
+PRESERVED(3)  P R IY0 - Z ER1 V D
+PRESERVER  P R IY0 - Z ER1 - V ER0
+PRESERVER(2)  P R IH0 - Z ER1 - V ER0
+PRESERVER(3)  P R AH0 - Z ER1 - V ER0
+PRESERVERS  P R IY0 - Z ER1 - V ER0 Z
+PRESERVERS(2)  P R AH0 - Z ER1 - V ER0 Z
+PRESERVES  P R AH0 - Z ER1 V Z
+PRESERVES(2)  P R IH0 - Z ER1 V Z
+PRESERVES(3)  P R IY0 - Z ER1 V Z
+PRESERVING  P R AH0 - Z ER1 - V IH0 NG
+PRESERVING(2)  P R IH0 - Z ER1 - V IH0 NG
+PRESERVING(3)  P R IY0 - Z ER1 - V IH0 NG
+PRESET  P R IY0 - S EH1 T
+PRESIDE  P R IH0 - Z AY1 D
+PRESIDE(2)  P R IY0 - Z AY1 D
+PRESIDED  P R IH0 - Z AY1 - D IH0 D
+PRESIDED(2)  P R IY0 - Z AY1 - D AH0 D
+PRESIDED(3)  P R IY0 - Z AY1 - D IH0 D
+PRESIDENCIES  P R EH1 - Z AH0 - D AH0 N - S IY0 Z
+PRESIDENCY  P R EH1 - Z AH0 - D AH0 N - S IY0
+PRESIDENCY'S  P R EH1 - Z AH0 - D AH0 N - S IY0 Z
+PRESIDENT  P R EH1 - Z AH0 - D EH2 N T
+PRESIDENT'S  P R EH1 - Z IH0 - D AH0 N T S
+PRESIDENT(2)  P R EH1 - Z IH0 - D AH0 N T
+PRESIDENTIAL  P R EH2 - Z AH0 - D EH1 N - CH AH0 L
+PRESIDENTIAL'S  P R EH2 - Z AH0 - D EH1 N - CH AH0 L Z
+PRESIDENTIAL'S(2)  P R EH2 - Z AH0 - D EH1 N - SH AH0 L Z
+PRESIDENTIAL(2)  P R EH2 - Z AH0 - D EH1 N - SH AH0 L
+PRESIDENTIALIST  P R EH2 - Z AH0 - D EH1 N - CH AH0 - L IH0 S T
+PRESIDENTIALIST(2)  P R EH2 - Z AH0 - D EH1 N - SH AH0 - L IH0 S T
+PRESIDENTIALLY  P R EH2 - S IH0 - D EH1 N - CH AH0 - L IY0
+PRESIDENTIALLY(2)  P R EH2 - S IH0 - D EH1 N - SH AH0 - L IY0
+PRESIDENTS  P R EH1 - Z AH0 - D EH2 N T S
+PRESIDENTS'  P R EH1 - Z IH0 - D AH0 N T S
+PRESIDENTS(2)  P R EH1 - Z IH0 - D AH0 N T S
+PRESIDENTS(3)  P R EH1 - Z IH0 - D AH0 N S
+PRESIDES  P R IH0 - Z AY1 D Z
+PRESIDES(2)  P R IY0 - Z AY1 D Z
+PRESIDING  P R IH0 - Z AY1 - D IH0 NG
+PRESIDING(2)  P R IY0 - Z AY1 - D IH0 NG
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+PROPAGATED  P R AA1 - P AH0 - G EY2 - T IH0 D
+PROPAGATING  P R AA1 - P AH0 - G EY2 - T IH0 NG
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+REBUTTAL  R IH0 - B AH1 - T AH0 L
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+REC  R EH1 K
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+RECALCITRANCE  R IH0 - K AE1 L - S AH0 - T R AH0 N S
+RECALCITRANT  R IH0 - K AE1 L - S IH0 - T R AH0 N T
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+RECANTED  R IY0 - K AE1 N - T IH0 D
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+RECAPPED  R IY0 - K AE1 P T
+RECAPPING  R IY0 - K AE1 - P IH0 NG
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+RECAPTURED  R IY0 - K AE1 P - CH ER0 D
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+RECAREY  R IY0 - K EH1 - R IY0
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+RECEDED(3)  R IY0 - S IY1 - D IH0 D
+RECEDES  R IY0 - S IY1 D Z
+RECEDING  R IH0 - S IY1 - D IH0 NG
+RECEDING(2)  R IY0 - S IY1 - D IH0 NG
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+RECEIPT(2)  R IY0 - S IY1 T
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+RECEIPTS(2)  R IY0 - S IY1 T S
+RECEIVABLE  R IH0 - S IY1 - V AH0 - B AH0 L
+RECEIVABLES  R IH0 - S IY1 - V AH0 - B AH0 L Z
+RECEIVE  R AH0 - S IY1 V
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+RECEIVE(3)  R IY0 - S IY1 V
+RECEIVED  R AH0 - S IY1 V D
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+RECEIVERS(3)  R IY0 - S IY1 - V ER0 Z
+RECEIVERSHIP  R IH0 - S IY1 - V ER0 - SH IH2 P
+RECEIVERSHIP(2)  R IY0 - S IY1 - V ER0 - SH IH2 P
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+RECEIVES  R AH0 - S IY1 V Z
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+RECEIVES(3)  R IY0 - S IY1 V Z
+RECEIVING  R AH0 - S IY1 - V IH0 NG
+RECEIVING(2)  R IH0 - S IY1 - V IH0 NG
+RECEIVING(3)  R IY0 - S IY1 - V IH0 NG
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+RECEPTACLE  R AH0 - S EH1 P - T AH0 - K AH0 L
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+RECEPTION  R IH0 - S EH1 P - SH AH0 N
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+RECEPTIONIST  R IH0 - S EH1 P - SH AH0 - N IH0 S T
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+RECEPTIVITY  R IY1 - S EH2 P - T IH1 - V IH0 - T IY0
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+RECERTIFIED  R IY0 - S ER1 - T IH0 - F AY0 D
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+RECERTIFYING  R IY0 - S ER1 - T AH0 - F AY0 - IH0 NG
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+RECHARGEABLE  R IY0 - CH AA1 R - JH AH0 - B AH0 L
+RECHARGED  R IY0 - CH AA1 R JH D
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+RECHECKED  R IY0 - CH EH1 K T
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+RECIPROCAL  R IH0 - S IH1 - P R AH0 - K AH0 L
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+RECLASSIFIED  R IY0 - K L AE1 - S AH0 - F AY2 D
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+RECLASSIFYING  R IY0 - K L AE1 - S IH0 - F AY2 - IH0 NG
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+RECLINING  R IH0 - K L AY1 - N IH0 NG
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+RECOUNT  R IH0 - K AW1 N T
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+RECOUNTED  R IH0 - K AW1 N - T IH0 D
+RECOUNTED(2)  R IY2 - K AW1 N - T IH0 D
+RECOUNTING  R IH0 - K AW1 N - T IH0 NG
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+REPATRIATE  R IY0 - P EY1 - T R IY0 - EY2 T
+REPATRIATED  R IY0 - P EY1 - T R IY0 - EY2 - T IH0 D
+REPATRIATING  R IY0 - P EY1 - T R IY0 - EY2 - T IH0 NG
+REPATRIATION  R IY0 - P EY2 - T R IY0 - EY1 - SH AH0 N
+REPAY  R IY0 - P EY1
+REPAYABLE  R IY0 - P EY1 - AH0 - B AH0 L
+REPAYING  R IY0 - P EY1 - IH0 NG
+REPAYMENT  R IY0 - P EY1 - M AH0 N T
+REPAYMENTS  R IY0 - P EY1 - M AH0 N T S
+REPAYS  R IY2 - P EY1 Z
+REPEAL  R IH0 - P IY1 L
+REPEAL(2)  R IY0 - P IY1 L
+REPEALED  R IH0 - P IY1 L D
+REPEALED(2)  R IY0 - P IY1 L D
+REPEALING  R IY0 - P IY1 - L IH0 NG
+REPEALS  R IY0 - P IY1 L Z
+REPEAT  R IH0 - P IY1 T
+REPEAT(2)  R IY0 - P IY1 T
+REPEATABLE  R IH0 - P IY1 - T AH0 - B AH0 L
+REPEATED  R IH0 - P IY1 - T IH0 D
+REPEATED(2)  R IY0 - P IY1 - T AH0 D
+REPEATED(3)  R IY0 - P IY1 - T IH0 D
+REPEATEDLY  R IH0 - P IY1 - T IH0 D - L IY0
+REPEATER  R IH0 - P IY1 - T ER0
+REPEATERS  R IH0 - P IY1 - T ER0 Z
+REPEATING  R IH0 - P IY1 - T IH0 NG
+REPEATING(2)  R IY0 - P IY1 - T IH0 NG
+REPEATS  R IH0 - P IY1 T S
+REPEATS(2)  R IY0 - P IY1 T S
+REPEL  R IH0 - P EH1 L
+REPELLED  R AH0 - P EH1 L D
+REPELLED(2)  R IH0 - P EH1 L D
+REPELLENT  R IH0 - P EH1 - L AH0 N T
+REPELLING  R AH0 - P EH1 - L IH0 NG
+REPELS  R IH0 - P EH1 L Z
+REPENT  R IH0 - P EH1 N T
+REPENTANCE  R IH0 - P EH1 N - T AH0 N S
+REPENTANT  R IH0 - P EH1 N - T AH0 N T
+REPENTED  R IH0 - P EH1 N - T IH0 D
+REPERCUSSION  R IY2 - P ER0 - K AH1 - SH AH0 N
+REPERCUSSION(2)  R IY2 - P R AH0 - K AH1 - SH AH0 N
+REPERCUSSIONS  R IY2 - P ER0 - K AH1 - SH AH0 N Z
+REPERCUSSIONS(2)  R IY2 - P R AH0 - K AH1 - SH AH0 N Z
+REPERFUSION  R EH2 - P ER0 - F Y UW1 - ZH AH0 N
+REPERTOIRE  R EH1 - P ER0 - T W AA2 R
+REPERTORY  R EH1 - P ER0 - T AO2 - R IY0
+REPETITION  R EH2 - P AH0 - T IH1 - SH AH0 N
+REPETITIONS  R EH2 - P AH0 - T IH1 - SH AH0 N Z
+REPETITIOUS  R EH2 - P AH0 - T IH1 - SH AH0 S
+REPETITIVE  R IH0 - P EH1 - T IH0 - T IH0 V
+REPETTI  R EH0 - P EH1 - T IY0
+REPETTO  R EH0 - P EH1 - T OW0
+REPH  R EH1 F
+REPHRASE  R IY0 - F R EY1 Z
+REPINSKI  R IH0 - P IH1 N - S K IY0
+REPKA  R EH1 P - K AH0
+REPKO  R EH1 P - K OW0
+REPLACE  R IY2 - P L EY1 S
+REPLACE(2)  ER0 - P L EY1 S
+REPLACEABLE  R IY2 - P L EY1 - S AH0 - B AH0 L
+REPLACED  R IY2 - P L EY1 S T
+REPLACEMENT  R IH0 - P L EY1 S - M AH0 N T
+REPLACEMENTS  R IY0 - P L EY1 S - M AH0 N T S
+REPLACES  R IH0 - P L EY1 - S IH0 Z
+REPLACING  R IH0 - P L EY1 - S IH0 NG
+REPLANT  R IY0 - P L AE1 N T
+REPLANTED  R IY0 - P L AE1 N - T IH0 D
+REPLANTED(2)  R IY0 - P L AE1 - N IH0 D
+REPLANTING  R IY0 - P L AE1 N - T IH0 NG
+REPLAY  R IY0 - P L EY1
+REPLAYED  R IY0 - P L EY1 D
+REPLAYING  R IY0 - P L EY1 - IH0 NG
+REPLAYS  R IY0 - P L EY1 Z
+REPLENISH  R IY0 - P L EH1 - N IH0 SH
+REPLENISHED  R IY0 - P L EH1 - N IH0 SH T
+REPLENISHING  R IY0 - P L EH1 - N IH0 - SH IH0 NG
+REPLENISHMENT  R IH0 - P L EH1 - N IH0 SH - M AH0 N T
+REPLETE  R IY0 - P L IY1 T
+REPLICA  R EH1 - P L IH0 - K AH0
+REPLICAS  R EH1 - P L AH0 - K AH0 Z
+REPLICASE  R EH1 - P L IH0 - K EY2 Z
+REPLICATE  R EH1 - P L AH0 - K EY2 T
+REPLICATED  R EH1 - P L IH0 - K EY2 - T IH0 D
+REPLICATES  R EH1 - P L IH0 - K EY2 T S
+REPLICATING  R EH1 - P L IH0 - K EY2 - T IH0 NG
+REPLICATION  R EH2 - P L AH0 - K EY1 - SH AH0 N
+REPLIED  R IH0 - P L AY1 D
+REPLIED(2)  R IY0 - P L AY1 D
+REPLIES  R IH0 - P L AY1 Z
+REPLIES(2)  R IY0 - P L AY1 Z
+REPLIGEN  R IH2 - P L AY1 - JH IH0 N
+REPLIGEN'S  R IH2 - P L AY1 - JH IH0 N Z
+REPLOGLE  R EH1 - P L OW0 - G AH0 L
+REPLY  R IH0 - P L AY1
+REPLY(2)  R IY0 - P L AY1
+REPLYING  R IH0 - P L AY1 - IH0 NG
+REPLYING(2)  R IY0 - P L AY1 - IH0 NG
+REPO  R IY1 - P OW0
+REPONSE  R IH0 - P AA1 N S
+REPORT  R IY0 - P AO1 R T
+REPORT'S  R IY0 - P AO1 R T S
+REPORT'S(2)  R IH0 - P AO1 R T S
+REPORT(2)  R IH0 - P AO1 R T
+REPORTABLE  R IH0 - P AO1 R - T AH0 - B AH0 L
+REPORTAGE  R IH0 - P AO1 R - T IH0 JH
+REPORTED  R IY2 - P AO1 R - T AH0 D
+REPORTED(2)  R IH0 - P AO1 R - T AH0 D
+REPORTEDLY  R IH0 - P AO1 R - T AH0 D - L IY0
+REPORTEDLY(2)  R IY0 - P AO1 R - T AH0 D - L IY0
+REPORTER  R IH0 - P AO1 R - T ER0
+REPORTER'S  R IH0 - P AO1 R - T ER0 Z
+REPORTERS  R IH0 - P AO1 R - T ER0 Z
+REPORTERS'  R IH0 - P AO1 R - T ER0 Z
+REPORTING  R IY0 - P AO1 R - T IH0 NG
+REPORTING(2)  R IH0 - P AO1 R - T IH0 NG
+REPORTORIAL  R EH2 - P ER0 - T AO1 - R IY0 - AH0 L
+REPORTS  R IH0 - P AO1 R T S
+REPORTS'  R IH0 - P AO1 R T S
+REPORTS'(2)  R IY0 - P AO1 R T S
+REPORTS(2)  R IY0 - P AO1 R T S
+REPOS  R IY1 - P OW2 Z
+REPOSA  R EH0 - P OW1 - S AH0
+REPOSE  R IY0 - P OW1 Z
+REPOSITION  R IY2 - P AH0 - Z IH1 - SH AH0 N
+REPOSITIONED  R IY2 - P AH0 - Z IH1 - SH AH0 N D
+REPOSITIONING  R IY2 - P AH0 - Z IH1 - SH AH0 N - IH0 NG
+REPOSITORIES  R IY0 - P AA1 - Z AH0 - T AO2 - R IY0 Z
+REPOSITORY  R IY0 - P AA1 - Z AH0 - T AO2 - R IY0
+REPOSSESS  R IY2 - P AH0 - Z EH1 S
+REPOSSESSED  R IY2 - P AH0 - Z EH1 S T
+REPOSSESSION  R IY2 - P AH0 - Z EH1 - SH AH0 N
+REPOSSESSIONS  R IY2 - P AH0 - Z EH1 - SH AH0 N Z
+REPP  R EH1 P
+REPPERT  R EH1 - P ER0 T
+REPPOND  R EH1 - P AH0 N D
+REPPUCCI  R EH0 - P UW1 - CH IY0
+REPR  EH1 P
+REPREHENSIBLE  R EH2 - P R IH0 - HH EH1 N - S AH0 - B AH0 L
+REPRESENT  R EH2 - P R AH0 - Z EH1 N T
+REPRESENT(2)  R EH2 - P R IH0 - Z EH1 N T
+REPRESENTATION  R EH2 - P R AH0 - Z EH0 N - T EY1 - SH AH0 N
+REPRESENTATIONAL  R EH2 - P R AH0 - Z AH0 N - T EY1 - SH AH0 - N AH0 L
+REPRESENTATIONS  R EH2 - P R AH0 - Z AH0 N - T EY1 - SH AH0 N Z
+REPRESENTATIVE  R EH2 - P R AH0 - Z EH1 N - T AH0 - T IH0 V
+REPRESENTATIVE'S  R EH2 - P R IH0 - Z EH1 N - T AH0 - T IH0 V Z
+REPRESENTATIVE'S(2)  R EH2 - P R IH0 - Z EH1 - N AH0 - T IH0 V Z
+REPRESENTATIVE(2)  R EH2 - P R IH0 - Z EH1 N - T AH0 - T IH0 V
+REPRESENTATIVE(3)  R EH2 - P R AH0 - Z EH1 - N AH0 - T IH0 V
+REPRESENTATIVE(4)  R EH2 - P R IH0 - Z EH1 - N AH0 - T IH0 V
+REPRESENTATIVES  R EH2 - P R AH0 - Z EH1 N - T AH0 - T IH0 V Z
+REPRESENTATIVES'  R EH2 - P R AH0 - S EH1 N - T AH0 - T IH0 V Z
+REPRESENTATIVES'(2)  R EH2 - P R AH0 - S EH1 - N AH0 - T IH0 V Z
+REPRESENTATIVES(2)  R EH2 - P R IH0 - Z EH1 N - T AH0 - T IH0 V Z
+REPRESENTATIVES(3)  R EH2 - P R AH0 - Z EH1 - N AH0 - T IH0 V Z
+REPRESENTATIVES(4)  R EH2 - P R IH0 - Z EH1 - N AH0 - T IH0 V Z
+REPRESENTED  R EH2 - P R AH0 - Z EH1 N - T AH0 D
+REPRESENTED(2)  R EH2 - P R IH0 - Z EH1 N - T IH0 D
+REPRESENTED(3)  R EH2 - P R AH0 - Z EH1 - N AH0 D
+REPRESENTED(4)  R EH2 - P R IH0 - Z EH1 - N IH0 D
+REPRESENTING  R EH2 - P R IH0 - Z EH1 N - T IH0 NG
+REPRESENTING(2)  R EH2 - P R IH0 - Z EH1 - N IH0 NG
+REPRESENTS  R EH2 - P R AH0 - Z EH1 N T S
+REPRESENTS(2)  R EH2 - P R IH0 - Z EH1 N T S
+REPRESS  R IY0 - P R EH1 S
+REPRESSED  R IY0 - P R EH1 S T
+REPRESSING  R IY0 - P R EH1 - S IH0 NG
+REPRESSION  R IY0 - P R EH1 - SH AH0 N
+REPRESSIONS  R IY0 - P R EH1 - SH AH0 N Z
+REPRESSIVE  R IY0 - P R EH1 - S IH0 V
+REPRICE  R IY0 - P R AY1 S
+REPRICED  R IY0 - P R AY1 S T
+REPRICING  R IY0 - P R AY1 - S IH0 NG
+REPRIEVE  R IY0 - P R IY1 V
+REPRIMAND  R EH1 - P R AH0 - M AE2 N D
+REPRIMANDED  R EH1 - P R AH0 - M AE2 N - D IH0 D
+REPRIMANDS  R EH1 - P R AH0 - M AE2 N D Z
+REPRINT  R IY0 - P R IH1 N T
+REPRINTED  R IY0 - P R IH1 N - T IH0 D
+REPRINTING  R IY0 - P R IH1 N - T IH0 NG
+REPRINTS  R IY0 - P R IH1 N T S
+REPRISAL  R IY0 - P R AY1 - Z AH0 L
+REPRISALS  R IH0 - P R AY1 - Z AH0 L Z
+REPRISALS(2)  R IY0 - P R AY1 - Z AH0 L Z
+REPRISE  R IH0 - P R AY1 Z
+REPRISE(2)  R IH0 - P R IY1 Z
+REPROACH  R IY0 - P R OW1 CH
+REPROBATE  R EH1 - P R AO0 - B EY0 T
+REPROCESS  R IY0 - P R AO1 - S EH0 S
+REPROCESSED  R IY0 - P R AO1 - S EH0 S T
+REPROCESSING  R IY0 - P R AO1 - S EH0 - S IH0 NG
+REPRODUCE  R IY2 - P R AH0 - D UW1 S
+REPRODUCED  R IY2 - P R AH0 - D UW1 S T
+REPRODUCES  R IY2 - P R AH0 - D UW1 - S IH0 Z
+REPRODUCING  R IY2 - P R AH0 - D UW1 - S IH0 NG
+REPRODUCTION  R IY2 - P R AH0 - D AH1 K - SH AH0 N
+REPRODUCTIONS  R IY2 - P R AH0 - D AH1 K - SH AH0 N Z
+REPRODUCTIVE  R IY2 - P R AH0 - D AH1 K - T IH0 V
+REPROGRAM  R IY0 - P R OW1 - G R AE2 M
+REPROGRAMMED  R IY0 - P R OW1 - G R AE2 M D
+REPROGRAMMING  R IY0 - P R OW1 - G R AE2 - M IH0 NG
+REPROGRAMS  R IY0 - P R OW1 - G R AE2 M Z
+REPROGRAPH  R EH1 - P R OW0 - G R AE2 F
+REPROGRAPHIC  R EH2 - P R OW0 - G R AE1 - F IH0 K
+REPROGRAPHICS  R EH2 - P R OW0 - G R AE1 - F IH0 K S
+REPS  R EH1 P S
+REPSHER  R EH1 P - SH ER0
+REPSOL  R EH1 P - S AA0 L
+REPTILE  R EH1 P - T AY0 L
+REPTILES  R EH1 P - T AY0 L Z
+REPUBLIC  R IY0 - P AH1 - B L AH0 K
+REPUBLIC'S  R IY0 - P AH1 - B L IH0 K S
+REPUBLIC(2)  R IY0 - P AH1 - B L IH0 K
+REPUBLICAN  R IH0 - P AH1 - B L IH0 - K AH0 N
+REPUBLICAN'S  R IY0 - P AH1 - B L IH0 - K AH0 N Z
+REPUBLICAN(2)  R IY0 - P AH1 - B L AH0 - K AH0 N
+REPUBLICAN(3)  R IY0 - P AH1 - B L IH0 - K AH0 N
+REPUBLICANISM  R IH0 - P AH1 - B L IH0 - K AH0 - N IH2 - Z AH0 M
+REPUBLICANS  R IH0 - P AH1 - B L IH0 - K AH0 N Z
+REPUBLICANS'  R IH0 - P AH1 - B L IH0 - K AH0 N Z
+REPUBLICANS'(2)  R IY0 - P AH1 - B L IH0 - K AH0 N Z
+REPUBLICANS(2)  R IY0 - P AH1 - B L AH0 - K AH0 N Z
+REPUBLICANS(3)  R IY0 - P AH1 - B L IH0 - K AH0 N Z
+REPUBLICBANK  R IY0 - P AH1 - B L IH0 K - B AE2 NG K
+REPUBLICBANK'S  R IY0 - P AH1 - B L IH0 K - B AE2 NG K S
+REPUBLICS  R IY0 - P AH1 - B L IH0 K S
+REPUDIATE  R IY0 - P Y UW1 - D IY0 - EY2 T
+REPUDIATED  R IY0 - P Y UW1 - D IY0 - EY2 - T AH0 D
+REPUDIATES  R IY0 - P Y UW1 - D IY0 - EY2 T S
+REPUDIATING  R IY0 - P Y UW1 - D IY0 - EY2 - T IH0 NG
+REPUDIATION  R IH0 - P Y UW2 - D IY0 - EY1 - SH AH0 N
+REPUGNANT  R IH0 - P AH1 G - N AH0 N T
+REPUGNANT(2)  R IY0 - P AH1 G - N AH0 N T
+REPULSE  R IY0 - P AH1 L S
+REPULSED  R IY0 - P AH1 L S T
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+REPURCHASE  R IY0 - P ER1 - CH AH0 S
+REPURCHASED  R IY0 - P ER1 - CH AH0 S T
+REPURCHASES  R IY0 - P ER1 - CH AH0 - S IH0 Z
+REPURCHASING  R IY0 - P ER1 - CH AH0 - S IH0 NG
+REPUTABLE  R EH1 - P Y AH0 - T AH0 - B AH0 L
+REPUTATION  R EH2 - P Y AH0 - T EY1 - SH AH0 N
+REPUTATIONS  R EH2 - P Y AH0 - T EY1 - SH AH0 N Z
+REPUTE  R IY0 - P Y UW1 T
+REPUTED  R IH0 - P Y UW1 - T IH0 D
+REPUTED(2)  R IY0 - P Y UW1 - T AH0 D
+REPUTED(3)  R IY0 - P Y UW1 - T IH0 D
+REPUTEDLY  R IH0 - P Y UW1 - T IH0 D - L IY0
+REQUA  R EY1 - K W AH0
+REQUALIFY  R IY2 - K W AA1 - L AH0 - F AY2
+REQUEST  R IH0 - K W EH1 S T
+REQUEST(2)  R IY0 - K W EH1 S T
+REQUESTED  R IH0 - K W EH1 - S T IH0 D
+REQUESTED(2)  R IY0 - K W EH1 - S T AH0 D
+REQUESTED(3)  R IY0 - K W EH1 - S T IH0 D
+REQUESTER  R IH0 - K W EH1 - S T ER0
+REQUESTING  R IH0 - K W EH1 - S T IH0 NG
+REQUESTING(2)  R IY0 - K W EH1 - S T IH0 NG
+REQUESTS  R IH0 - K W EH1 S T S
+REQUESTS(2)  R IY0 - K W EH1 S T S
+REQUESTS(3)  R IH0 - K W EH1 S S
+REQUESTS(4)  R IY0 - K W EH1 S S
+REQUESTS(5)  R IH0 - K W EH1 S
+REQUESTS(6)  R IY0 - K W EH1 S
+REQUIEM  R EH1 - K W IY0 - AH0 M
+REQUIRE  R IY2 - K W AY1 - ER0
+REQUIRE(2)  R IY0 - K W AY1 R
+REQUIRE(3)  R IH0 - K W AY1 - ER0
+REQUIRED  R IY0 - K W AY1 - ER0 D
+REQUIRED(2)  R IY0 - K W AY1 R D
+REQUIREMENT  R IH0 - K W AY1 R - M AH0 N T
+REQUIREMENTS  R IH0 - K W AY1 R - M AH0 N T S
+REQUIRES  R IY0 - K W AY1 - ER0 Z
+REQUIRES(2)  R IY0 - K W AY1 R Z
+REQUIRING  R IY0 - K W AY1 - ER0 - IH0 NG
+REQUIRING(2)  R IY0 - K W AY1 - R IH0 NG
+REQUISITE  R EH1 - K W AH0 - Z AH0 T
+REQUISITES  R EH1 - K W AH0 - Z AH0 T S
+REQUISITION  R EH2 - K W AH0 - Z IH1 - SH AH0 N
+REQUISITIONED  R EH2 - K W AH0 - Z IH1 - SH AH0 N D
+REREAD  R IY1 - R IY1 D
+REREADING  R IY1 - R IY1 - D IH0 NG
+REREGULATE  R IY0 - R EH1 - G Y AH0 - L EY2 T
+REREGULATION  R IY0 - R EH0 - G Y AH0 - L EY1 - SH AH0 N
+REROUTE  R IY0 - R UW1 T
+REROUTE(2)  R IY0 R - AW1 T
+REROUTED  R IY0 - R UW1 - T IH0 D
+REROUTED(2)  R IY0 - R AW1 - T IH0 D
+REROUTING  R IY0 - R UW1 - T IH0 NG
+REROUTING(2)  R IY0 - R AW1 - T IH0 NG
+RERUN  R IY1 - R AH1 N
+RERUNNING  R IY1 - R AH1 - N IH0 NG
+RERUNS  R IY1 - R AH1 N Z
+RES  R EY1 Z
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+RESALES  R IY1 - S EY2 L Z
+RESCH  R EH1 SH
+RESCHEDULE  R IY0 - S K EH1 - JH UW0 L
+RESCHEDULED  R IY0 - S K EH1 - JH UW0 L D
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+RESCHEDULINGS  R IY0 SH - K EH1 - JH UW0 - L IH0 NG Z
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+RESCINDED  R IH0 - S IH1 N - D IH0 D
+RESCINDED(2)  R IY0 - S IH1 N - D AH0 D
+RESCINDED(3)  R IY0 - S IH1 N - D IH0 D
+RESCINDING  R IH0 - S IH1 N - D IH0 NG
+RESCISSION  R IH0 - S IH1 - ZH AH0 N
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+RESCUE  R EH1 - S K Y UW0
+RESCUED  R EH1 - S K Y UW0 D
+RESCUER  R EH1 - S K Y UW2 - ER0
+RESCUERS  R EH1 - S K Y UW2 - ER0 Z
+RESCUES  R EH1 - S K Y UW2 Z
+RESCUING  R EH1 - S K Y UW0 - IH0 NG
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+RESEACHERS  R IY0 - S ER1 - CH ER0 Z
+RESEAL  R IY0 - S IY1 L
+RESEALABLE  R IY0 - S IY1 - L AH0 - B AH0 L
+RESEALED  R IY0 - S IY1 L D
+RESEALS  R IY0 - S IY1 L Z
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+RESEARCH(2)  R IY1 - S ER0 CH
+RESEARCHED  R IY0 - S ER1 CH T
+RESEARCHER  R IY1 - S ER0 - CH ER0
+RESEARCHERS  R IY1 - S ER0 - CH ER0 Z
+RESEARCHERS'  R IY1 - S ER0 - CH ER0 Z
+RESEARCHES  R IY0 - S ER1 - CH IH0 Z
+RESEARCHING  R IY0 - S ER1 - CH IH0 NG
+RESEDA  R EH0 - S EY1 - D AH0
+RESEED  R IY0 - S IY1 D
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+RESELLER  R IY0 - S EH1 - L ER0
+RESELLERS  R IY0 - S EH1 - L ER0 Z
+RESELLING  R IY0 - S EH1 - L IH0 NG
+RESELLS  R IY0 - S EH1 L Z
+RESEMBLANCE  R IH0 - Z EH1 M - B L AH0 N S
+RESEMBLANCE(2)  R IY0 - Z EH1 M - B L AH0 N S
+RESEMBLANCES  R IY0 - Z EH1 M - B L AH0 N - S AH0 Z
+RESEMBLE  R IH0 - Z EH1 M - B AH0 L
+RESEMBLE(2)  R IY0 - Z EH1 M - B AH0 L
+RESEMBLED  R IH0 - Z EH1 M - B AH0 L D
+RESEMBLED(2)  R IY0 - Z EH1 M - B AH0 L D
+RESEMBLES  R IH0 - Z EH1 M - B AH0 L Z
+RESEMBLES(2)  R IY0 - Z EH1 M - B AH0 L Z
+RESEMBLING  R IH0 - Z EH1 M - B AH0 L - IH0 NG
+RESEMBLING(2)  R IY0 - Z EH1 M - B AH0 L - IH0 NG
+RESEMBLING(3)  R IY0 - Z EH1 M - B L IH0 NG
+RESENDE  R IH0 - S EH1 N - D EY0
+RESENDES  R EH1 - S IH0 N D Z
+RESENDEZ  R EY0 - S EY1 N - D EH0 Z
+RESENDIZ  R IH0 - S EH1 N - D IH0 Z
+RESENT  R IH0 - Z EH1 N T
+RESENT(2)  R IY0 - Z EH1 N T
+RESENTED  R IY0 - Z EH1 N - T AH0 D
+RESENTED(2)  R IY0 - Z EH1 - N AH0 D
+RESENTFUL  R IH0 - Z EH1 N T - F AH0 L
+RESENTING  R IH0 - Z EH1 N - T IH0 NG
+RESENTING(2)  R IY0 - Z EH1 N - T IH0 NG
+RESENTING(3)  R IH0 - Z EH1 - N IH0 NG
+RESENTING(4)  R IY0 - Z EH1 - N IH0 NG
+RESENTMENT  R IH0 - Z EH1 N T - M AH0 N T
+RESENTMENT(2)  R IH0 - Z EH1 N - M AH0 N T
+RESENTMENTS  R IH0 - Z EH1 N T - M AH0 N T S
+RESENTMENTS(2)  R IH0 - Z EH1 N - M AH0 N T S
+RESENTS  R IH0 - Z EH1 N T S
+RESER  R IY1 - Z ER0
+RESERVATION  R EH2 - Z ER0 - V EY1 - SH AH0 N
+RESERVATIONIST  R EH2 - Z ER0 - V EY1 - SH AH0 N - IH0 S T
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+RESERVATIONS  R EH2 - Z ER0 - V EY1 - SH AH0 N Z
+RESERVE  R IH0 - Z ER1 V
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+RESERVE'S(2)  R IY0 - Z ER1 V Z
+RESERVE(2)  R IY0 - Z ER1 V
+RESERVED  R IH0 - Z ER1 V D
+RESERVED(2)  R IY0 - Z ER1 V D
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+RESERVES  R IH0 - Z ER1 V Z
+RESERVES(2)  R IY0 - Z ER1 V Z
+RESERVING  R IH0 - Z ER1 - V IH0 NG
+RESERVING(2)  R IY0 - Z ER1 - V IH0 NG
+RESERVIST  R IH0 - Z ER1 - V IH0 S T
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+RESERVISTS(2)  R IH0 - Z ER1 - V IH0 S S
+RESERVISTS(3)  R IH0 - Z ER1 - V IH0 S
+RESERVOIR  R EH1 - Z AH0 - V W AA2 R
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+RESERVOIRS  R EH1 - Z ER0 - V W AA2 R Z
+RESET  R IY0 - S EH1 T
+RESET(2)  R IY1 - S EH0 T
+RESETAR  R EH1 - S IH0 - T ER0
+RESETING  R IY0 - S EH1 - T IH0 NG
+RESETING(2)  R IY1 - S EH0 - T IH0 NG
+RESETS  R IY0 - S EH1 T S
+RESETS(2)  R IY1 - S EH0 T S
+RESETTABLE  R IY0 - S EH1 - T AH0 - B AH0 L
+RESETTLE  R IY0 - S EH1 - T AH0 L
+RESETTLED  R IY0 - S EH1 - T AH0 L D
+RESETTLEMENT  R IY0 - S EH1 - T AH0 L - M AH0 N T
+RESH  R EH1 SH
+RESHAPE  R IY0 - SH EY1 P
+RESHAPED  R IY0 - SH EY1 P T
+RESHAPING  R IY0 - SH EY1 - P IH0 NG
+RESHOT  R IY0 - SH AO1 T
+RESHUFFLE  R IY0 - SH AH1 - F AH0 L
+RESHUFFLED  R IY0 - SH AH1 - F AH0 L D
+RESHUFFLING  R IY0 - SH AH1 - F AH0 L - IH0 NG
+RESHUFFLING(2)  R IY0 - SH AH1 - F L IH0 NG
+RESIDE  R IH0 - Z AY1 D
+RESIDE(2)  R IY0 - Z AY1 D
+RESIDED  R IH0 - Z AY1 - D IH0 D
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+RESIDENCIES  R EH1 - Z IH0 - D EH2 N - S IY0 Z
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+RESIDENT  R EH1 - Z IH0 - D AH0 N T
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+RESIDENTIAL  R EH2 - Z IH0 - D EH1 N - CH AH0 L
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+RESIDES  R IH0 - Z AY1 D Z
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+RESIDING  R IH0 - Z AY1 - D IH0 NG
+RESIDING(2)  R IY0 - Z AY1 - D IH0 NG
+RESIDUAL  R IH0 - Z IH1 - JH UW0 - AH0 L
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+RESIDUE  R EH1 - Z AH0 - D UW2
+RESIDUES  R EH1 - Z AH0 - D UW2 Z
+RESIGN  R IH0 - Z AY1 N
+RESIGN(2)  R IY0 - Z AY1 N
+RESIGN(3)  R IY0 - S AY1 N
+RESIGNATION  R EH2 - Z AH0 G - N EY1 - SH AH0 N
+RESIGNATION(2)  R EH2 - Z IH0 G - N EY1 - SH AH0 N
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+RESIGNED  R IH0 - Z AY1 N D
+RESIGNED(2)  R IY0 - Z AY1 N D
+RESIGNED(3)  R IY0 - S AY1 N D
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+RESIGNEES  R EH2 - Z IH0 G - N IY1 Z
+RESIGNING  R IH0 - Z AY1 - N IH0 NG
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+RESIGNING(3)  R IY0 - S AY1 - N IH0 NG
+RESIGNS  R IH0 - Z AY1 N Z
+RESIGNS(2)  R IY0 - Z AY1 N Z
+RESIGNS(3)  R IY0 - S AY1 N Z
+RESILIENCE  R IH0 - Z IH1 - L IY0 - AH0 N S
+RESILIENCE(2)  R IH0 - Z IH1 - L Y AH0 N S
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+RESISTANCE(2)  R IY0 - Z IH1 - S T AH0 N S
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+RESISTANT(2)  R IY0 - Z IH1 - S T AH0 N T
+RESISTED  R IH0 - Z IH1 - S T IH0 D
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+RESISTIVENESS  R IH2 - Z IH1 - S T IH2 V - N AH0 S
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+RESISTS(4)  R IY0 - Z IH1 S S
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+RESNICK  R EH1 Z - N IH0 K
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+RESO(3)  R IH1 - S OW0
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+RESOLD  R IY0 - S OW1 L D
+RESOLUTE  R EH1 - Z AH0 - L UW2 T
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+RESOLUTION  R EH2 - Z AH0 - L UW1 - SH AH0 N
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+RESOLUTIONS  R EH2 - Z AH0 - L UW1 - SH AH0 N Z
+RESOLVE  R IY0 - Z AA1 L V
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+RESOUND  R IY2 - S AW1 N D
+RESOUND(2)  R IY2 - Z AW1 N D
+RESOUNDING  R IY0 - S AW1 N - D IH0 NG
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+RESPECTABLE  R IH0 - S P EH1 K - T AH0 - B AH0 L
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+RESPECTABLY  R IY0 - S P EH1 K - T AH0 - B L IY0
+RESPECTED  R IH0 - S P EH1 K - T IH0 D
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+RESPECTFUL  R IH0 - S P EH1 K T - F AH0 L
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+RESPIRATION  R EH2 - S P ER0 - EY1 - SH AH0 N
+RESPIRATOR  R EH1 - S P ER0 - EY2 - T ER0
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+RESPIRATORY  R EH1 - S P ER0 - AH0 - T AO2 - R IY0
+RESPIRONIC  R EH2 - S P ER0 - AA1 - N IH0 K
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+RESPONDENT  R IH0 - S P AA1 N - D AH0 N T
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+RESPONDERS  R IH0 - S P AA1 N - D ER0 Z
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+RESPONSE  R IH0 - S P AA1 N S
+RESPONSE(2)  R IY0 - S P AA1 N S
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+RESPONSES(2)  R IY0 - S P AA1 N - S AH0 Z
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+RESPONSIBILITIES  R IY0 - S P AA2 N - S AH0 - B IH1 - L AH0 - T IY0 Z
+RESPONSIBILITY  R IY0 - S P AA2 N - S AH0 - B IH1 - L AH0 - T IY0
+RESPONSIBLE  R IY0 - S P AA1 N - S AH0 - B AH0 L
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+RESPONSIVENESS  R IH0 - S P AA1 N - S IH0 V - N AH0 S
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+RESSA  R EH1 - S AH0
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+RESSEGUIE  R EH1 - S IH0 - G W IY0
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+RESTAGE  R IY0 - S T EY1 JH
+RESTAGED  R IY0 - S T EY1 JH D
+RESTAINO  R EH0 - S T AA0 - IY1 - N OW0
+RESTART  R IY0 - S T AA1 R T
+RESTARTED  R IY0 - S T AA1 R - T IH0 D
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+RESTATING  R IY0 - S T EY1 - T IH0 NG
+RESTAURANT  R EH1 - S T ER0 - AA2 N T
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+RESTAURANT'S(2)  R EH1 - S T R AA2 N T S
+RESTAURANT(2)  R EH1 - S T R AA2 N T
+RESTAURANTS  R EH1 - S T ER0 - AA2 N T S
+RESTAURANTS'  R EH1 - S T ER0 - AA2 N T S
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+RESTAURATEUR  R EH2 - S T ER0 - AH0 - T ER1
+RESTAURATEUR(2)  R EH2 - S T R AH0 - T ER1
+RESTAURATEURS  R EH2 - S T ER0 - AH0 - T ER1 Z
+RESTAURATEURS(2)  R EH2 - S T R AH0 - T ER1 Z
+RESTED  R EH1 - S T AH0 D
+RESTED(2)  R EH1 - S T IH0 D
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+RESTFUL  R EH1 S T - F AH0 L
+RESTING  R EH1 - S T IH0 NG
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+RESTITUTION  R EH2 - S T IH0 - T UW1 - SH AH0 N
+RESTIVE  R EH1 - S T IH0 V
+RESTIVENESS  R EH1 - S T IH0 V - N AH0 S
+RESTIVO  R EH0 - S T IY1 - V OW0
+RESTLESS  R EH1 S T - L AH0 S
+RESTLESSLY  R EH1 S T - L AH0 S - L IY0
+RESTLESSNESS  R EH1 S T - L AH0 S - N AH0 S
+RESTO  R EH1 - S T OW0
+RESTOCK  R IY0 - S T AA1 K
+RESTOCKED  R IY0 - S T AA1 K T
+RESTOCKING  R IY0 - S T AA1 - K IH0 NG
+RESTON  R EH1 - S T AH0 N
+RESTORATION  R EH2 - S T ER0 - EY1 - SH AH0 N
+RESTORATIONS  R EH2 - S T ER0 - EY1 - SH AH0 N Z
+RESTORATIVE  R AH0 - S T AO1 - R AH0 - T IH0 V
+RESTORE  R IH0 - S T AO1 R
+RESTORED  R IH0 - S T AO1 R D
+RESTORER  R IH0 - S T AO1 - R ER0
+RESTORES  R IH0 - S T AO1 R Z
+RESTORING  R IH0 - S T AO1 - R IH0 NG
+RESTRAIN  R IY0 - S T R EY1 N
+RESTRAINED  R IY0 - S T R EY1 N D
+RESTRAINING  R IY0 - S T R EY1 - N IH0 NG
+RESTRAINS  R IY0 - S T R EY1 N Z
+RESTRAINT  R IH0 - S T R EY1 N T
+RESTRAINT(2)  R IY0 - S T R EY1 N T
+RESTRAINTS  R IH0 - S T R EY1 N T S
+RESTRAINTS(2)  R IY0 - S T R EY1 N T S
+RESTREPO  R EH0 - S T R EH1 - P OW0
+RESTRICT  R IY0 - S T R IH1 K T
+RESTRICTED  R IY0 - S T R IH1 K - T AH0 D
+RESTRICTED(2)  R IY0 - S T R IH1 K - T IH0 D
+RESTRICTING  R IY0 - S T R IH1 K - T IH0 NG
+RESTRICTION  R IY0 S - T R IH1 K - SH AH0 N
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+RESTRICTIVE  R IY0 - S T R IH1 K - T IH0 V
+RESTRICTIVENESS  R AH0 - S T R IH1 K - T IH0 V - N AH0 S
+RESTRICTS  R IY0 - S T R IH1 K T S
+RESTROOM  R EH1 S T - R UW2 M
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+RESTRUCTURE  R IY0 - S T R AH1 K - CH ER0
+RESTRUCTURED  R IY0 - S T R AH1 K - CH ER0 D
+RESTRUCTURES  R IY0 - S T R AH1 K - CH ER0 Z
+RESTRUCTURING  R IY0 - S T R AH1 K - CH ER0 - IH0 NG
+RESTRUCTURINGS  R IY0 - S T R AH1 K - CH ER0 - IH0 NG Z
+RESTS  R EH1 S T S
+RESTYLE  R IY0 - S T AY1 L
+RESTYLED  R IY0 - S T AY1 L D
+RESUBMIT  R IY2 - S AH0 B - M IH1 T
+RESUBMITTED  R IY2 - S AH0 B - M IH1 - T IH0 D
+RESUBMITTING  R IY2 - S AH0 B - M IH1 - T IH0 NG
+RESULT  R IH0 - Z AH1 L T
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+RESULTED(3)  R IY0 - Z AH1 L - T IH0 D
+RESULTING  R IH0 - Z AH1 L - T IH0 NG
+RESULTING(2)  R IY0 - Z AH1 L - T IH0 NG
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+RESULTS(2)  R IY0 - Z AH1 L T S
+RESUME  R IH0 - Z UW1 M
+RESUME(2)  R IY0 - Z UW1 M
+RESUME(3)  R EH1 - Z AH0 - M EY2
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+RESUMES(2)  R IY0 - Z UW1 M Z
+RESUMES(3)  R EH1 - Z AH0 - M EY2 Z
+RESUMING  R IH0 - Z UW1 - M IH0 NG
+RESUMING(2)  R IY0 - Z UW1 - M IH0 NG
+RESUMPTION  R IH0 - Z AH1 M P - SH AH0 N
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+RESURFACED  R IY0 - S ER1 - F AH0 S T
+RESURFACING  R IY0 - S ER1 - F AH0 - S IH0 NG
+RESURGENCE  R IY0 - S ER1 - JH AH0 N S
+RESURGENCY  R IH0 - S ER1 - JH AH0 N - S IY0
+RESURGENCY(2)  R IY0 - S ER1 - JH AH0 N - S IY0
+RESURGENT  R IH0 - S ER1 - JH AH0 N T
+RESURGENT(2)  R IY0 - S ER1 - JH AH0 N T
+RESURGING  R IY0 - S ER1 - JH IH0 NG
+RESURRECT  R EH2 - Z ER0 - EH1 K T
+RESURRECTED  R EH2 - Z ER0 - EH1 K - T IH0 D
+RESURRECTING  R EH2 - Z ER0 - EH1 K - T IH0 NG
+RESURRECTION  R EH2 - Z ER0 - EH1 K - SH AH0 N
+RESUSCITATE  R IH0 - S AH1 - S IH0 - T EY2 T
+RESUSCITATE(2)  R IY0 - S AH1 - S IH0 - T EY2 T
+RESUSCITATED  R IH0 - S AH1 - S IH0 - T EY2 - T IH0 D
+RESUSCITATING  R IH0 - S AH1 - S IH0 - T EY2 - T IH0 NG
+RESUSCITATION  R IH0 - S AH2 - S IH0 - T EY1 - SH AH0 N
+RET  R EH1 T
+RETA  R EH1 - T AH0
+RETABLOS  R IY0 - T AE1 - B L OW0 S
+RETAIL  R IY1 - T EY2 L
+RETAILED  R IY1 - T EY2 L D
+RETAILER  R IY1 - T EY2 - L ER0
+RETAILER'S  R IY1 - T EY2 - L ER0 Z
+RETAILERS  R IY1 - T EY2 - L ER0 Z
+RETAILERS'  R IY1 - T EY2 - L ER0 Z
+RETAILING  R IY1 - T EY2 - L IH0 NG
+RETAILING'S  R IY1 - T EY2 - L IH0 NG Z
+RETAILS  R IY1 - T EY2 L Z
+RETAIN  R IH0 - T EY1 N
+RETAIN(2)  R IY0 - T EY1 N
+RETAINED  R IH0 - T EY1 N D
+RETAINED(2)  R IY0 - T EY1 N D
+RETAINER  R IH0 - T EY1 - N ER0
+RETAINER(2)  R IY0 - T EY1 - N ER0
+RETAINERS  R IH0 - T EY1 - N ER0 Z
+RETAINING  R IH0 - T EY1 - N IH0 NG
+RETAINING(2)  R IY0 - T EY1 - N IH0 NG
+RETAINS  R IH0 - T EY1 N Z
+RETAINS(2)  R IY0 - T EY1 N Z
+RETAKE  R IY1 - T EY1 K
+RETAKE(2)  R IY0 - T EY1 K
+RETAKEN  R IY0 - T EY1 - K AH0 N
+RETAKING  R IY0 - T EY1 - K IH0 NG
+RETALIATE  R IH0 - T AE1 - L IY0 - EY2 T
+RETALIATE(2)  R IY0 - T AE1 - L IY0 - EY2 T
+RETALIATED  R IH0 - T AE1 - L IY0 - EY2 - T IH0 D
+RETALIATED(2)  R IY0 - T AE1 - L IY0 - EY2 - T IH0 D
+RETALIATING  R IH0 - T AE1 - L IY0 - EY2 - T IH0 NG
+RETALIATION  R IY0 - T AE2 - L IY0 - EY1 - SH AH0 N
+RETALIATORY  R IY0 - T AE1 - L Y AH0 - T AO2 - R IY0
+RETANA  R EH0 - T AE1 - N AH0
+RETARD  R IH0 - T AA1 R D
+RETARD(2)  R IY0 - T AA1 R D
+RETARDANT  R IY0 - T AA1 R - D AH0 N T
+RETARDATION  R IY0 - T AA0 R - D EY1 - SH AH0 N
+RETARDED  R IH0 - T AA1 R - D IH0 D
+RETARDED(2)  R IY0 - T AA1 R - D AH0 D
+RETARDED(3)  R IY0 - T AA1 R - D IH0 D
+RETARDING  R IH0 - T AA1 R - D IH0 NG
+RETARDING(2)  R IY0 - T AA1 R - D IH0 NG
+RETARDS  R IH0 - T AA1 R D Z
+RETARDS(2)  R IY0 - T AA1 R D Z
+RETELL  R IY0 - T EH1 L
+RETELLING  R IY0 - T EH1 - L IH0 NG
+RETEMEYER  R EH1 - T AH0 - M AY2 R
+RETENTION  R IY0 - T EH1 N - SH AH0 N
+RETEST  R IY1 - T EH1 S T
+RETESTED  R IY0 - T EH1 - S T IH0 D
+RETESTING  R IY0 - T EH1 - S T IH0 NG
+RETESTS  R IY1 - T EH1 S T S
+RETESTS(2)  R IY1 - T EH1 S S
+RETESTS(3)  R IY1 - T EH1 S
+RETHERFORD  R IH0 - TH ER1 - F ER0 D
+RETHINK  R IY0 - TH IH1 NG K
+RETHINKING  R IY0 - TH IH1 NG - K IH0 NG
+RETHOUGHT  R IY0 - TH AO1 T
+RETICENCE  R EH1 - T IH0 - S AH0 N S
+RETICENT  R EH1 - T IH0 - S AH0 N T
+RETIN  R EH1 - T IH0 N
+RETINA  R EH1 - T AH0 - N AH0
+RETINAL  R EH1 - T AH0 - N AH0 L
+RETINOBLASTOMA  R EH2 - T IH0 - N OW2 - B L AE2 - S T OW1 - M AH0
+RETINOID  R EH1 - T IH0 - N OY0 D
+RETINOIDS  R EH1 - T IH0 - N OY0 D Z
+RETINUE  R EH1 - T AH0 - N UW2
+RETINYL  R EH1 - T IH0 - N AH0 L
+RETIRE  R IH0 - T AY1 R
+RETIRE(2)  R IY0 - T AY1 R
+RETIRE(3)  R IY2 - T AY1 - ER0
+RETIRED  R IH0 - T AY1 R D
+RETIRED(2)  R IY0 - T AY1 - ER0 D
+RETIRED(3)  R IY0 - T AY1 R D
+RETIREE  R IY0 - T AY1 - R IY1
+RETIREE'S  R IH0 - T AY2 - R IY1 Z
+RETIREES  R IY0 - T AY1 - R IY1 Z
+RETIREES'  R IH0 - T AY2 - R IY1 Z
+RETIREMENT  R IY0 - T AY1 - ER0 - M AH0 N T
+RETIREMENT(2)  R IH0 - T AY1 - ER0 - M AH0 N T
+RETIREMENTS  R IH0 - T AY1 R - M AH0 N T S
+RETIREMENTS(2)  R IY0 - T AY1 R - M AH0 N T S
+RETIRES  R IH0 - T AY1 R Z
+RETIRES(2)  R IY0 - T AY1 - ER0 Z
+RETIRES(3)  R IY0 - T AY1 R Z
+RETIRING  R IH0 - T AY1 - R IH0 NG
+RETIRING(2)  R IY0 - T AY1 - ER0 - IH0 NG
+RETIRING(3)  R IY0 - T AY1 - R IH0 NG
+RETLIN  R EH1 T - L IH0 N
+RETO  R IY1 - T UW1
+RETOOK  R IY0 - T UH1 K
+RETOOL  R IY0 - T UW1 L
+RETOOLED  R IY0 - T UW1 L D
+RETOOLING  R IY0 - T UW1 - L IH0 NG
+RETORT  R IY1 - T AO2 R T
+RETORTED  R IY0 - T AO1 R - T IH0 D
+RETORTS  R IH0 - T AO1 R T S
+RETORTS(2)  R IY0 - T AO1 R T S
+RETOUCHING  R IY0 - T AH1 - CH IH0 NG
+RETRACE  R IY0 - T R EY1 S
+RETRACED  R IY0 - T R EY1 S T
+RETRACEMENT  R IY0 - T R EY1 S - M AH0 N T
+RETRACING  R IY0 - T R EY1 - S IH0 NG
+RETRACT  R IY0 - T R AE1 K T
+RETRACTABLE  R IY0 - T R AE1 K - T AH0 - B AH0 L
+RETRACTED  R IY0 - T R AE1 K - T AH0 D
+RETRACTING  R IY0 - T R AE1 K - T IH0 NG
+RETRACTION  R IY0 - T R AE1 K - SH AH0 N
+RETRACTS  R IY0 - T R AE1 K T S
+RETRAIN  R IY0 - T R EY1 N
+RETRAINED  R IY0 - T R EY1 N D
+RETRAINING  R IY0 - T R EY1 - N IH0 NG
+RETRANSMISSION  R IY2 - T R AE0 N Z - M IH1 - SH AH0 N
+RETREAD  R IY0 - T R EH1 D
+RETREADING  R IY0 - T R EH1 - D IH0 NG
+RETREADS  R IY0 - T R EH1 D Z
+RETREAT  R IY0 - T R IY1 T
+RETREATED  R IY0 - T R IY1 - T AH0 D
+RETREATED(2)  R IY0 - T R IY1 - T IH0 D
+RETREATING  R IY0 - T R IY1 - T IH0 NG
+RETREATS  R IY0 - T R IY1 T S
+RETRENCH  R IY0 - T R EH1 N CH
+RETRENCHED  R IY0 - T R EH1 N CH T
+RETRENCHING  R IY0 - T R EH1 N - CH IH0 NG
+RETRENCHMENT  R IY0 - T R EH1 N CH - M AH0 N T
+RETRENCHMENTS  R IY0 - T R EH1 N CH - M AH0 N T S
+RETRIAL  R IY0 - T R AY1 - AH0 L
+RETRIBUTION  R EH2 - T R AH0 - B Y UW1 - SH AH0 N
+RETRIED  R IY0 - T R AY1 D
+RETRIEVAL  R IH0 - T R IY1 - V AH0 L
+RETRIEVAL(2)  R IY0 - T R IY1 - V AH0 L
+RETRIEVE  R IH0 - T R IY1 V
+RETRIEVE(2)  R IY0 - T R IY1 V
+RETRIEVED  R IY0 - T R IY1 V D
+RETRIEVER  R IY0 - T R IY1 - V ER0
+RETRIEVERS  R IY0 - T R IY1 - V ER0 Z
+RETRIEVES  R IH0 - T R IY1 V Z
+RETRIEVES(2)  R IY0 - T R IY1 V Z
+RETRIEVING  R IY0 - T R IY1 - V IH0 NG
+RETRO  R EH1 - T R OW0
+RETROACTIVE  R EH2 - T R OW0 - AE1 K - T IH0 V
+RETROACTIVELY  R EH2 - T R OW0 - AE1 K - T IH0 V - L IY0
+RETROACTIVITY  R EH2 - T R OW0 - AE0 K - T IH1 - V IH0 - T IY0
+RETROFIT  R EH1 - T R OW0 - F IH2 T
+RETROFITS  R EH1 - T R OW0 - F IH2 T S
+RETROFITTED  R EH1 - T R OW2 - F IH2 - T IH0 D
+RETROFITTER  R EH1 - T R OW2 - F IH2 - T ER0
+RETROFITTING  R EH1 - T R OW0 - F IH2 - T IH0 NG
+RETROGRADE  R EH1 - T R AH0 - G R EY2 D
+RETROSPECT  R EH1 - T R AH0 - S P EH2 K T
+RETROSPECTIVE  R EH2 - T R AH0 - S P EH1 K - T IH0 V
+RETROSPECTIVELY  R EH2 - T R OW0 - S P EH1 K - T IH0 V - L IY0
+RETROVIR  R EH1 - T R OW0 - V IH2 R
+RETROVIRUS  R EH2 - T R OW0 - V AY1 - R AH0 S
+RETROVIRUSES  R EH2 - T R OW0 - V AY1 - R AH0 - S IH0 Z
+RETRY  R IY0 - T R AY1
+RETRYING  R IY0 - T R AY1 - IH0 NG
+RETTBERG  R EH1 T - B ER0 G
+RETTER  R EH1 - T ER0
+RETTEW  R EH1 - CH UW0
+RETTIG  R EH1 - T IH0 G
+RETTINGER  R EH1 - T IH0 N - JH ER0
+RETTINGER(2)  R EH1 - T IH0 - NG ER0
+RETTKE  R EH1 T - K IY0
+RETTON  R EH1 - T AH0 N
+RETURN  R IH0 - T ER1 N
+RETURN(2)  R IY0 - T ER1 N
+RETURNABLE  R IY0 - T ER1 - N AH0 - B AH0 L
+RETURNED  R IH0 - T ER1 N D
+RETURNED(2)  R IY0 - T ER1 N D
+RETURNEE  R IH0 - T ER0 - N IY1
+RETURNEES  R IH0 - T ER0 - N IY1 Z
+RETURNING  R IH0 - T ER1 - N IH0 NG
+RETURNING(2)  R IY0 - T ER1 - N IH0 NG
+RETURNS  R IH0 - T ER1 N Z
+RETURNS'  R AH0 - T ER1 N Z
+RETURNS'(2)  R IY0 - T ER1 N Z
+RETURNS(2)  R IY0 - T ER1 N Z
+RETZ  R EH1 T S
+RETZER  R EH1 T - Z ER0
+RETZLAFF  R EH1 T Z - L AH0 F
+RETZLOFF  R EH1 T Z - L AO0 F
+REUBEN  R UW1 - B AH0 N
+REUBER  R OY1 - B ER0
+REUL  R UW1 L
+REULAND  R OY1 - L AH0 N D
+REULE  R UW1 L
+REUM  R IY1 - AH0 M
+REUNIFICATION  R IY0 - UW2 - N AH0 - F AH0 - K EY1 - SH AH0 N
+REUNIFIED  R IY0 - UW1 - N AH0 - F AY2 D
+REUNIFY  R IY0 - UW1 - N AH0 - F AY2
+REUNION  R IY0 - UW1 - N Y AH0 N
+REUNIONS  R IY0 - UW1 - N Y AH0 N Z
+REUNITE  R IY2 - UW0 - N AY1 T
+REUNITED  R IY2 - UW0 - N AY1 - T IH0 D
+REUNITES  R IY2 - UW0 - N AY1 T S
+REUNITING  R IY2 - UW0 - N AY1 - T IH0 NG
+REUSABLE  R IY0 - UW1 - Z AH0 - B AH0 L
+REUSCH  R OY1 SH
+REUSE  R IY0 - Y UW1 S
+REUSE(2)  R IY0 - Y UW1 Z
+REUSED  R IY0 - UW1 Z D
+REUSING  R IY0 - Y UW1 - Z IH0 NG
+REUSS  R UW1 S
+REUSSER  R OY1 - S ER0
+REUST  R UW1 S T
+REUTER  R OY1 - T ER0
+REUTER'S  R OY1 - T ER0 Z
+REUTERS  R OY1 - T ER0 Z
+REUTERS'  R OY1 - T ER0 Z
+REUTERS'S  R OY1 - T ER0 - Z IH0 Z
+REUTERS'S(2)  R OY1 - T ER0 Z
+REUTGERS  R OY1 T - G ER0 Z
+REUTHER  R OY1 - DH ER0
+REUTTER  R OY1 - T ER0
+REUTZEL  R OY1 T - Z AH0 L
+REV  R EH1 V
+REVA  R EY1 - V AH0
+REVAK  R EH1 - V AH0 K
+REVALUATION  R IY0 - V AE1 L - Y UW0 - EY1 - SH AH0 N
+REVALUATIONS  R IY0 - IH0 - V AE2 L - Y UW0 - EY1 - SH AH0 N Z
+REVALUE  R IY0 - V AE1 L - Y UW2
+REVALUED  R IY0 - V AE1 L - Y UW0 D
+REVALUING  R IY0 - V AE1 L - Y UW0 - IH0 NG
+REVAMP  R IY0 - V AE1 M P
+REVAMPED  R IY0 - V AE1 M P T
+REVAMPING  R IY0 - V AE1 M - P IH0 NG
+REVAMPS  R IY0 - V AE1 M P S
+REVARD  R IH0 - V AA1 R D
+REVCO  R EH1 V - K OW0
+REVCO'S  R EH1 V - K OW0 Z
+REVEAL  R IH0 - V IY1 L
+REVEAL(2)  R IY0 - V IY1 L
+REVEALED  R IH0 - V IY1 L D
+REVEALED(2)  R IY0 - V IY1 L D
+REVEALING  R IH0 - V IY1 - L IH0 NG
+REVEALING(2)  R IY0 - V IY1 - L IH0 NG
+REVEALS  R IH0 - V IY1 L Z
+REVEALS(2)  R IY0 - V IY1 L Z
+REVEL  R EH1 - V AH0 L
+REVELATION  R EH2 - V AH0 - L EY1 - SH AH0 N
+REVELATIONS  R EH2 - V AH0 - L EY1 - SH AH0 N Z
+REVELATORY  R IH0 - V EH1 - L AH0 - T AO2 - R IY0
+REVELED  R EH1 - V AH0 L D
+REVELER  R EH1 - V AH0 - L ER0
+REVELERS  R EH1 - V AH0 - L ER0 Z
+REVELES  R EY0 - V EY1 - L EH0 S
+REVELING  R EH1 - V AH0 L - IH0 NG
+REVELL  R EY0 - V EY1 L
+REVELLE  R IH0 - V EH1 L
+REVELLO  R EH0 - V EH1 - L OW0
+REVELRY  R EH1 - V AH0 L - R IY0
+REVELS  R EH1 - V AH0 L Z
+REVENGE  R IY0 - V EH1 N JH
+REVENUE  R EH1 - V AH0 - N UW2
+REVENUE(2)  R EH1 - V AH0 - N Y UW2
+REVENUES  R EH1 - V AH0 - N UW2 Z
+REVENUES(2)  R EH1 - V AH0 - N Y UW2 Z
+REVERB  R IY0 - V ER1 B
+REVERBED  R IY0 - V ER1 B D
+REVERBERATE  R IH0 - V ER1 - B ER0 - AH0 T
+REVERBERATE(2)  R IH0 - V ER1 - B ER0 - EY0 T
+REVERBERATED  R IH0 - V ER1 - B ER0 - EY2 - T IH0 D
+REVERBERATED(2)  R IY0 - V ER1 - B ER0 - EY2 - T AH0 D
+REVERBERATED(3)  R IY0 - V ER1 - B ER0 - EY2 - T IH0 D
+REVERBERATES  R IH0 - V ER1 - B ER0 - EY2 T S
+REVERBERATING  R IH0 - V ER1 - B ER0 - EY2 - T IH0 NG
+REVERBERATING(2)  R IY0 - V ER1 - B ER0 - EY2 - T IH0 NG
+REVERBERATION  R IY0 - V ER2 - B ER0 - EY1 - SH AH0 N
+REVERBERATIONS  R IH0 - V ER2 - B ER0 - EY1 - SH AH0 N Z
+REVERCOMB  R EH1 - V ER0 - K AH0 M
+REVERE  R IH0 - V IH1 R
+REVERED  R IH0 - V IH1 R D
+REVERENCE  R EH1 - V ER0 - AH0 N S
+REVEREND  R EH1 - V ER0 - AH0 N D
+REVEREND(2)  R EH1 - V R AH0 N D
+REVERENT  R EH1 - V ER0 - AH0 N T
+REVERENTIAL  R EH2 - V ER0 - EH1 N - CH AH0 L
+REVERENTIAL(2)  R EH2 - V ER0 - EH1 N - SH AH0 L
+REVERENTLY  R EH1 - V ER0 - AH0 N T - L IY0
+REVERIE  R EH1 - V ER0 - IY0
+REVERIES  R EH1 - V ER0 - IY0 Z
+REVERON  R EH1 - V ER0 - AA2 N
+REVERON'S  R EH1 - V ER0 - AA2 N Z
+REVERSAL  R IH0 - V ER1 - S AH0 L
+REVERSAL(2)  R IY0 - V ER1 - S AH0 L
+REVERSALS  R IH0 - V ER1 - S AH0 L Z
+REVERSALS(2)  R IY0 - V ER1 - S AH0 L Z
+REVERSE  R IH0 - V ER1 S
+REVERSE(2)  R IY0 - V ER1 S
+REVERSED  R IH0 - V ER1 S T
+REVERSED(2)  R IY0 - V ER1 S T
+REVERSER  R IH0 - V ER1 - S ER0
+REVERSERS  R IH0 - V ER1 - S ER0 Z
+REVERSES  R IH0 - V ER1 - S IH0 Z
+REVERSES(2)  R IY0 - V ER1 - S AH0 Z
+REVERSES(3)  R IY0 - V ER1 - S IH0 Z
+REVERSIBLE  R IH0 - V ER1 - S AH0 - B AH0 L
+REVERSIBLE(2)  R IY0 - V ER1 - S AH0 - B AH0 L
+REVERSING  R IH0 - V ER1 - S IH0 NG
+REVERSING(2)  R IY0 - V ER1 - S IH0 NG
+REVERSION  R IH0 - V ER1 - ZH AH0 N
+REVERT  R IH0 - V ER1 T
+REVERT(2)  R IY0 - V ER1 T
+REVERTED  R IH0 - V ER1 - T IH0 D
+REVERTED(2)  R IY0 - V ER1 - T IH0 D
+REVERTING  R IH0 - V ER1 - T IH0 NG
+REVERTS  R IH0 - V ER1 T S
+REVES  R IY1 V Z
+REVETTE  R IH0 - V EH1 T
+REVIER  R IY1 - V IY0 - ER0
+REVIEW  R IY2 - V Y UW1
+REVIEW'S  R IY0 - V Y UW1 Z
+REVIEWED  R IY0 - V Y UW1 D
+REVIEWER  R IY0 - V Y UW1 - ER0
+REVIEWER'S  R IY0 - V Y UW1 - ER0 Z
+REVIEWERS  R IY0 - V Y UW1 - ER0 Z
+REVIEWING  R IY0 - V Y UW1 - IH0 NG
+REVIEWS  R IY0 - V Y UW1 Z
+REVIEWS(2)  R AH0 - V Y UW1 Z
+REVIGLIO  R AH0 - V IH1 G - L IY0 - OW0
+REVILE  R IY0 - V AY1 L
+REVILED  R IY0 - V AY1 L D
+REVILLA  R EH0 - V IH1 - L AH0
+REVILLE  R EH1 - V IH2 L
+REVIS  R EH1 - V IH0 S
+REVISE  R IH0 - V AY1 Z
+REVISE(2)  R IY0 - V AY1 Z
+REVISED  R IH0 - V AY1 Z D
+REVISED(2)  R IY0 - V AY1 Z D
+REVISES  R IH0 - V AY1 - Z IH0 Z
+REVISES(2)  R IY0 - V AY1 - Z IH0 Z
+REVISING  R IH0 - V AY1 - Z IH0 NG
+REVISING(2)  R IY0 - V AY1 - Z IH0 NG
+REVISION  R IY0 - V IH1 - ZH AH0 N
+REVISIONISM  R IY0 - V IH1 - ZH AH0 N - IH2 - Z AH0 M
+REVISIONIST  R IY0 - V IH1 - ZH AH0 N - IH0 S T
+REVISIONISTS  R IY0 - V IH1 - ZH AH0 N - IH0 S T S
+REVISIONISTS(2)  R IY0 - V IH1 - ZH AH0 N - IH0 S S
+REVISIONISTS(3)  R IY0 - V IH1 - ZH AH0 N - IH0 S
+REVISIONS  R IY0 - V IH1 - ZH AH0 N Z
+REVISIT  R IY0 - V IH1 - Z IH0 T
+REVISITED  R IY0 - V IH1 - Z AH0 - T IH0 D
+REVISITING  R IY0 - V IH1 - Z IH0 - T IH0 NG
+REVISITS  R IY0 - V IH1 - Z IH0 T S
+REVITALIZATION  R IY2 - V AY2 - T AH0 - L AH0 - Z EY1 - SH AH0 N
+REVITALIZE  R IY0 - V AY1 - T AH0 - L AY2 Z
+REVITALIZED  R IY0 - V AY1 - T AH0 - L AY2 Z D
+REVITALIZING  R IY0 - V AY1 - T AH0 - L AY2 - Z IH0 NG
+REVIVAL  R IH0 - V AY1 - V AH0 L
+REVIVAL(2)  R IY0 - V AY1 - V AH0 L
+REVIVALIST  R IY0 - V AY1 - V AH0 - L IH0 S T
+REVIVALS  R IY0 - V AY1 - V AH0 L Z
+REVIVE  R IH0 - V AY1 V
+REVIVE(2)  R IY0 - V AY1 V
+REVIVED  R IH0 - V AY1 V D
+REVIVED(2)  R IY0 - V AY1 V D
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+RUDDICK  R AH1 - D IH0 K
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+RUDDOCK  R AH1 - D AH0 K
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+RUDE  R UW1 D
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+RUDENSTEIN(2)  R UW1 - D IH0 N - S T AY0 N
+RUDENSTINE  R UW1 - D AH0 N Z - T AY2 N
+RUDER  R UW1 - D ER0
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+RUDESILL  R AH1 - D IH0 - S AH0 L
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+RUDGE  R AH1 JH
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+RUDIMENTARY  R UW2 - D AH0 - M EH1 N - T ER0 - IY0
+RUDIMENTS  R UW1 - D IH0 - M AH0 N T S
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+RUDISILL  R AH1 - D IH0 - S IH0 L
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+RUDZINSKI  R AH0 - JH IH1 N - S K IY0
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+RUEB  R UW1 B
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+RUEFUL  R UW1 - F AH0 L
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+RUFENACHT  R UW1 - F AH0 - N AA0 K T
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+RUINING  R UW1 - IH0 - N IH0 NG
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+RUMBLINGS  R AH1 M - B AH0 - L IH0 NG Z
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+RUNAWAYS  R AH1 N - AH0 - W EY2 Z
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+RUNCK  R AH1 NG K
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+RUNCO  R AH1 NG - K OW0
+RUND  R AH1 N D
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+RUNG  R AH1 NG
+RUNGE  R AH1 N JH
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+RUNKLE  R AH1 NG - K AH0 L
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+RUNKO  R AH1 N - K OW0
+RUNNELLS  R AH1 - N AH0 L Z
+RUNNELS  R AH1 - N AH0 L Z
+RUNNER  R AH1 - N ER0
+RUNNER'S  R AH1 - N ER0 Z
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+RUNNIN'  R AH1 - N IH0 N
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+RUNNINGS  R AH1 - N IH0 NG Z
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+RUPTURE  R AH1 P - CH ER0
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+RUPTURES  R AH1 P - CH ER0 Z
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+SELF-CONGRATULATION  S EH1 L F - K AH0 N - G R AE2 - CH AH0 - L EY1 - SH AH0 N
+SELF-CONSISTENT  S EH2 L F - K AH0 N - S IH1 - S T AH0 N T
+SELF-CONTAINED  S EH1 L F - K AH0 N - T EY1 N D
+SELF-CONTROL  S EH1 L F - K AH0 N - T R OW1 L
+SELF-DECEIVING  S EH2 L F - D IY0 - S IY1 - V IH0 NG
+SELF-DECEPTION  S EH1 L F - D AH0 - S EH1 P - SH AH0 N
+SELF-DELIVERANCE  S EH1 L F - D IH0 - L IH1 - V ER0 - AH0 N S
+SELF-DEPRECATING  S EH1 L F - D EH1 - P R AH0 - K EY2 - T IH0 NG
+SELF-DETERMINATION  S EH1 L F - D IH0 - T ER2 - M AH0 - N EY1 - SH AH0 N
+SELF-DORMANT  S EH1 L F - D AO1 R - M AH0 N T
+SELF-ENERGIZING  S EH1 L - F EH1 - N ER0 - JH AY2 - Z IH0 NG
+SELF-ENRICHMENT  S EH2 L - F AH0 N - R IH1 CH - M AH0 N T
+SELF-FERTILIZING  S EH1 L F - F ER1 - T AH0 - L AY2 - Z IH0 NG
+SELF-FRUITFUL  S EH1 L F - F R UW1 T - F AH0 L
+SELF-GOVERN  S EH1 L F - G AH1 - V ER0 N
+SELF-GOVERNING  S EH1 L F - G AH1 - V ER0 - N IH0 NG
+SELF-GOVERNMENT  S EH1 L F - G AH1 - V ER0 N - M AH0 N T
+SELF-HELP  S EH1 L F - HH EH1 L P
+SELF-IMPROVEMENT  S EH1 L - F IH0 M - P R UW1 V - M AH0 N T
+SELF-PERPETUATE  S EH2 L F - P ER0 - P EH1 - CH UW0 - EY2 T
+SELF-PERPETUATING  S EH2 L F - P ER0 - P EH1 - CH UW0 - EY2 - T IH0 NG
+SELF-PERPETUATION  S EH1 L F - P ER0 - P EH2 - CH UW0 - EY1 - SH AH0 N
+SELF-POLLINATE  S EH1 L - F P AA1 - L AH0 - N EY2 T
+SELF-PORTRAIT  S EH1 L F - P AO1 R - T R AH0 T
+SELF-PROFESSED  S EH1 L F - P R AH0 - F EH1 S T
+SELF-SUBSISTENCE  S EH1 L F - S AH0 B - S IH1 - S T AH0 N S
+SELF-SUFFICIENCY  S EH1 L F - S AH0 - F IH1 - SH AH0 N - S IY0
+SELF-SUFFICIENT  S EH1 L F - S AH0 - F IH1 - SH AH0 N T
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+SELF-TORMENT  S EH1 L F - T AO1 R - M EH2 N T
+SELF-TORMENTS  S EH1 L F - T AO1 R - M EH2 N T S
+SELFISH  S EH1 L - F IH0 SH
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+SELFLESSNESS  S EH1 L F - L AH0 S - N IH0 S
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+SELIES  S EH1 - L IY0 Z
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+SELINA  S AH0 - L IY1 - N AH0
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+SELK  S EH1 L K
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+SELLE  S EH1 L
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+SELLER'S  S EH1 - L ER0 Z
+SELLERS  S EH1 - L ER0 Z
+SELLERS'  S EH1 - L ER0 Z
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+SELLICK  S EH1 - L IH0 K
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+SELLINGER  S EH1 - L IH0 - NG ER0
+SELLINGS  S EH1 - L IH0 NG Z
+SELLMAN  S EH1 L - M AH0 N
+SELLMEYER  S EH1 L - M AY0 - ER0
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+SELLOFF  S EH1 L - AO2 F
+SELLOFFS  S EH1 - L AO2 F S
+SELLON  S EH1 - L AH0 N
+SELLOUT  S EH1 L - AW2 T
+SELLOUTS  S EH1 L - AW2 T S
+SELLS  S EH1 L Z
+SELMA  S EH1 L - M AH0
+SELMAN  S EH1 L - M AH0 N
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+SELMON  S EH1 L - M AH0 N
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+SELPH  S EH1 L F
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+SELVES  S EH1 L V Z
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+SELVIDGE  S EH1 L - V IH0 JH
+SELVIG  S EH1 L - V IH0 G
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+SELZ  S EH1 L Z
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+SELZER'S  S EH1 L - Z ER0 Z
+SEMA  S IY1 - M AH0
+SEMAN  S IY1 - M AH0 N
+SEMANS  S IY1 - M AH0 N Z
+SEMANTIC  S IH0 - M AE1 N - T IH0 K
+SEMANTICS  S IH0 - M AE1 N - T IH0 K S
+SEMATECH  S EH1 - M AH0 - T EH2 K
+SEMBER  S EH1 M - B ER0
+SEMBLANCE  S EH1 M - B L AH0 N S
+SEMEGRAN  S EH1 - M AH0 - G R AH0 N
+SEMEL  S EH1 - M AH0 L
+SEMELE  S EH1 - M AH0 - L IY2
+SEMEN  S IY1 - M AH0 N
+SEMENZA  S EH0 - M EH1 N - Z AH0
+SEMERAD  S EH1 - M ER0 - AE0 D
+SEMESTER  S AH0 - M EH1 - S T ER0
+SEMESTERS  S AH0 - M EH1 - S T ER0 Z
+SEMI  S EH1 - M IY0
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+SEMI-COLON  S EH1 - M IY0 - K OW1 - L AH0 N
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+SEMI-HEIGHT  S EH1 - M IY0 - HH AY1 T
+SEMI-HEIGHT(2)  S EH1 - M IH0 - HH AY1 T
+SEMI-HEIGHT(3)  S EH1 - M AY0 - HH AY1 T
+SEMI-HEIGHTS  S EH1 - M IY0 - HH AY1 T S
+SEMI-HEIGHTS(2)  S EH1 - M AY0 - HH AY1 T S
+SEMI-HEIGHTS(3)  S EH1 - M IH0 - HH AY1 T S
+SEMIANNUAL  S EH2 - M IY0 - AE1 - N Y AH0 - W AH0 L
+SEMIANNUAL(2)  S EH2 - M AY0 - AE1 - N Y AH0 - W AH0 L
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+SEMIANNUALLY(2)  S EH2 - M AY0 - AE1 - N UW0 - AH0 - L IY0
+SEMIANNUALLY(3)  S EH2 - M IY0 - AE1 - N UW0 - L IY0
+SEMIANNUALLY(4)  S EH2 - M AY0 - AE1 - N UW0 - L IY0
+SEMIANNUALLY(5)  S EH2 - M IH0 - AE1 - N UW0 - L IY0
+SEMIANNUALLY(6)  S EH2 - M IH0 - AE1 - N UW0 - AH0 - L IY0
+SEMIAUTOMATIC  S EH2 - M IY0 - AO2 - T AH0 - M AE1 - T IH0 K
+SEMIAUTOMATIC(2)  S EH2 - M AY0 - AO2 - T AH0 - M AE1 - T IH0 K
+SEMIAUTOMATIC(3)  S EH2 - M IH0 - AO2 - T AH0 - M AE1 - T IH0 K
+SEMICIRCULAR  S EH2 - M IY0 - S ER1 - K Y AH0 - L ER0
+SEMICIRCULAR(2)  S EH2 - M AY0 - S ER1 - K Y AH0 - L ER0
+SEMICIRCULAR(3)  S EH2 - M AH0 - S ER1 - K Y AH0 - L ER0
+SEMICLAD  S EH1 - M IY0 - K L AE2 D
+SEMICLAD(2)  S EH1 - M AY0 - K L AE2 D
+SEMICLAD(3)  S EH1 - M AH0 - K L AE2 D
+SEMICLASSICAL  S EH2 - M IY0 - K L AE1 - S IH0 - K AH0 L
+SEMICLASSICAL(2)  S EH2 - M IH0 - K L AE1 - S IH0 - K AH0 L
+SEMICLASSICAL(3)  S EH2 - M AY0 - K L AE1 - S IH0 - K AH0 L
+SEMICON  S EH1 - M IH0 - K AA2 N
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+SEMICONDUCTOR'S  S EH2 - M IY0 - K AH0 N - D AH1 K - T ER0 Z
+SEMICONDUCTOR'S(2)  S EH2 - M IH0 - K AH0 N - D AH1 K - T ER0 Z
+SEMICONDUCTOR'S(3)  S EH2 - M AY0 - K AH0 N - D AH1 K - T ER0 Z
+SEMICONDUCTOR(2)  S EH2 - M IH0 - K AH0 N - D AH1 K - T ER0
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+SEMICONDUCTORS(2)  S EH2 - M IH0 - K AH0 N - D AH1 K - T ER0 Z
+SEMICONDUCTORS(3)  S EH2 - M AY0 - K AH0 N - D AH1 K - T ER0 Z
+SEMICYLINDRICAL  S EH2 - M IY0 - S AH0 - L IH1 N - D R IH0 - K AH0 L
+SEMICYLINDRICAL(2)  S EH2 - M IH0 - S AH0 - L IH1 N - D R IH0 - K AH0 L
+SEMICYLINDRICAL(3)  S EH2 - M AY0 - S AH0 - L IH1 N - D R IH0 - K AH0 L
+SEMIDRY  S EH2 - M IY0 - D R AY1
+SEMIDRY(2)  S EH2 - M IH0 - D R AY1
+SEMIDRY(3)  S EH2 - M AY0 - D R AY1
+SEMIDRYING  S EH2 - M IY0 - D R AY1 - IH0 NG
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+SEMIDRYING(3)  S EH2 - M AY0 - D R AY1 - IH0 NG
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+SEMIFINAL(3)  S EH2 - M AY0 - F AY1 - N AH0 L
+SEMIFINALIST  S EH2 - M IY0 - F AY1 - N AH0 L - IH0 S T
+SEMIFINALIST(2)  S EH2 - M IH0 - F AY1 - N AH0 - L IH0 S T
+SEMIFINALIST(3)  S EH2 - M AY0 - F AY1 - N AH0 - L IH0 S T
+SEMIFINALISTS  S EH2 - M IY0 - F AY1 - N AH0 L - IH0 S T S
+SEMIFINALISTS(2)  S EH2 - M IY0 - F AY1 - N AH0 L - IH0 S S
+SEMIFINALISTS(3)  S EH2 - M IY0 - F AY1 - N AH0 L - IH0 S
+SEMIFINALISTS(4)  S EH2 - M AY0 - F AY1 - N AH0 - L IH0 S T S
+SEMIFINALISTS(5)  S EH2 - M AY0 - F AY1 - N AH0 L - IH0 S S
+SEMIFINALISTS(6)  S EH2 - M AY0 - F AY1 - N AH0 L - IH0 S
+SEMIFINALISTS(7)  S EH2 - M IH0 - F AY1 - N AH0 - L IH0 S T S
+SEMIFINALISTS(8)  S EH2 - M IH0 - F AY1 - N AH0 L - IH0 S S
+SEMIFINALISTS(9)  S EH2 - M IH0 - F AY1 - N AH0 L - IH0 S
+SEMIFINALS  S EH2 - M IY0 - F AY1 - N AH0 L Z
+SEMIFINALS(2)  S EH2 - M IH0 - F AY1 - N AH0 L Z
+SEMIFINALS(3)  S EH2 - M AY0 - F AY1 - N AH0 L Z
+SEMIFINISH  S EH2 - M IY0 - F IH1 - N IH0 SH
+SEMIFINISH(2)  S EH2 - M AY0 - F IH1 - N IH0 SH
+SEMIFINISH(3)  S EH2 - M IH0 - F IH1 - N IH0 SH
+SEMIFINISHED  S EH2 - M IY0 - F IH1 - N IH0 SH T
+SEMIFINISHED(2)  S EH2 - M AY0 - F IH1 - N IH0 SH T
+SEMIFINISHED(3)  S EH2 - M IH0 - F IH1 - N IH0 SH T
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+SEMILEGENDARY  S EH2 - M IY0 - L EH1 - JH AH0 N - D EH2 - R IY0
+SEMILEGENDARY(2)  S EH2 - M IH0 - L EH1 - JH AH0 N - D EH2 - R IY0
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+SENATORE  S EH0 - N AA0 - T AO1 - R IY0
+SENATORIAL  S EH2 - N AH0 - T AO1 - R IY0 - AH0 L
+SENATORS  S EH1 - N AH0 - T ER0 Z
+SENATORS'  S EH1 - N AH0 - T ER0 Z
+SEND  S EH1 N D
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+SHEELEN  SH IY1 - L AH0 N
+SHEELER  SH IY1 - L ER0
+SHEELEY  SH IY1 - L IY0
+SHEELY  SH IY1 - L IY0
+SHEEN  SH IY1 N
+SHEENA  SH IY1 - N AH0
+SHEEP  SH IY1 P
+SHEEP'S  SH IY1 P S
+SHEEPISH  SH IY1 - P IH0 SH
+SHEEPISHLY  SH IY1 - P IH0 SH - L IY0
+SHEEPS  SH IY1 P S
+SHEEPSKIN  SH IY1 P - S K IH2 N
+SHEER  SH IH1 R
+SHEERAN  SH IH1 - R AH0 N
+SHEERER  SH IY1 - R ER0
+SHEERIN  SH IH1 - R IH0 N
+SHEESH  SH IY1 SH
+SHEESLEY  SH IY1 Z - L IY0
+SHEET  SH IY1 T
+SHEETING  SH IY1 - T IH0 NG
+SHEETS  SH IY1 T S
+SHEETZ  SH IY1 T S
+SHEFF  SH EH1 F
+SHEFFER  SH EH1 - F ER0
+SHEFFEY  SH EH1 - F IY0
+SHEFFIELD  SH EH1 - F IY0 L D
+SHEFFLER  SH EH1 F - L ER0
+SHEFTEL  SH EH2 F - T EH1 L
+SHEFTEL'S  SH EH2 F - T EH1 L Z
+SHEGOG  SH EH1 - G AA0 G
+SHEHAN  SH EH1 - HH AH0 N
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+SHEHORN  SH EH1 - HH ER0 N
+SHEIK  SH IY1 K
+SHEIK'S  SH IY1 K S
+SHEIKDOM  SH IY1 K - D AH0 M
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+SHEIKH  SH IY1 K
+SHEIKS  SH IY1 K S
+SHEIL  SH AY1 L
+SHEILA  SH IY1 - L AH0
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+SHEILAH  SH IY1 - L AH0
+SHEILDS  SH AY1 L D Z
+SHEILS  SH AY1 L Z
+SHEIN  SH AY1 N
+SHEINBERG  SH AY1 N - B ER0 G
+SHEK  SH EH1 K
+SHEK'S  SH EH1 K S
+SHEKEL  SH EH1 - K AH0 L
+SHEKELS  SH EH1 - K AH0 L Z
+SHELBURNE  SH EH1 L - B ER0 N
+SHELBY  SH EH1 L - B IY0
+SHELBY'S  SH EH1 L - B IY0 Z
+SHELBYVILLE  SH EH1 L - B IY0 - V IH2 L
+SHELDAHL  SH EH1 L - D AA2 L
+SHELDEN  SH EH1 L - D AH0 N
+SHELDON  SH EH1 L - D AH0 N
+SHELEV  SH EH1 - L IH0 V
+SHELEY  SH IY1 - L IY0
+SHELF  SH EH1 L F
+SHELHAMER  SH EH1 L - HH AH0 - M ER0
+SHELINE  SH EH1 - L AY0 N
+SHELL  SH EH1 L
+SHELL'S  SH EH1 L Z
+SHELLABARGER  SH EH1 - L AH0 - B AA2 R - G ER0
+SHELLED  SH EH1 L D
+SHELLENBARGER  SH EH1 - L IH0 N - B AA0 R - G ER0
+SHELLENBERGER  SH EH1 - L AH0 N - B ER0 - G ER0
+SHELLER  SH EH1 - L ER0
+SHELLEY  SH EH1 - L IY0
+SHELLEY'S  SH EH1 - L IY0 Z
+SHELLFISH  SH EH1 L - F IH2 SH
+SHELLHAMMER  SH EH1 L - HH AE2 - M ER0
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+SHELLING  SH EH1 - L IH0 NG
+SHELLINGS  SH EH1 - L IH0 NG Z
+SHELLITO  SH EY0 - L IY1 - T OW0
+SHELLMAN  SH EH1 L - M AH0 N
+SHELLS  SH EH1 L Z
+SHELLSHOCK  SH EH1 L - SH AA2 K
+SHELLSHOCKED  SH EH1 L - SH AA2 K T
+SHELLY  SH EH1 - L IY0
+SHELMAN  SH EH1 L - M AH0 N
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+SHELOR  SH EH1 - L ER0
+SHELP  SH EH1 L P
+SHELSTAD  SH EH1 L - S T AH0 D
+SHELTER  SH EH1 L - T ER0
+SHELTERED  SH EH1 L - T ER0 D
+SHELTERING  SH EH1 L - T ER0 - IH0 NG
+SHELTERS  SH EH1 L - T ER0 Z
+SHELTON  SH EH1 L - T AH0 N
+SHELTON'S  SH EH1 L - T AH0 N Z
+SHELVE  SH EH1 L V
+SHELVED  SH EH1 L V D
+SHELVES  SH EH1 L V Z
+SHELVING  SH EH1 L - V IH0 NG
+SHEMANSKI  SH IH0 - M AE1 N - S K IY0
+SHEMONA  SH IH0 - M OW1 - N AH0
+SHEMWELL  SH EH1 M - W EH2 L
+SHEN  SH EH1 N
+SHENA  SH IY1 - N AH0
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+SHENANIGAN  SH AH0 - N AE1 - N IH0 - G AH0 N
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+SHENBERGER  SH EH1 N - B ER0 - G ER0
+SHENEFIELD  SH EH1 - N IH0 - F IY2 L D
+SHENEMAN  SH IY1 N - M AH0 N
+SHENG  SH EH1 NG
+SHENG-FEN  SH EH1 NG - F EH1 N
+SHENICE  SH AH0 - N IY1 S
+SHENK  SH EH1 NG K
+SHENKER  SH EH1 NG - K ER0
+SHENKMAN  SH EH1 NG K - M AH0 N
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+SHENZHEN  SH EH1 N - ZH EH2 N
+SHEP  SH EH1 P
+SHEPARD  SH EH1 - P ER0 D
+SHEPARD'S  SH EH1 - P ER0 D Z
+SHEPARDSON  SH EH1 - P AA0 R D - S AH0 N
+SHEPERD  SH EH1 - P ER0 D
+SHEPHARD  SH EH1 - F ER0 D
+SHEPHEARD  SH EH1 - F ER0 D
+SHEPHERD  SH EH1 - P ER0 D
+SHEPHERD'S  SH EH1 - P ER0 D Z
+SHEPHERDED  SH EH1 - P ER0 - D IH0 D
+SHEPHERDING  SH EH1 - P ER0 - D IH0 NG
+SHEPHERDS  SH EH1 - P ER0 D Z
+SHEPLER  SH EH1 P - L ER0
+SHEPLEY  SH EH1 P - L IY0
+SHEPP  SH EH1 P
+SHEPPARD  SH EH1 - P ER0 D
+SHEPPARDS  SH EH1 - P ER0 D Z
+SHEPPER  SH EH1 - P ER0
+SHEPPERD  SH EH1 - P ER0 D
+SHEPPERSON  SH EH1 - P ER0 - S AH0 N
+SHEPPY  SH EH1 - P IY0
+SHER  SH ER1
+SHERAK  SH EH1 - R AE0 K
+SHERARD  SH EH1 - R ER0 D
+SHERATON  SH EH1 - R AH0 - T AH0 N
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+SHERBERT  SH ER1 - B ER0 T
+SHERBET  SH ER1 - B AH0 T
+SHERBONDY  SH ER0 - B AA1 N - D IY0
+SHERBORNE  SH ER1 - B ER0 N
+SHERBOURN  SH ER0 - B UH1 R N
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+SHERBURN  SH ER1 - B ER0 N
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+SHERE  SH IH1 R
+SHEREE  SH ER0 - IY1
+SHERER  SH IH1 - R ER0
+SHERFEY  SH ER1 - F IY0
+SHERFIELD  SH ER1 - F IY0 L D
+SHERI  SH EH1 - R IY0
+SHERICK  SH EH1 - R IH0 K
+SHERIDAN  SH EH1 - R IH0 - D AH0 N
+SHERIFF  SH EH1 - R AH0 F
+SHERIFF'S  SH EH1 - R AH0 F S
+SHERIFF'S(2)  SH EH1 - R IH0 F S
+SHERIFF(2)  SH EH1 - R IH0 F
+SHERIFFS  SH EH1 - R AH0 F S
+SHERIN  SH EH1 - R IH0 N
+SHERK  SH ER1 K
+SHERLEY  SH ER1 - L IY0
+SHERLIN  SH ER1 - L IH0 N
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+SHERLOCK'S  SH ER1 - L AA2 K S
+SHERLUND  SH ER1 - L AH0 N D
+SHERMAN  SH ER1 - M AH0 N
+SHERMAN'S  SH ER1 - M AH0 N Z
+SHERMER  SH ER1 - M ER0
+SHERNOFF  SH ER1 - N AO2 F
+SHEROD  SH EH1 - R AH0 D
+SHERR  SH EH1 R
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+SHERRARD  SH EH1 - R ER0 D
+SHERRELL  SH EH1 - R AH0 L
+SHERRER  SH EH1 - R ER0
+SHERRGOLD  SH EH1 R - G OW2 L D
+SHERRI  SH EH1 - R IY0
+SHERRI'S  SH EH1 - R IY0 Z
+SHERRICK  SH EH1 - R IH0 K
+SHERRIE  SH EH1 - R IY0
+SHERRIFF  SH EH1 - R IH0 F
+SHERRILL  SH EH1 - R IH0 L
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+SHERRITT  SH EH1 - R IH0 T
+SHERROD  SH EH1 - R AH0 D
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+SHERRY  SH EH1 - R IY0
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+SHERTZER  SH ER1 T - Z ER0
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+SHERYL  SH EH1 - R AH0 L
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+SHETH  SH EH1 TH
+SHETLAND  SH EH1 T - L AH0 N D
+SHETLER  SH EH1 T - L ER0
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+SHETTER  SH EH1 - T ER0
+SHETTERLY  SH EH1 - T ER0 - L IY0
+SHEVARDNADZE  SH EH2 - V ER0 D - N AA1 D - Z IY0
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+SHEVLIN  SH EH1 V - L IH0 N
+SHEVTL  SH EH1 - V IH0 L
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+SHEW  SH UW1
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+SHEWCHUK  SH UW1 - CH AH0 K
+SHEWELL  SH EH1 - W EH0 L
+SHEWMAKE  SH UW1 - M EY2 K
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+SHH  SH
+SHI  SH IY1
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+SHIDELER  SH IH1 - D AH0 L - ER0
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+SHIED  SH AY1 D
+SHIEH  SH IY1
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+SHIELDED  SH IY1 L - D IH0 D
+SHIELDING  SH IY1 L - D IH0 NG
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+SHIELS  SH IY1 L Z
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+SHIFF  SH IH1 F
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+SHIFFMAN  SH IH1 F - M AH0 N
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+SHIFLETT  SH IH1 F - L IH0 T
+SHIFRIN  SH IH1 - F R IH0 N
+SHIFT  SH IH1 F T
+SHIFTED  SH IH1 F - T AH0 D
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+SHIFTER  SH IH1 F - T ER0
+SHIFTING  SH IH1 F - T IH0 NG
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+SHIFTY  SH IH1 F - T IY0
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+SHOCKED  SH AA1 K T
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+SHOCKLEY  SH AA1 K - L IY0
+SHOCKS  SH AA1 K S
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+SHOD  SH AA1 D
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+SHOE  SH UW1
+SHOE'S  SH UW1 Z
+SHOEBOX  SH OW1 - B AA0 K S
+SHOEHORN  SH UW1 - HH AO2 R N
+SHOEHORNED  SH UW1 - HH AO0 R N D
+SHOELACE  SH UW1 - L EY2 S
+SHOELACES  SH UW1 - L EY2 - S AH0 Z
+SHOEMAKE  SH UW1 - M EY2 K
+SHOEMAKER  SH UW1 - M EY2 - K ER0
+SHOEMAKERS  SH UW1 - M EY2 - K ER0 Z
+SHOEMATE  SH UW1 - M EY2 T
+SHOEN  SH UW1 N
+SHOEPRINT  SH UW1 - P R IH2 N T
+SHOEPRINTS  SH UW1 - P R IH2 N T S
+SHOES  SH UW1 Z
+SHOESHINE  SH UW1 - SH AY2 N
+SHOESTRING  SH UW1 - S T R IH2 NG
+SHOFF  SH AO1 F
+SHOFFNER  SH AO1 F - N ER0
+SHOFNER  SH AA1 F - N ER0
+SHOGREN  SH AA1 - G R EH0 N
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+SHOHAT  SH OW1 - HH AE0 T
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+SHOICHIRO  SH OW2 - IH0 - CH IH1 - R OW0
+SHOJI  SH OW1 - JH IY0
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+SHOLL  SH AA1 L
+SHOLLENBERGER  SH AA1 - L AH0 N - B ER0 - G ER0
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+SHOLTIS  SH OW1 L - T IH0 S
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+SHON  SH AA1 N
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+SHONK  SH AA1 NG K
+SHONKA  SH AA1 NG - K AH0
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+SHONTZ  SH AA1 N T S
+SHOO  SH UW1
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+SHOOFLY  SH UW1 - F L AY2
+SHOOK  SH UH1 K
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+SHOOTIN'  SH UW1 - T IH0 N
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+SHOOTINGS  SH UW1 - T IH0 NG Z
+SHOOTOUT  SH UW1 T - AW0 T
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+SHOOTS  SH UW1 T S
+SHOP  SH AA1 P
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+SHOPE  SH OW1 P
+SHOPKEEPER  SH AA1 P - K IY2 - P ER0
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+SHOPKO  SH AA1 P - K OW0
+SHOPKORN  SH AA1 P - K AO2 R N
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+SHOPPE  SH AA1 P
+SHOPPED  SH AA1 P T
+SHOPPER  SH AA1 - P ER0
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+SHOPPES  SH AA1 P S
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+SHOPPING'S  SH AA1 - P IH0 NG Z
+SHOPS  SH AA1 P S
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+SHORB  SH AO1 R B
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+SHORE'S  SH AO1 R Z
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+SHOREHAM  SH AO1 - R AH0 M
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+SHORELINE  SH AO1 R - L AY2 N
+SHORENSTEIN  SH AO1 - R AH0 N - S T IY0 N
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+SHOREY  SH AO1 - R IY0
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+SHORKEY  SH AO1 R - K IY0
+SHORN  SH AO1 R N
+SHORR  SH AO1 R
+SHORT  SH AO1 R T
+SHORT-WINDED  SH AO1 R T - W IH1 N - D IH0 D
+SHORTAGE  SH AO1 R - T AH0 JH
+SHORTAGE(2)  SH AO1 R - T IH0 JH
+SHORTAGES  SH AO1 R - T AH0 - JH AH0 Z
+SHORTAGES(2)  SH AO1 R - T IH0 - JH IH0 Z
+SHORTALL  SH AO1 R - T AH0 L
+SHORTCAKE  SH AO1 R T - K EY2 K
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+SHORTCHANGED  SH AO2 R T - CH EY1 N JH D
+SHORTCHANGING  SH AO2 R T - CH EY1 N - JH IH0 NG
+SHORTCOMING  SH AO1 R T - K AH2 - M IH0 NG
+SHORTCOMINGS  SH AO1 R T - K AH2 - M IH0 NG Z
+SHORTCUT  SH AO1 R T - K AH2 T
+SHORTCUTS  SH AO1 R T - K AH2 T S
+SHORTED  SH AO1 R - T IH0 D
+SHORTELL  SH AO0 R - T EH1 L
+SHORTEN  SH AO1 R - T AH0 N
+SHORTENED  SH AO1 R - T AH0 N D
+SHORTENING  SH AO1 R - T AH0 N - IH0 NG
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+SHORTENS  SH AO1 R - T AH0 N Z
+SHORTER  SH AO1 R - T ER0
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+SHORTEST  SH AO1 R - T IH0 S T
+SHORTFALL  SH AO1 R T - F AO2 L
+SHORTFALLS  SH AO1 R T - F AO2 L Z
+SHORTGRASS  SH AO1 R T - G R AE2 S
+SHORTHAIR  SH AO1 R T - HH EH2 R
+SHORTHAIRED  SH AO1 R T - HH EH2 R D
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+SHORTING  SH AO1 R - T IH0 NG
+SHORTLIVED  SH AO1 R T - L IH1 V D
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+SHORTLY  SH AO1 R T - L IY0
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+SHORTS'  SH AO1 R T S
+SHORTSIGHTED  SH AO1 R T - S AY1 - T IH0 D
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+SHORTSTOP  SH AO1 R T - S T AA2 P
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+SHORTZ'  SH AO1 R T S
+SHORTZ'S  SH AO1 R T - S IH0 Z
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+SHOT  SH AA1 T
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+SPINNER  S P IH1 - N ER0
+SPINNER'S  S P IH1 - N ER0 Z
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+SPINNEY  S P IH1 - N IY0
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+SPINOFFS  S P IH1 - N AO2 F S
+SPINOLA  S P IY0 - N OW1 - L AH0
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+SPIRES  S P AY1 R Z
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+SPIRITUALISTS(4)  S P IH1 - R IH0 - CH W AH0 - L IH0 S S
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+SPLASH  S P L AE1 SH
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+SPLENIC  S P L EH1 - N IH0 K
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+SPLICED  S P L AY1 S T
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+SPLIT  S P L IH1 T
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+SPLITT  S P L IH1 T
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+SPOKESMAN  S P OW1 K S - M AH0 N
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+SQUEAMISH  S K W IY1 - M IH0 SH
+SQUEAMISHNESS  S K W IY1 - M IH0 SH - N AH0 S
+SQUEEGEE  S K W IY1 - JH IY0
+SQUEEZE  S K W IY1 Z
+SQUEEZED  S K W IY1 Z D
+SQUEEZES  S K W IY1 - Z IH0 Z
+SQUEEZING  S K W IY1 - Z IH0 NG
+SQUELCH  S K W EH1 L CH
+SQUELCHED  S K W EH1 L CH T
+SQUELCHING  S K W EH1 L - CH IH0 NG
+SQUIBB  S K W IH1 B
+SQUIBB'S  S K W IH1 B Z
+SQUID  S K W IH1 D
+SQUIER  S K W AY1 - ER0
+SQUIERS  S K W AY1 - ER0 Z
+SQUIGGLE  S K W IH1 - G AH0 L
+SQUIGGLES  S K W IH1 - G AH0 L Z
+SQUILLACE  S K W IH1 - L AH0 S
+SQUILLANTE  S K W IY0 - L AA1 N - T EY0
+SQUINT  S K W IH1 N T
+SQUINTING  S K W IH1 N - T IH0 NG
+SQUIRE  S K W AY1 R
+SQUIRES  S K W AY1 - ER0 Z
+SQUIRM  S K W ER1 M
+SQUIRMING  S K W ER1 - M IH0 NG
+SQUIRMS  S K W ER1 M Z
+SQUIRREL  S K W ER1 - AH0 L
+SQUIRRELED  S K W ER1 - AH0 L D
+SQUIRRELS  S K W ER1 - AH0 L Z
+SQUIRT  S K W ER1 T
+SQUIRTED  S K W ER1 - T AH0 D
+SQUIRTED(2)  S K W ER1 - T IH0 D
+SQUIRTING  S K W ER1 - T IH0 NG
+SQUIRTS  S K W ER1 T S
+SQUISHY  S K W IH1 - SH IY0
+SQUITIERI  S K W IY0 - T IH1 - R IY0
+SQUYRES  S K W AY1 R Z
+SR  S IY1 - N Y ER0
+SR(2)  S IH1 - S T ER0
+SRADER  SH R EY1 - D ER0
+SRAM  SH R AE1 M
+SRAM(2)  EH1 - S R AE1 M
+SRAMEK  SH R AE1 - M IH0 K
+SRDAN  S ER1 - D AE2 N
+SREBRENICA  S R EY2 - B R EH0 - N IY1 T - S AH0
+SREBRENICA'S  S R EY2 - B R EH0 - N IY1 T - S AH0 Z
+SREBRENICA'S(2)  SH R EY2 - B R AH0 - N IY1 T - S AH0 Z
+SREBRENICA(2)  SH R EY2 - B R AH0 - N IY1 T - S AH0
+SREMAC  S R IY1 - M AE2 K
+SRI  SH R IY1
+SRI(2)  EH1 - S AA1 - R AY1
+SRI(3)  S R IY1
+SRI-LANKA  S R IY1 - L AE1 NG - K AH0
+SRI-LANKA(2)  SH R IY1 - L AE1 NG - K AH0
+SRINAGAR  S R IY1 - N AH0 - G AA2 R
+SRINAGAR(2)  SH R IY1 - N AH0 - G AA2 R
+SRINAGARB  S R IY1 - N AH0 - G AA2 R B
+SRINAGARB(2)  SH R IY1 - N AH0 - G AA2 R B
+SRINIVAS  S R IY1 - N IH0 - V AA2 S
+SRINIVASAN  S R IY0 - N IY0 - V AA0 - S AA1 N
+SRINIVASAN(2)  SH R IY0 - N IY0 - V AA0 - S AA1 N
+SRIRAM  S R IY1 - R AA2 M
+SRIRAM(2)  SH R IY1 - R AA2 M
+SRIVASTAVA  S R IY0 - V AA0 - S T AA1 - V AH0
+SRIVASTAVA(2)  SH R IY0 - V AA0 - S T AA1 - V AH0
+SROCK  SH R AA1 K
+SROGE  SH R OW1 G
+SROKA  SH R OW1 - K AH0
+SROUFE  SH R OW1 F
+SSANGYONG  S AE1 NG - Y AO2 NG
+ST  S T R IY1 T
+ST(2)  S EY1 N T
+ST-JAMES  S EY1 N T - JH EY1 M Z
+ST-JOHNS  S EY1 N T - JH AA1 N Z
+STA  S T AH1
+STA(2)  EH1 - S T IY1 - EY1
+STAAB  S T AA1 B
+STAACK  S T AA1 K
+STAAL  S T AA1 L
+STAAR  S T AA1 R
+STAAR'S  S T AA1 R Z
+STAAS  S T AA1 Z
+STAAT  S T AA1 T
+STAATS  S T AA1 T S
+STAB  S T AE1 B
+STABBED  S T AE1 B D
+STABBING  S T AE1 - B IH0 NG
+STABBINGS  S T AE1 - B IH0 NG Z
+STABENOW  S T AE1 - B IH0 - N OW0
+STABILE  S T EY1 - B IH0 L
+STABILITY  S T AH0 - B IH1 - L IH0 - T IY0
+STABILIZATION  S T EY2 - B AH0 - L AH0 - Z EY1 - SH AH0 N
+STABILIZE  S T EY1 - B AH0 - L AY2 Z
+STABILIZED  S T EY1 - B AH0 - L AY2 Z D
+STABILIZER  S T EY1 - B AH0 - L AY2 - Z ER0
+STABILIZERS  S T EY1 - B AH0 - L AY2 - Z ER0 Z
+STABILIZES  S T EY1 - B AH0 - L AY2 - Z AH0 Z
+STABILIZES(2)  S T EY1 - B AH0 - L AY2 - Z IH0 Z
+STABILIZING  S T EY1 - B AH0 - L AY2 - Z IH0 NG
+STABLE  S T EY1 - B AH0 L
+STABLER  S T EY1 - B AH0 L - ER0
+STABLER(2)  S T EY1 - B L ER0
+STABLES  S T EY1 - B AH0 L Z
+STABLEST  S T EY1 - B AH0 - L AH0 S T
+STABLEY  S T AE1 - B L IY0
+STABS  S T AE1 B Z
+STAC  S T AE1 K
+STAC'S  S T AE1 K S
+STACCATO  S T AH0 - K AA1 - T OW2
+STACEY  S T EY1 - S IY0
+STACH  S T AE1 CH
+STACHNIK  S T AE1 K - N IH0 K
+STACHOWIAK  S T AH0 - HH AW1 - IY0 - AE0 K
+STACHOWICZ  S T AA1 - HH AH0 - V IH0 CH
+STACHOWSKI  S T AH0 - HH AO1 F S - K IY0
+STACHURA  S T AA0 - K UH1 - R AH0
+STACHURSKI  S T AH0 - HH ER1 S - K IY0
+STACIA  S T AA1 - CH AH0
+STACIE  S T AE1 - K IY0
+STACK  S T AE1 K
+STACKED  S T AE1 K T
+STACKER  S T AE1 - K ER0
+STACKHOUSE  S T AE1 K - HH AW2 S
+STACKING  S T AE1 - K IH0 NG
+STACKPOLE  S T AE1 K - P OW2 L
+STACKS  S T AE1 K S
+STACY  S T EY1 - S IY0
+STADE  S T EY1 D
+STADEL  S T AE1 - D AH0 L
+STADELMAN  S T AE1 - D AH0 L - M AH0 N
+STADER  S T EY1 - D ER0
+STADIA  S T EY1 - D IY0 - AH0
+STADIUM  S T EY1 - D IY0 - AH0 M
+STADIUM'S  S T EY1 - D IY0 - AH0 M Z
+STADIUMS  S T EY1 - D IY0 - AH0 M Z
+STADLER  S T AE1 D - L ER0
+STADNIK  S T AE1 D - N IH0 K
+STADT  S T AE1 D T
+STADTLANDER  SH T AE1 T - L AE2 N - D ER0
+STADTMILLER  SH T AE1 T - M IH1 - L ER0
+STAEBELL  S T EH1 - B EH0 L
+STAEBLER  S T EY1 - L ER0
+STAEHLE  S T EY1 L
+STAFF  S T AE1 F
+STAFF'S  S T AE1 F S
+STAFFA  S T AA1 - F AH0
+STAFFED  S T AE1 F T
+STAFFER  S T AE1 - F ER0
+STAFFERS  S T AE1 - F ER0 Z
+STAFFIERI  S T AA0 - F IH1 - R IY0
+STAFFING  S T AE1 - F IH0 NG
+STAFFORD  S T AE1 - F ER0 D
+STAFFORD'S  S T AE1 - F ER0 D Z
+STAFFORDSHIRE  S T AE1 - F ER0 D - SH ER0
+STAFFORDSHIRE'S  S T AE1 - F ER0 D - SH ER0 Z
+STAFFORDSHIRE'S(2)  S T AE1 - F ER0 D - SH AY2 - ER0 Z
+STAFFORDSHIRE(2)  S T AE1 - F ER0 D - SH AY2 - ER0
+STAFFS  S T AE1 F S
+STAG  S T AE1 G
+STAGE  S T EY1 JH
+STAGECOACH  S T EY1 JH - K OW2 CH
+STAGECRAFT  S T EY1 JH - K R AE2 F T
+STAGED  S T EY1 JH D
+STAGEHAND  S T EY1 JH - HH AE2 N D
+STAGEHANDS  S T EY1 JH - HH AE2 N D Z
+STAGER  S T EY1 - JH ER0
+STAGES  S T EY1 - JH AH0 Z
+STAGES(2)  S T EY1 - JH IH0 Z
+STAGFLATE  S T AE2 G - F L EY1 T
+STAGFLATION  S T AE0 G - F L EY1 - SH AH0 N
+STAGG  S T AE1 G
+STAGGER  S T AE1 - G ER0
+STAGGERED  S T AE1 - G ER0 D
+STAGGERING  S T AE1 - G ER0 - IH0 NG
+STAGGERS  S T AE1 - G ER0 Z
+STAGGS  S T AE1 G Z
+STAGING  S T EY1 - JH IH0 NG
+STAGLIANO  S T AA0 G - L IY0 - AA1 - N OW0
+STAGNANT  S T AE1 G - N AH0 N T
+STAGNARO  S T AA0 G - N AA1 - R OW0
+STAGNATE  S T AE1 G - N EY2 T
+STAGNATED  S T AE1 G - N EY2 - T IH0 D
+STAGNATING  S T AE1 G - N EY2 - T IH0 NG
+STAGNATION  S T AE0 G - N EY1 - SH AH0 N
+STAGNER  S T AE1 G - N ER0
+STAHL  S T AA1 L
+STAHLBERG  S T AA1 L - B ER0 G
+STAHLE  S T EY1 - HH AH0 L
+STAHLECKER  S T AA1 - L IH0 - K ER0
+STAHLER  S T AA1 - L ER0
+STAHLEY  S T AE1 - L IY0
+STAHLHUT  S T AA1 L - HH AH0 T
+STAHLMAN  S T AA1 L - M AH0 N
+STAHLY  S T AE1 - L IY0
+STAHMER  S T AA1 - M ER0
+STAHNKE  S T AE1 NG K
+STAHR  S T AE1 R
+STAI  S T AA1 - IY0
+STAIB  S T EY1 B
+STAID  S T EY1 D
+STAIGER  S T AY1 - G ER0
+STAILEY  S T EY1 - L IY0
+STAIN  S T EY1 N
+STAINBACK  S T EY1 N - B AE2 K
+STAINBROOK  S T EY1 N - B R UH2 K
+STAINED  S T EY1 N D
+STAINES  S T EY1 N Z
+STAINING  S T EY1 - N IH0 NG
+STAINLESS  S T EY1 N - L AH0 S
+STAINMASTER  S T EY1 N - M AE2 - S T ER0
+STAINS  S T EY1 N Z
+STAIR  S T EH1 R
+STAIRCASE  S T EH1 R - K EY2 S
+STAIRCASES  S T EH1 R - K EY2 - S IH0 Z
+STAIRS  S T EH1 R Z
+STAIRWAY  S T EH1 R - W EY2
+STAIRWAYS  S T EH1 R - W EY2 Z
+STAIRWELL  S T EH1 R - W EH2 L
+STAIRWELLS  S T EH1 R - W EH2 L Z
+STAKE  S T EY1 K
+STAKE'S  S T EY1 K S
+STAKE-OUT  S T EY1 K - AW1 T
+STAKED  S T EY1 K T
+STAKEHOLDER  S T EY1 K - HH OW2 L - D ER0
+STAKEHOLDERS  S T EY1 K - HH OW2 L - D ER0 Z
+STAKEOUT  S T EY1 K - AW2 T
+STAKEOUTS  S T EY1 K - AW2 T S
+STAKER  S T EY1 - K ER0
+STAKES  S T EY1 K S
+STAKING  S T EY1 - K IH0 NG
+STALCUP  S T AO1 L K - AH2 P
+STALDER  S T AO1 L - D ER0
+STALE  S T EY1 L
+STALEMATE  S T EY1 L - M EY2 T
+STALEMATED  S T EY1 L - M EY2 - T IH0 D
+STALEY  S T EY1 - L IY0
+STALEY'S  S T EY1 - L IY0 Z
+STALIN  S T AA1 - L AH0 N
+STALIN'S  S T AA1 - L IH0 N Z
+STALINGRAD  S T AE1 - L IH0 N - G R AE2 D
+STALINISM  S T AE1 - L IH0 - N IH2 - Z AH0 M
+STALINIST  S T AA1 - L IH0 - N IH0 S T
+STALINISTIC  S T AA2 - L IH0 - N IH1 - S T IH0 K
+STALINISTS  S T AE1 - L IH0 - N IH0 S T S
+STALINISTS(2)  S T AE1 - L IH0 - N IH0 S S
+STALINISTS(3)  S T AE1 - L IH0 - N IH0 S
+STALINIZATION  S T AE2 - L IH0 - N IH0 - Z EY1 - SH AH0 N
+STALINIZE  S T AE1 - L IH0 - N AY2 Z
+STALK  S T AO1 K
+STALKED  S T AO1 K T
+STALKER  S T AO1 - K ER0
+STALKERS  S T AO1 - K ER0 Z
+STALKING  S T AO1 - K IH0 NG
+STALKS  S T AO1 K S
+STALKY  S T AO1 - K IY0
+STALL  S T AO1 L
+STALLARD  S T AE1 - L ER0 D
+STALLCUP  S T AO1 L K - AH2 P
+STALLED  S T AO1 L D
+STALLER  S T AO1 - L ER0
+STALLIBRASS  S T AE1 - L IH0 - B R AE0 S
+STALLING  S T AO1 - L IH0 NG
+STALLINGS  S T AO1 - L IH0 NG Z
+STALLION  S T AE1 - L Y AH0 N
+STALLIONS  S T AE1 - L Y AH0 N Z
+STALLKAMP  S T AO1 L - K AE2 M P
+STALLMAN  S T AO1 L - M AH0 N
+STALLONE  S T AH0 - L OW1 N
+STALLONE'S  S T AH0 - L OW1 N Z
+STALLS  S T AO1 L Z
+STALLSMITH  S T AO1 L - S M IH2 TH
+STALLWORTH  S T AO1 L - W ER2 TH
+STALNAKER  S T AE1 L - N AH0 - K ER0
+STALOFF  S T AE1 - L AO0 F
+STALON  S T EY1 - L AH0 N
+STALOWA  S T AH0 - L OW1 - AH0
+STALTER  S T AO1 L - T ER0
+STALVEY  S T AE1 L - V IY0
+STALWART  S T AO1 L - W ER0 T
+STALWARTS  S T AO1 L - W ER0 T S
+STALZER  S T EY1 L - Z ER0
+STAM  S T AE1 M
+STAMAND  S T AE1 - M AH0 N D
+STAMANT  S T AE1 - M AH0 N T
+STAMAS  S T AA1 - M AH0 Z
+STAMATY  S T AE1 - M AH0 - T IY0
+STAMBAUGH  S T AE1 M - B AO0
+STAMBERG  S T AE1 M - B ER0 G
+STAMENSON  S T EY1 - M AH0 N - S AH0 N
+STAMER  S T EY1 - M ER0
+STAMEY  S T EY1 - M IY0
+STAMFORD  S T AE1 M - F ER0 D
+STAMINA  S T AE1 - M AH0 - N AH0
+STAMLER  S T AE1 M - L ER0
+STAMM  S T AE1 M
+STAMMEN  S T AE1 - M AH0 N
+STAMMER  S T AE1 - M ER0
+STAMOS  S T EY1 - M OW0 Z
+STAMOUR  S T AH0 - M UH1 R
+STAMP  S T AE1 M P
+STAMPED  S T AE1 M P T
+STAMPEDE  S T AE0 M - P IY1 D
+STAMPEDED  S T AE0 M - P IY1 - D AH0 D
+STAMPEDED(2)  S T AE0 M - P IY1 - D IH0 D
+STAMPEDING  S T AE0 M - P IY1 - D IH0 NG
+STAMPER  S T AE1 M - P ER0
+STAMPFLI  S T AE1 M P F - L IY0
+STAMPING  S T AE1 M - P IH0 NG
+STAMPINGS  S T AE1 M - P IH0 NG Z
+STAMPLEY  S T AE1 M - P L IY0
+STAMPS  S T AE1 M P S
+STAN  S T AE1 N
+STAN'S  S T AE1 N Z
+STANADYNE  S T AE1 - N AH0 - D AY2 N
+STANALAND  S T AE1 - N AH0 - L AH0 N D
+STANARD  S T AE1 - N ER0 D
+STANAWAY  S T AE1 N - AH0 - W EY0
+STANBACK  S T AE1 N - B AE2 K
+STANBERRY  S T AE1 N - B EH2 - R IY0
+STANBERY  S T AE1 N - B ER0 - IY0
+STANBIC  S T AE1 N - B IH0 K
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+STANBURY  S T AE1 N - B EH2 - R IY0
+STANCE  S T AE1 N S
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+STANCH  S T AE1 N CH
+STANCHED  S T AE1 N CH T
+STANCHFIELD  S T AE1 N CH - F IY0 L D
+STANCHING  S T AE1 N - CH IH0 NG
+STANCIK  S T AE1 N - S IH0 K
+STANCIL  S T AE1 N - S IH0 L
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+STANCLIFF  S T AE1 N - K L IH0 F
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+STAND  S T AE1 N D
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+STANDARD'S  S T AE1 N - D ER0 D Z
+STANDARD-BEARER  S T AE1 N - D ER0 D - B EH1 - R ER0
+STANDARD-BEARERS  S T AE1 N - D ER0 D - B EH1 - R ER0 Z
+STANDARDIZATION  S T AE0 N - D ER0 - D IH0 - Z EY1 - SH AH0 N
+STANDARDIZE  S T AE1 N - D ER0 - D AY2 Z
+STANDARDIZED  S T AE1 N - D ER0 - D AY2 Z D
+STANDARDIZING  S T AE1 N - D ER0 - D AY2 - Z IH0 NG
+STANDARDS  S T AE1 N - D ER0 D Z
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+STANDBYS  S T AE1 N D - B AY2 Z
+STANDEFER  S T AE1 N - D IH0 - F ER0
+STANDEN  S T AE1 N - D AH0 N
+STANDER  S T AE1 N - D ER0
+STANDERFER  S T AE1 N - D ER0 - F ER0
+STANDERFORD  S T AE1 N - D ER0 - F ER0 D
+STANDEX  S T AE1 N - D AH0 K S
+STANDFIELD  S T AE1 N D - F IY2 L D
+STANDIFER  S T AE1 N - D IH0 - F ER0
+STANDIFORD  S T AE1 N - D IH0 - F ER0 D
+STANDIN'  S T AE1 N - D IH0 N
+STANDING  S T AE1 N - D IH0 NG
+STANDINGS  S T AE1 N - D IH0 NG Z
+STANDISH  S T AE1 N - D IH0 SH
+STANDLEE  S T AE1 N D - L IY2
+STANDLEY  S T AE1 N D - L IY0
+STANDOFF  S T AE1 N - D AO2 F
+STANDOFFS  S T AE1 N - D AO2 F S
+STANDOUT  S T AE1 N D - AW2 T
+STANDOUTS  S T AE1 N D - AW2 T S
+STANDPOINT  S T AE1 N D - P OY2 N T
+STANDPOINTS  S T AE1 N D - P OY2 N T S
+STANDRE  S T AE1 N - D ER0
+STANDRIDGE  S T AE1 N - D R IH0 JH
+STANDS  S T AE1 N D Z
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+STANDUP  S T AE1 N D - AH2 P
+STANEK  S T AE1 - N IH0 K
+STANFIELD  S T AE1 N - F IY2 L D
+STANFILL  S T AE1 N - F AH0 L
+STANFORD  S T AE1 N - F ER0 D
+STANFORD'S  S T AE1 N - F ER0 D Z
+STANFORTH  S T AE1 N - F ER0 TH
+STANG  S T AE1 NG
+STANGA  S T AA1 NG - G AH0
+STANGE  S T AE1 N JH
+STANGEL  S T EY1 NG - G AH0 L
+STANGELAND  S T EY1 NG - G IH0 - L AH0 N D
+STANGELAND(2)  S T EY1 NG - G L AH0 N D
+STANGELO  S T AA0 NG - G EH1 - L OW0
+STANGER  S T AE1 - NG ER0
+STANGL  S T AE1 NG - G AH0 L
+STANGLAND  S T AE1 NG - G L AH0 N D
+STANGLE  S T AE1 NG - G AH0 L
+STANGLER  S T AE1 NG - G AH0 - L ER0
+STANGLER(2)  S T AE1 NG - G L ER0
+STANGO  S T AA1 NG - G OW0
+STANHOPE  S T AE1 - N AH0 P
+STANIAR  S T EY1 - N IY0 - AA0 R
+STANICH  S T AE1 - N IH0 CH
+STANIFER  S T AE1 - N IH0 - F ER0
+STANIS  S T AE1 - N IH0 S
+STANISH  S T AE1 - N IH0 SH
+STANISLAS  S T AH0 - N IH1 S - L AH0 S
+STANISLAV  S T AE1 - N IH0 - S L AA0 V
+STANISLAW  S T AE1 - N IH0 S - L AO2
+STANISLAWSKI  S T AH0 - N IH0 S - L AA1 F S - K IY0
+STANISZEWSKI  S T AH0 - N IH0 - SH EH1 F S - K IY0
+STANK  S T AE1 NG K
+STANKE  S T AE1 NG K
+STANKEVICH  S T AE1 NG - K AH0 - V IH2 CH
+STANKEY  S T AE1 NG - K IY0
+STANKIEWICZ  S T AE1 N - K AH0 - V IH0 CH
+STANKO  S T AE1 NG - K OW0
+STANKOVICH  S T AE1 NG - K AH0 - V IH0 CH
+STANKOWSKI  S T AH0 NG - K AO1 F S - K IY0
+STANKUS  S T AE1 NG - K AH0 S
+STANLEIGH  S T AE1 N - L AH0
+STANLEY  S T AE1 N - L IY0
+STANLEY'S  S T AE1 N - L IY0 Z
+STANLEYTOWN  S T AE1 N - L IY0 - T AW2 N
+STANLINE  S T AE1 N - L AY2 N
+STANLY  S T AE1 N - L IY0
+STANMORE  S T AE1 N - M AO0 R
+STANN  S T AE1 N
+STANNARD  S T AE1 - N ER0 D
+STANNIE  S T AE1 - N IY0
+STANO  S T AA1 - N OW0
+STANPHILL  S T AE1 N P - HH IH2 L
+STANPHILL(2)  S T AE1 M P - HH IH2 L
+STANSBERRY  S T AE1 N S - B EH2 - R IY0
+STANSBURY  S T AE1 N S - B EH0 - R IY0
+STANSEL  S T AE1 N - S AH0 L
+STANSELL  S T AE1 N - S AH0 L
+STANSFIELD  S T AE1 N S - F IY0 L D
+STANSKY  S T AE1 N S - K IY0
+STANT  S T AE1 N T
+STANTON  S T AE1 N - T AH0 N
+STANWAY  S T AE1 N - W EY2
+STANWICK  S T AE1 N - W IH0 K
+STANWOOD  S T AE1 N - W UH2 D
+STANZA  S T AE1 N - Z AH0
+STANZAS  S T AE1 N - Z AH0 Z
+STANZIONE  S T AA0 N - Z IY0 - OW1 - N IY0
+STAPEL  S T AE1 - P AH0 L
+STAPF  S T AE1 P F
+STAPLE  S T EY1 - P AH0 L
+STAPLED  S T EY1 - P AH0 L D
+STAPLER  S T EY1 - P AH0 - L ER0
+STAPLER(2)  S T EY1 P - L ER0
+STAPLERS  S T EY1 - P AH0 - L ER0 Z
+STAPLERS(2)  S T EY1 P - L ER0 Z
+STAPLES  S T EY1 - P AH0 L Z
+STAPLETON  S T EY1 - P AH0 L - T AH0 N
+STAPLEY  S T AE1 P - L IY0
+STAPLING  S T EY1 - P AH0 L - IH0 NG
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+STAPP  S T AE1 P
+STAR  S T AA1 R
+STAR'S  S T AA1 R Z
+STARACE  S T AA0 - R AA1 - CH IY0
+STARBIRD  S T AA1 R - B ER2 D
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+STARBOARDS  S T AA1 R - B ER0 R D Z
+STARBOARDS(2)  S T AA1 R - B AO2 R D Z
+STARBUCK  S T AA1 R - B AH2 K
+STARBUCK'S  S T AA1 R - B AH2 K S
+STARBUCKS  S T AA1 R - B AH2 K S
+STARCEVICH  S T AA1 R - S IH0 - V IH0 CH
+STARCH  S T AA1 R CH
+STARCHED  S T AA1 R CH T
+STARCHER  S T AA1 R - CH ER0
+STARCHES  S T AA1 R - CH IH0 Z
+STARCHLIKE  S T AA1 R CH - L AY2 K
+STARCHY  S T AA1 R - CH IY0
+STARCK  S T AA1 R K
+STARCKMANN  S T AA1 R K - M AH0 N
+STARCRAFT  S T AA1 R - K R AE2 F T
+STARCROSS  S T AA1 R - K R AO2 S
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+STARDENT  S T AA1 R - D EH2 N T
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+STARED  S T EH1 R D
+STARER  S T EH1 - R ER0
+STARES  S T EH1 R Z
+STARFISH  S T AA1 R - F IH2 SH
+STARGATE  S T AA1 R - G EY2 T
+STARGATES  S T AA1 R - G EY2 T S
+STARGAZER  S T AA1 R - G EY2 - Z ER0
+STARGAZERS  S T AA1 R - G EY2 - Z ER0 Z
+STARIN  S T AE1 - R IH0 N
+STARING  S T EH1 - R IH0 NG
+STARK  S T AA1 R K
+STARK'S  S T AA1 R K S
+STARKE  S T AA1 R K
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+STARKER  S T AA1 R - K ER0
+STARKES  S T AA1 R K S
+STARKEY  S T AA1 R - K IY2
+STARKIST  S T AA1 R - K IH0 S T
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+STARKOVICH  S T AA1 R - K AH0 - V IH0 CH
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+STARLET  S T AA1 R - L AH0 T
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+STARLIT  S T AA1 R - L IH0 T
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+STARN  S T AA1 R N
+STARNER  S T AA1 R - N ER0
+STARNES  S T AA1 R N Z
+STARNS  S T AA1 R N Z
+STARODUBSTEV  S T AA2 - R OW0 - D AH1 B - S T EH0 V
+STARON  S T AE1 - R AH0 N
+STARPLEX  S T AA1 R - P L EH2 K S
+STARPOINTE  S T AA1 R - P OY2 N T
+STARR  S T AA1 R
+STARR'S  S T AA1 R Z
+STARRED  S T AA1 R D
+STARRETT  S T AE1 - R IH0 T
+STARRING  S T AA1 - R IH0 NG
+STARRS  S T AA1 R Z
+STARRY  S T AA1 - R IY0
+STARS  S T AA1 R Z
+STARS'  S T AA1 R Z
+STARSHIP  S T AA1 R - SH IH2 P
+STARSIGHT  S T AA1 R - S AY2 T
+STARSTREAM  S T AA1 R - S T R IY2 M
+STARSTRUCK  S T AA1 R - S T R AH2 K
+START  S T AA1 R T
+START-UP  S T AA1 R T - AH2 P
+START-UPS  S T AA1 R T - AH1 P S
+STARTED  S T AA1 R - T AH0 D
+STARTED(2)  S T AA1 R - T IH0 D
+STARTER  S T AA1 R - T ER0
+STARTERS  S T AA1 R - T ER0 Z
+STARTING  S T AA1 R - T IH0 NG
+STARTLE  S T AA1 R - T AH0 L
+STARTLED  S T AA1 R - T AH0 L D
+STARTLES  S T AA1 R - T AH0 L Z
+STARTLING  S T AA1 R T - L IH0 NG
+STARTLINGLY  S T AA1 R T - L IH0 NG - L IY0
+STARTS  S T AA1 R T S
+STARTUP  S T AA1 R T - AH2 P
+STARTUPS  S T AA1 R T - AH2 P S
+STARVATION  S T AA0 R - V EY1 - SH AH0 N
+STARVE  S T AA1 R V
+STARVED  S T AA1 R V D
+STARVING  S T AA1 R - V IH0 NG
+STARWALT  S T AA1 R - W AH0 L T
+STARWAVE  S T AA1 R - W EY2 V
+STARY  S T EH1 - R IY0
+STARZYK  S T AA1 R - Z IH0 K
+STASH  S T AE1 SH
+STASHED  S T AE1 SH T
+STASHING  S T AE1 - SH IH0 NG
+STASI  S T AA1 - S IY0
+STASIAK  S T AA1 - S IY0 - AE0 K
+STASIK  S T AA1 - S IH0 K
+STASIO  S T AA1 - S IY0 - OW0
+STASKO  S T AA1 - S K OW0
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+STASNY  S T AE1 S - N IY0
+STASSEN  S T AE1 - S AH0 N
+STASSI  S T AE1 - S IY0
+STASTNY  S T AE1 S T - N IY0
+STASZAK  S T AA1 - SH AH0 K
+STASZEWSKI  S T AH0 - SH EH1 F S - K IY0
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+STATE  S T EY1 T
+STATE'S  S T EY1 T S
+STATECRAFT  S T EY1 T - K R AE2 F T
+STATED  S T EY1 - T AH0 D
+STATED(2)  S T EY1 - T IH0 D
+STATEHOOD  S T EY1 T - HH UH2 D
+STATEHOUSE  S T EY1 T - HH AW2 S
+STATEHOUSES  S T EY1 T - HH AW2 - S IH0 Z
+STATELESS  S T EY1 T - L IH0 S
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+STATEMENT'S  S T EY1 T - M AH0 N T S
+STATEMENTS  S T EY1 T - M AH0 N T S
+STATEN  S T AE1 - T AH0 N
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+STATER'S  S T EY1 - T ER0 Z
+STATERS  S T EY1 - T ER0 Z
+STATES  S T EY1 T S
+STATES'  S T EY1 T S
+STATESBOROUGH  S T EY1 T S - B AH0 - R OW0
+STATESIDE  S T EY1 T - S AY1 D
+STATESMAN  S T EY1 T S - M AH0 N
+STATESMAN'S  S T EY1 T S - M AH0 N Z
+STATESMANLIKE  S T AH0 - T EH1 S - M AH0 N - L AY2 K
+STATESMANSHIP  S T EY1 T S - M AH0 N - SH IH2 P
+STATESMEN  S T EY1 T S - M IH0 N
+STATESWEST  S T EY2 T - S W EH1 S T
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+STATHAM  S T AE1 - TH AH0 M
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+STATHOPOULOS  S T AH0 - TH AA1 - P AH0 - L IH0 S
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+STATING  S T EY1 - T IH0 NG
+STATION  S T EY1 - SH AH0 N
+STATION'S  S T EY1 - SH AH0 N Z
+STATIONARY  S T EY1 - SH AH0 N - EH2 - R IY0
+STATIONED  S T EY1 - SH AH0 N D
+STATIONER  S T EY1 - SH AH0 N - ER0
+STATIONERS  S T EY1 - SH AH0 N - ER0 Z
+STATIONERY  S T EY1 - SH AH0 N - EH2 - R IY0
+STATIONING  S T EY1 - SH AH0 N - IH0 NG
+STATIONS  S T EY1 - SH AH0 N Z
+STATIONS'  S T EY1 - SH AH0 N Z
+STATISM  S T EY1 - T IH2 - Z AH0 M
+STATIST  S T EY1 - T IH0 S T
+STATISTIC  S T AH0 - T IH1 - S T IH0 K
+STATISTICAL  S T AH0 - T IH1 - S T IH0 - K AH0 L
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+STATISTICALLY(2)  S T AH0 - T IH1 - S T IH0 K - L IY0
+STATISTICIAN  S T AE2 - T AH0 - S T IH1 - SH AH0 N
+STATISTICIANS  S T AE2 - T IH0 - S T IH1 - SH AH0 N Z
+STATISTICS  S T AH0 - T IH1 - S T IH0 K S
+STATISTICS'  S T AH0 - T IH1 - S T IH0 K S
+STATISTS  S T EY1 - T IH0 S T S
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+STATISTS(3)  S T EY1 - T IH0 S
+STATLER  S T AE1 T - L ER0
+STATOIL  S T AH0 - T OY1 L
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+STATS  S T AE1 T S
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+STATTON  S T AE1 - T AH0 N
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+STATUESQUE  S T AE2 - CH UW0 - EH1 S K
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+STATUM  S T AE1 - T AH0 M
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+STATUS  S T AE1 - T AH0 S
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+STATUTORY  S T AE1 - CH AH0 - T AO2 - R IY0
+STATZ  S T AE1 T S
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+STAUB  S T AO1 B
+STAUBER  S T AW1 - B ER0
+STAUBIN  S T AW1 - B IH0 N
+STAUBS  S T AO1 B Z
+STAUCH  S T AO1 CH
+STAUDACHER  S T AW1 - D AH0 - K ER0
+STAUDE  S T AO1 D
+STAUDER  S T AW1 - D ER0
+STAUDINGER  S T AW1 - D IH0 - NG ER0
+STAUDT  S T AO1 D T
+STAUFF  S T AO1 F
+STAUFFACHER  S T AW1 - F AH0 - K ER0
+STAUFFER  S T AO1 - F ER0
+STAUFFER'S  S T AO1 - F ER0 Z
+STAUNCH  S T AO1 N CH
+STAUNCHEST  S T AO1 N - CH AH0 S T
+STAUNCHLY  S T AO1 N CH - L IY0
+STAUNTON  S T AO1 N - T AH0 N
+STAUP  S T AO1 P
+STAUSS  S T AO1 S
+STAUTER  S T AW1 - T ER0
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+STAVED  S T EY1 V D
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+STAVER  S T EY1 - V ER0
+STAVES  S T EY1 V Z
+STAVING  S T EY1 - V IH0 NG
+STAVINOHA  S T AE0 - V IH0 - N OW1 - HH AH0
+STAVOLA  S T AA0 - V OW1 - L AH0
+STAVROPOULOS  S T AH0 - V R AA1 - P AH0 - L IH0 S
+STAVROS  S T AH0 - V R OW1 Z
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+STAWSKI  S T AA1 F S - K IY0
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+STAYOVERS  S T EY1 - OW2 - V ER0 Z
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+STEELMAKERS  S T IY1 L - M EY2 - K ER0 Z
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+STEELWORKERS  S T IY1 L - W ER2 - K ER0 Z
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+STEELWORKS  S T IY1 L - W ER2 K S
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+STEFANI  S T EH1 - F AH0 - N IY0
+STEFANI'S  S T EH1 - F AH0 - N IY0 Z
+STEFANIAK  S T IH0 - F AE1 - N IY0 - AE0 K
+STEFANIC  S T IH0 - F AE1 - N IH0 K
+STEFANICH  S T EH1 - F AH0 - N IH0 CH
+STEFANICK  S T EH1 - F AH0 N - IH0 K
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+STEFANO  S T EH1 - F AH0 - N OW0
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+STEFANOWICZ  S T IH0 - F AE1 - N AH0 - V IH0 CH
+STEFANSKI  S T IH0 - F AE1 N S - K IY0
+STEFFAN  S T EH1 - F AH0 N
+STEFFANCI  S T EH2 - F AA1 N - S IY0
+STEFFE  S T EH1 F
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+STEFFEL  S T EH1 - F AH0 L
+STEFFEN  S T EH1 - F AH0 N
+STEFFENHAGEN  S T EH1 - F IH0 N - HH AH0 - G AH0 N
+STEFFENS  S T EH1 - F AH0 N Z
+STEFFENSEN  S T EH1 - F IH0 N - S AH0 N
+STEFFENSMEIER  S T EH1 - F IH0 N - S M AY0 - ER0
+STEFFENSON  S T EH1 - F IH0 N - S AH0 N
+STEFFES  S T EH1 F S
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+STEFFI  S T EH1 - F IY0
+STEFFIE  S T EH1 - F IY0
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+STEFL  S T EH1 - F AH0 L
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+STEGE  S T IY1 JH
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+STEGENGA  S T EH0 - JH EH1 NG - G AH0
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+STEGMAN  S T EH1 G - M AH0 N
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+STEGOSAURUS  S T EH2 - G AH0 - S AO1 - R AH0 S
+STEHLE  S T EH1 - HH AH0 L
+STEHLIK  S T EH1 - L IH0 K
+STEHLIN  S T EH1 - L IH0 N
+STEHLING  S T EH1 - L IH0 NG
+STEHMAN  S T EH1 - M AH0 N
+STEHR  S T EH1 R
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+STEICHEN  S T AY1 - K AH0 N
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+STEIDL  S T IY1 - D AH0 L
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+STEIG  S T IY1 G
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+STEIGERWALT  S T AY1 - G ER0 - W AH0 L T
+STEIL  S T IY1 L
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+STEIMEL  S T AY1 - M AH0 L
+STEIMER  S T AY1 - M ER0
+STEIMLE  S T IY1 - M AH0 L
+STEIN  S T AY1 N
+STEIN'S  S T AY1 N Z
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+STEINBERG'S  S T AY1 N - B ER0 G Z
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+STEINBRINK  S T AY1 N - B R IH2 NG K
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+STRAIGHTER  S T R EY1 - T ER0
+STRAIGHTFORWARD  S T R EY1 T - F AO1 R - W ER0 D
+STRAIGHTFORWARDLY  S T R EY2 T - F AO1 R - W ER0 D - L IY0
+STRAIGHTS  S T R EY1 T S
+STRAIN  S T R EY1 N
+STRAINED  S T R EY1 N D
+STRAINING  S T R EY1 - N IH0 NG
+STRAINS  S T R EY1 N Z
+STRAIT  S T R EY1 T
+STRAITJACKET  S T R EY1 T - JH AE2 - K AH0 T
+STRAITS  S T R EY1 T S
+STRAKA  S T R AA1 - K AH0
+STRAKER  S T R EY1 - K ER0
+STRALEY  S T R AE1 - L IY0
+STRAM  S T R AE1 M
+STRANAHAN  S T R AE1 - N AH0 - HH AE0 N
+STRAND  S T R AE1 N D
+STRANDBERG  S T R AE1 N D - B ER0 G
+STRANDE  S T R AE1 N D
+STRANDED  S T R AE1 N - D AH0 D
+STRANDED(2)  S T R AE1 N - D IH0 D
+STRANDING  S T R AE1 N - D IH0 NG
+STRANDLINE  S T R AE1 N D - L AY2 N
+STRANDLINE(2)  S T R AE1 N - L AY2 N
+STRANDLINES  S T R AE1 N D - L AY2 N Z
+STRANDLINES(2)  S T R AE1 N - L AY2 N Z
+STRANDS  S T R AE1 N D Z
+STRANG  S T R AE1 NG
+STRANGE  S T R EY1 N JH
+STRANGELOVE  S T R EY1 N - JH L AH2 V
+STRANGELY  S T R EY1 N JH - L IY0
+STRANGENESS  S T R EY1 N JH - N AH0 S
+STRANGER  S T R EY1 N - JH ER0
+STRANGER'S  S T R EY1 N - JH ER0 Z
+STRANGERS  S T R EY1 N - JH ER0 Z
+STRANGEST  S T R EY1 N - JH IH0 S T
+STRANGIS  S T R AE1 N - JH IH0 S
+STRANGLE  S T R AE1 NG - G AH0 L
+STRANGLED  S T R AE1 NG - G AH0 L D
+STRANGLEHOLD  S T R AE1 NG - G AH0 L - HH OW2 L D
+STRANGLER  S T R AE1 NG - G L ER0
+STRANGLING  S T R AE1 NG - G AH0 - L IH0 NG
+STRANGLING(2)  S T R AE1 NG - G L IH0 NG
+STRANGULATE  S T R AE1 NG - G Y AH0 - L EY2 T
+STRANGULATION  S T R AE2 NG - G Y AH0 - L EY1 - SH AH0 N
+STRANGULATIONS  S T R AE2 NG - G Y AH0 - L EY1 - SH AH0 N Z
+STRANGWAYES  S T R AE1 NG - W EY2 Z
+STRANO  S T R AA1 - N OW0
+STRANSKY  S T R AE1 N S - K IY0
+STRAP  S T R AE1 P
+STRAPPED  S T R AE1 P T
+STRAPPING  S T R AE1 - P IH0 NG
+STRAPS  S T R AE1 P S
+STRASBERG  S T R AE1 S - B ER0 G
+STRASBOURG  S T R AE1 S - B AO2 R G
+STRASBURG  S T R AE1 S - B ER0 G
+STRASBURGER  S T R AE1 S - B ER0 - G ER0
+STRASSBURG  S T R AE1 S - B ER0 G
+STRASSBURGER  S T R AE1 S - B ER0 - G ER0
+STRASSER  S T R AE1 - S ER0
+STRASSMAN  S T R AE1 S - M AH0 N
+STRASSNER  S T R AE1 S - N ER0
+STRASZHEIM  S T R AE1 S - HH AY2 M
+STRATA  S T R AE1 - T AH0
+STRATACOM  S T R AE1 - T AH0 - K AA0 M
+STRATAGEMS  S T R AE1 - T AH0 - JH AH0 M Z
+STRATAS  S T R AE1 - T AH0 Z
+STRATE  S T R EY1 T
+STRATEGEM  S T R AE1 - T IH0 - JH EH0 M
+STRATEGIC  S T R AH0 - T IY1 - JH IH0 K
+STRATEGICAL  S T R AH0 - T IY1 - JH IH0 - K AH0 L
+STRATEGICALLY  S T R AH0 - T IY1 - JH IH0 K - L IY0
+STRATEGIES  S T R AE1 - T AH0 - JH IY0 Z
+STRATEGIST  S T R AE1 - T IH0 - JH IH0 S T
+STRATEGISTS  S T R AE1 - T IH0 - JH IH0 S T S
+STRATEGISTS(2)  S T R AE1 - T IH0 - JH IH0 S S
+STRATEGISTS(3)  S T R AE1 - T IH0 - JH IH0 S
+STRATEGIZE  S T R AE1 - T AH0 - JH AY0 Z
+STRATEGIZING  S T R AE1 - T AH0 - JH AY0 - Z IH0 NG
+STRATEGY  S T R AE1 - T AH0 - JH IY0
+STRATEGY'S  S T R AE1 - T AH0 - JH IY0 Z
+STRATER  S T R EY1 - T ER0
+STRATFORD  S T R AE1 T - F ER0 D
+STRATHMAN  S T R AE1 TH - M AH0 N
+STRATIFIED  S T R AE1 - T AH0 - F AY2 D
+STRATIFY  S T R AE1 - T AH0 - F AY2
+STRATIGRAPHIC  S T R AE2 - T AH0 - G R AE1 - F IH0 K
+STRATMAN  S T R AE1 T - M AH0 N
+STRATMANN  S T R AE1 T - M AH0 N
+STRATOCASTER  S T R AE1 - T OW0 - K AE2 - S T ER0
+STRATOFLEX  S T R AE1 - T OW0 - F L EH2 K S
+STRATOSPHERE  S T R AE1 - T AH0 - S F IH2 R
+STRATOSPHERIC  S T R AE2 - T AH0 - S F IH1 - R IH0 K
+STRATTON  S T R AE1 - T AH0 N
+STRATUM  S T R AE1 - T AH0 M
+STRATUS  S T R AE1 - T AH0 S
+STRATUS'S  S T R AE1 - T AH0 - S IH0 Z
+STRAUB  S T R AW1 B
+STRAUBE  S T R AW1 B
+STRAUCH  S T R AW1 K
+STRAUGHAN  S T R AO1 - AH0 N
+STRAUGHN  S T R AO1 N
+STRAUGHTER  S T R AO1 - T ER0
+STRAUM  S T R AW1 M
+STRAUM(2)  S T R AA1 M
+STRAUS  S T R AW1 S
+STRAUSBAUGH  S T R AW1 S - B AW0
+STRAUSE  S T R AW1 S
+STRAUSER  S T R AW1 - S ER0
+STRAUSS  S T R AW1 S
+STRAUSS'S  S T R AW1 - S IH0 Z
+STRAUSSER  S T R AW1 - S ER0
+STRAVINSKY  S T R AH0 - V IH1 N - S K IY0
+STRAVINSKY'S  S T R AH0 - V IH1 N - S K IY0 Z
+STRAW  S T R AO1
+STRAWBERRIES  S T R AO1 - B EH2 - R IY0 Z
+STRAWBERRY  S T R AO1 - B EH2 - R IY0
+STRAWBRIDGE  S T R AO1 - B R IH2 JH
+STRAWDER  S T R AO1 - D ER0
+STRAWDERMAN  S T R AO1 - D ER0 - M AH0 N
+STRAWN  S T R AO1 N
+STRAWS  S T R AO1 Z
+STRAWSER  S T R AO1 - Z ER0
+STRAY  S T R EY1
+STRAYED  S T R EY1 D
+STRAYER  S T R EY1 - ER0
+STRAYHORN  S T R EY1 - HH ER0 N
+STRAYING  S T R EY1 - IH0 NG
+STRAYS  S T R EY1 Z
+STREAK  S T R IY1 K
+STREAKED  S T R IY1 K T
+STREAKER  S T R IY1 - K ER0
+STREAKING  S T R IY1 - K IH0 NG
+STREAKS  S T R IY1 K S
+STREAM  S T R IY1 M
+STREAMED  S T R IY1 M D
+STREAMER  S T R IY1 - M ER0
+STREAMERS  S T R IY1 - M ER0 Z
+STREAMING  S T R IY1 - M IH0 NG
+STREAMLINE  S T R IY1 M - L AY2 N
+STREAMLINED  S T R IY1 M - L AY2 N D
+STREAMLINING  S T R IY1 M - L AY2 - N IH0 NG
+STREAMS  S T R IY1 M Z
+STREATER  S T R IY1 - T ER0
+STREB  S T R EH1 B
+STREBE  S T R IY1 B
+STREBECK  S T R IY1 - B EH0 K
+STREBEL  S T R EH1 - B AH0 L
+STRECK  S T R EH1 K
+STRECKER  S T R EH1 - K ER0
+STREED  S T R IY1 D
+STREEP  S T R IY1 P
+STREEPER  S T R IY1 - P ER0
+STREET  S T R IY1 T
+STREET'S  S T R IY1 T S
+STREETCAR  S T R IY1 T - K AA2 R
+STREETER  S T R IY1 - T ER0
+STREETERS  S T R IY1 - T ER0 Z
+STREETMAN  S T R IY1 T - M AH0 N
+STREETS  S T R IY1 T S
+STREETT  S T R IY1 T
+STREETWISE  S T R IY1 T - W AY2 Z
+STREETY  S T R IY1 - T IY0
+STREFF  S T R EH1 F
+STREGE  S T R IY1 JH
+STREHL  S T R EH1 L
+STREHLE  S T R EH1 L
+STREHLOW  S T R EH1 - L OW0
+STREIB  S T R AY1 B
+STREIBER  S T R AY1 - B ER0
+STREICH  S T R AY1 K
+STREICHER  S T R AY1 - K ER0
+STREIFF  S T R AY1 F
+STREIGHT  S T R EY1 T
+STREIKER  S T R AY1 - K ER0
+STREISAND  S T R AY1 - Z AH0 N D
+STREISAND'S  S T R AY1 - Z AH0 N D Z
+STREISAND'S(2)  S T R AY1 - S AE2 N D Z
+STREISAND(2)  S T R AY1 - S AE2 N D
+STREIT  S T R AY1 T
+STREITMATTER  S T R AY1 T - M AH0 - T ER0
+STRELOW  S T R EH1 - L OW0
+STRENG  S T R EH1 NG
+STRENGER  S T R EH1 NG - G ER0
+STRENGTH  S T R EH1 NG K TH
+STRENGTH(2)  S T R EH1 NG TH
+STRENGTHEN  S T R EH1 NG - TH AH0 N
+STRENGTHENED  S T R EH1 NG - TH AH0 N D
+STRENGTHENING  S T R EH1 NG - TH AH0 N - IH0 NG
+STRENGTHENS  S T R EH1 NG - TH AH0 N Z
+STRENGTHS  S T R EH1 NG K TH S
+STRENGTHS(2)  S T R EH1 NG TH S
+STRENIO  S T R IY1 - N IY0 - OW0
+STRENUOUS  S T R EH1 - N Y UW0 - AH0 S
+STRENUOUSLY  S T R EH1 - N Y UW0 - AH0 S - L IY0
+STREP  S T R EH1 P
+STREPS  S T R EH1 P S
+STREPTOCOCCUS  S T R EH2 P - T AH0 - K AO1 - K AH0 S
+STREPTOKINASE  S T R EH2 P - T AH0 - K AY1 - N EY2 S
+STREPTOKINASE(2)  S T R EH2 P - T OW0 - K AY1 - N EY2 Z
+STRESS  S T R EH1 S
+STRESSED  S T R EH1 S T
+STRESSES  S T R EH1 - S AH0 Z
+STRESSES(2)  S T R EH1 - S IH0 Z
+STRESSFUL  S T R EH1 S - F AH0 L
+STRESSING  S T R EH1 - S IH0 NG
+STRESSOR  S T R EH1 - S ER0
+STRESSORS  S T R EH1 - S ER0 Z
+STRETCH  S T R EH1 CH
+STRETCHED  S T R EH1 CH T
+STRETCHER  S T R EH1 - CH ER0
+STRETCHER-BEARER  S T R EH1 - CH ER0 - B EH1 - R ER0
+STRETCHER-BEARERS  S T R EH1 - CH ER0 - B EH1 - R ER0 Z
+STRETCHERS  S T R EH1 - CH ER0 Z
+STRETCHES  S T R EH1 - CH AH0 Z
+STRETCHES(2)  S T R EH1 - CH IH0 Z
+STRETCHING  S T R EH1 - CH IH0 NG
+STRETTO  S T R EH1 - T OW2
+STREVIG  S T R EH1 - V IH0 G
+STREW  S T R UW1
+STREWN  S T R UW1 N
+STREY  S T R EY1
+STRIAR  S T R AY1 R
+STRIBLING  S T ER1 - AH0 - B AH0 L - IH0 NG
+STRIBLING(2)  S T R IH1 - B L IH0 NG
+STRICK  S T R IH1 K
+STRICKEN  S T R IH1 - K AH0 N
+STRICKER  S T R IH1 - K ER0
+STRICKLAND  S T R IH1 - K L AH0 N D
+STRICKLEN  S T R IH1 - K AH0 - L AH0 N
+STRICKLER  S T R IH1 - K L ER0
+STRICKLIN  S T R IH1 - K L IH0 N
+STRICKLING  S T R IH1 - K L IH0 NG
+STRICT  S T R IH1 K T
+STRICTER  S T R IH1 K - T ER0
+STRICTEST  S T R IH1 K - T AH0 S T
+STRICTLY  S T R IH1 K T - L IY0
+STRICTURE  S T R IH1 K - CH ER0
+STRICTURES  S T R IH1 K - CH ER0 Z
+STRIDE  S T R AY1 D
+STRIDENCY  S T R AY1 - D AH0 N - S IY0
+STRIDENT  S T R AY1 - D AH0 N T
+STRIDENTLY  S T R AY1 - D AH0 N T - L IY0
+STRIDER  S T R AY1 - D ER0
+STRIDES  S T R AY1 D Z
+STRIDING  S T R AY1 - D IH0 NG
+STRIEBER  S T R AY1 - B ER0
+STRIEGEL  S T R IY1 - G AH0 L
+STRIEKER  S T R IY1 - K ER0
+STRIEKER'S  S T R IY1 - K ER0 Z
+STRIETER  S T R IY1 - T ER0
+STRIFE  S T R AY1 F
+STRIFES  S T R AY1 F S
+STRIKE  S T R AY1 K
+STRIKE'S  S T R AY1 K S
+STRIKEBREAKER  S T R AY1 K - B R EY2 - K ER0
+STRIKEBREAKERS  S T R AY1 K - B R EY2 - K ER0 Z
+STRIKEOUT  S T R AY1 K - AW2 T
+STRIKEOUTS  S T R AY1 K - AW2 T S
+STRIKER  S T R AY1 - K ER0
+STRIKERS  S T R AY1 - K ER0 Z
+STRIKERS'  S T R AY1 - K ER0 Z
+STRIKES  S T R AY1 K S
+STRIKES'  S T R AY1 K S
+STRIKING  S T R AY1 - K IH0 NG
+STRIKINGLY  S T R AY1 - K IH0 NG - L IY0
+STRIMPLE  S T R IH1 M - P AH0 L
+STRINDEN  S T R IH1 N - D AH0 N
+STRINE  S T R AY1 N
+STRING  S T R IH1 NG
+STRINGED  S T R IH1 NG D
+STRINGENCY  S T R IH1 N - JH AH0 N - S IY0
+STRINGENT  S T R IH1 N - JH AH0 N T
+STRINGENTLY  S T R IH1 N - JH AH0 N T - L IY0
+STRINGER  S T R IH1 - NG ER0
+STRINGERS  S T R IH1 - NG ER0 Z
+STRINGFELLOW  S T R IH1 NG - F EH2 - L OW0
+STRINGFIELD  S T R IH1 NG - F IY2 L D
+STRINGHAM  S T R IH1 NG - HH AE2 M
+STRINGING  S T R IH1 - NG IH0 NG
+STRINGS  S T R IH1 NG Z
+STRINGY  S T R IH1 - NG IY0
+STRIP  S T R IH1 P
+STRIP'S  S T R IH1 P S
+STRIPE  S T R AY1 P
+STRIPED  S T R AY1 P T
+STRIPER  S T R AY1 - P ER0
+STRIPERS  S T R AY1 - P ER0 Z
+STRIPES  S T R AY1 P S
+STRIPLIN  S T R IH1 - P L IH0 N
+STRIPLING  S T R IH1 - P L IH0 NG
+STRIPPED  S T R IH1 P T
+STRIPPER  S T R IH1 - P ER0
+STRIPPERS  S T R IH1 - P ER0 Z
+STRIPPING  S T R IH1 - P IH0 NG
+STRIPS  S T R IH1 P S
+STRIPTEASE  S T R IH1 P - T IY2 Z
+STRITE  S T R AY1 T
+STRITTMATTER  S T R IH1 T - M AH0 - T ER0
+STRIVE  S T R AY1 V
+STRIVEN  S T R IH1 - V AH0 N
+STRIVES  S T R AY1 V Z
+STRIVING  S T R AY1 - V IH0 NG
+STRIVINGS  S T R AY1 - V IH0 NG Z
+STRNAD  S T ER1 - N AE0 D
+STROBE  S T R OW1 B
+STROBEL  S T R OW1 - B AH0 L
+STROBEL'S  S T R OW1 - B AH0 L Z
+STROBER  S T R OW1 - B ER0
+STROBL  S T R AA1 - B AH0 L
+STROBLE  S T R OW1 - B AH0 L
+STROBRIDGE  S T R AA1 - B R IH0 JH
+STROCK  S T R AA1 K
+STRODE  S T R OW1 D
+STRODER  S T R OW1 - D ER0
+STROEBEL  S T R OW1 - B AH0 L
+STROESSNER  S T R OW1 S - N ER0
+STROGANOFF  S T R OW1 - G AH0 - N AO2 F
+STROH  S T R OW1
+STROHECKER  S T R OW1 - IH0 - K ER0
+STROHL  S T R OW1 L
+STROHM  S T R OW1 M
+STROHMAIER  S T R OW1 - M AY0 - ER0
+STROHMAN  S T R OW1 - M AH0 N
+STROHMEIER  S T R OW1 - M AY0 - ER0
+STROHMEYER  S T R OW1 - M AY0 - ER0
+STROIK  S T R OY1 K
+STROJNY  S T R OW1 Y - N IY0
+STROKE  S T R OW1 K
+STROKED  S T R OW1 K T
+STROKES  S T R OW1 K S
+STROKING  S T R OW1 - K IH0 NG
+STROLE  S T R OW1 L
+STROLL  S T R OW1 L
+STROLLED  S T R OW1 L D
+STROLLER  S T R OW1 - L ER0
+STROLLERS  S T R OW1 - L ER0 Z
+STROLLING  S T R OW1 - L IH0 NG
+STROLLO  S T R AA1 - L OW0
+STROLLS  S T R OW1 L Z
+STROM  S T R AA1 M
+STROMA  S T R OW1 - M AH0
+STROMAIN  S T R AA1 - M AY0 N
+STROMAN  S T R OW1 - M AH0 N
+STROMBECK  S T R AA1 M - B EH2 K
+STROMBERG  S T R AA1 M - B ER0 G
+STROMBOLI  S T R AA2 M - B OW1 - L IY0
+STROMBOLI'S  S T R AA2 M - B OW1 - L IY0 Z
+STROME  S T R OW1 M
+STROMER  S T R OW1 - M ER0
+STROMGREN  S T R AA1 M - G R EH0 N
+STROMME  S T R AA1 M
+STROMMEN  S T R AA1 - M AH0 N
+STROMQUIST  S T R AA1 M - K W IH2 S T
+STRONACH  S T R AA1 - N AH0 K
+STRONG  S T R AO1 NG
+STRONGER  S T R AO1 NG - ER0
+STRONGER(2)  S T R AO1 NG - G ER0
+STRONGEST  S T R AO1 NG - G AH0 S T
+STRONGHOLD  S T R AO1 NG - HH OW2 L D
+STRONGHOLDS  S T R AO1 NG - HH OW2 L D Z
+STRONGLY  S T R AO1 NG - L IY0
+STRONGMAN  S T R AO1 NG - M AE2 N
+STRONTIUM  S T R AA1 N - T IY0 - AH0 M
+STROOCK  S T R UH1 K
+STROOP  S T R UW1 P
+STROOPE  S T R UW1 P
+STROOT  S T R UW1 T
+STROPE  S T R OW1 P
+STROSCHEIN  S T R AO1 - SH AY0 N
+STROSNIDER  S T R AA1 S - N AY0 - D ER0
+STROSSEN  S T R AO1 - S EH0 N
+STROSSEN(2)  S T R AO1 - S IH0 N
+STROTHER  S T R AA1 - DH ER0
+STROTHERS  S T R AH1 - DH ER0 Z
+STROTHMAN  S T R AA1 TH - M AH0 N
+STROUD  S T R AW1 D
+STROUGH  S T R AW1
+STROUP  S T R UW1 P
+STROUPE  S T R UW1 P
+STROUSE  S T R AW1 S
+STROUT  S T R AW1 T
+STROUTH  S T R AW1 TH
+STROVE  S T R OW1 V
+STROW  S T R OW1
+STROZIER  S T R OW1 - Z IY0 - ER0
+STRUB  S T R AH1 B
+STRUBBE  S T R AH1 B
+STRUBE  S T R UW1 B
+STRUBEL  S T R UW1 - B AH0 L
+STRUBLE  S T R UW1 - B AH0 L
+STRUCHEN  S T R AH1 - K AH0 N
+STRUCK  S T R AH1 K
+STRUCKMAN  S T R AH1 K - M AH0 N
+STRUCTURAL  S T R AH1 K - CH ER0 - AH0 L
+STRUCTURALLY  S T R AH1 K - CH ER0 - AH0 - L IY0
+STRUCTURE  S T R AH1 K - CH ER0
+STRUCTURE'S  S T R AH1 K - CH ER0 Z
+STRUCTURED  S T R AH1 K - CH ER0 D
+STRUCTURES  S T R AH1 K - CH ER0 Z
+STRUCTURING  S T R AH1 K - CH ER0 - IH0 NG
+STRUEBING  S T R UH1 - B IH0 NG
+STRUGGLE  S T R AH1 - G AH0 L
+STRUGGLED  S T R AH1 - G AH0 L D
+STRUGGLES  S T R AH1 - G AH0 L Z
+STRUGGLING  S T R AH1 - G AH0 - L IH0 NG
+STRUGGLING(2)  S T R AH1 - G L IH0 NG
+STRUM  S T R AH1 M
+STRUMMING  S T R AH1 - M IH0 NG
+STRUMS  S T R AH1 M Z
+STRUNG  S T R AH1 NG
+STRUNK  S T R AH1 NG K
+STRUNK'S  S T R AH1 NG K S
+STRUPP  S T R AH1 P
+STRUSS  S T R AH1 S
+STRUT  S T R AH1 T
+STRUTHERS  S T R AH1 - DH ER0 Z
+STRUTS  S T R AH1 T S
+STRUTTING  S T R AH1 - T IH0 NG
+STRUTTON  S T R AH1 - T AH0 N
+STRUTZ  S T R AH1 T S
+STRUVE  S T R UW1 V
+STRYCHARZ  S T R IH1 - HH ER0 Z
+STRYCHNINE  S T R IH1 K - N AY2 N
+STRYKER  S T R AY1 - K ER0
+STRZELECKI  S T R EH2 - Z IH0 - L EH1 T S - K IY0
+STRZELECKI(2)  S T ER2 - Z IH0 - L EH1 T S - K IY0
+STU  S T UW1
+STUARD  S T UW1 - ER0 D
+STUART  S T UW1 - ER0 T
+STUART'S  S T UW1 - ER0 T S
+STUART'S(2)  S T Y UW1 - ER0 T S
+STUART'S(3)  S T AO1 R T S
+STUART(2)  S T Y UW1 - ER0 T
+STUART(3)  S T AO1 R T
+STUARTS  S T UW1 - ER0 T S
+STUB  S T AH1 B
+STUBBE  S T AH1 B
+STUBBED  S T AH1 B D
+STUBBINS  S T AH1 - B IH0 N Z
+STUBBLE  S T AH1 - B AH0 L
+STUBBLEFIELD  S T AH1 - B AH0 L - F IY2 L D
+STUBBORN  S T AH1 - B ER0 N
+STUBBORNLY  S T AH1 - B ER0 N - L IY0
+STUBBORNNESS  S T AH1 - B ER0 N - N AH0 S
+STUBBORNNESS(2)  S T AH1 - B ER0 - N AH0 S
+STUBBS  S T AH1 B Z
+STUBBY  S T AH1 - B IY0
+STUBER  S T UW1 - B ER0
+STUBS  S T AH1 B Z
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+STUCHELL  S T AH1 - K AH0 L
+STUCK  S T AH1 K
+STUCKE  S T AH1 K
+STUCKER  S T AH1 - K ER0
+STUCKERT  S T AH1 - K ER0 T
+STUCKEY  S T AH1 - K IY0
+STUCKI  S T AH1 - K IY0
+STUCKMAN  S T AH1 K - M AH0 N
+STUCKY  S T AH1 - K IY0
+STUD  S T AH1 D
+STUDDARD  S T AH1 - D ER0 D
+STUDDED  S T AH1 - D IH0 D
+STUDDS  S T AH1 D Z
+STUDE  S T UW1 D
+STUDEBAKER  S T UW1 - D AH0 - B EY2 - K ER0
+STUDEMAN  S T UW1 D - M AH0 N
+STUDEMAN(2)  S T UW1 - D AH0 - M AH0 N
+STUDENT  S T UW1 - D AH0 N T
+STUDENT'S  S T UW1 - D AH0 N T S
+STUDENTS  S T UW1 - D AH0 N T S
+STUDENTS'  S T UW1 - D AH0 N T S
+STUDER  S T UW1 - D ER0
+STUDIED  S T AH1 - D IY0 D
+STUDIES  S T AH1 - D IY0 Z
+STUDIO  S T UW1 - D IY0 - OW2
+STUDIO'S  S T UW1 - D IY0 - OW2 Z
+STUDIOS  S T UW1 - D IY0 - OW2 Z
+STUDIOS'  S T UW1 - D IY0 - OW2 Z
+STUDIOUS  S T UW1 - D IY0 - AH0 S
+STUDIOUSLY  S T UW1 - D IY0 - AH0 S - L IY0
+STUDLEY  S T AH1 D - L IY0
+STUDNICKA  S T AH0 D - N IH1 - S K AH0
+STUDS  S T AH1 D Z
+STUDSTILL  S T AH1 D - S T IH2 L
+STUDT  S T AH1 D T
+STUDTGARD  S T AH1 T - G AA2 R D
+STUDY  S T AH1 - D IY0
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+STUDYING  S T AH1 - D IY0 - IH0 NG
+STUDZINSKI  S T AH0 - JH IH1 N - S K IY0
+STUEBE  S T UW1 B
+STUEBER  S T UH1 - B ER0
+STUECK  S T UW1 K
+STUEVE  S T UW1 V
+STUEWE  S T UW1
+STUFF  S T AH1 F
+STUFF'S  S T AH1 F S
+STUFF-IT  S T AH1 - F IH0 T
+STUFF-IT'S  S T AH1 - F IH0 T S
+STUFFED  S T AH1 F T
+STUFFER  S T AH1 - F ER0
+STUFFING  S T AH1 - F IH0 NG
+STUFFLEBEAM  S T AH1 - F AH0 L - B IY2 M
+STUFFLEBEAN  S T AH1 - F AH0 L - B IY2 N
+STUFFS  S T AH1 F S
+STUFFY  S T AH1 - F IY0
+STUHLER  S T UW1 - L ER0
+STUHR  S T ER1
+STUHR(2)  S T UH1 R
+STUKA  S T UW1 - K AH0
+STUKEL  S T UW1 - K AH0 L
+STUKES  S T UW1 K S
+STUKEY  S T AH1 - K IY0
+STULL  S T AH1 L
+STULLER  S T AH1 - L ER0
+STULTIFY  S T AH1 L - T AH0 - F AY2
+STULTIFYING  S T AH1 L - T AH0 - F AY2 - IH0 NG
+STULTS  S T AH1 L T S
+STULTZ  S T AH1 L T S
+STUM  S T AH1 M
+STUMBAUGH  S T AH1 M - B AO2
+STUMBLE  S T AH1 M - B AH0 L
+STUMBLED  S T AH1 M - B AH0 L D
+STUMBLES  S T AH1 M - B AH0 L Z
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+STUMBLING(2)  S T AH1 M - B L IH0 NG
+STUMBO  S T AH1 M - B OW0
+STUMM  S T AH1 M
+STUMP  S T AH1 M P
+STUMPAGE  S T AH1 M - P IH0 JH
+STUMPE  S T AH1 M P
+STUMPED  S T AH1 M P T
+STUMPF  S T AH1 M P F
+STUMPFF  S T AH1 M P F
+STUMPH  S T AH1 M F
+STUMPING  S T AH1 M - P IH0 NG
+STUMPO  S T AH1 M - P OW0
+STUMPP  S T AH1 M P
+STUMPS  S T AH1 M P S
+STUN  S T AH1 N
+STUNG  S T AH1 NG
+STUNK  S T AH1 NG K
+STUNNED  S T AH1 N D
+STUNNING  S T AH1 - N IH0 NG
+STUNNINGLY  S T AH1 - N IH0 NG - L IY0
+STUNT  S T AH1 N T
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+STUNTS  S T AH1 N T S
+STUNTZ  S T AH1 N T S
+STUPA  S T UW1 - P AH0
+STUPAK  S T UW1 - P AH0 K
+STUPAR  S T UW1 - P ER0
+STUPAY  S T UW0 - P EY1
+STUPENDOUS  S T UW0 - P EH1 N - D AH0 S
+STUPID  S T UW1 - P AH0 D
+STUPID(2)  S T UW1 - P IH0 D
+STUPIDEST  S T UW1 - P IH0 - D AH0 S T
+STUPIDITY  S T UW0 - P IH1 - D IH0 - T IY0
+STUPIDLY  S T UW1 - P AH0 D - L IY0
+STUPKA  S T AH1 P - K AH0
+STUPOR  S T UW1 - P ER0
+STUPP  S T AH1 P
+STUPSKI  S T AH1 P - S K IY0
+STURBRIDGE  S T ER1 - B R IH2 JH
+STURC  S T ER1 K
+STURDEVANT  S T ER1 - D IH0 - V AH0 N T
+STURDHAL  S T ER1 - D AA0 L
+STURDIER  S T ER1 - D IY0 - ER0
+STURDINESS  S T ER1 - D IY0 - N AH0 S
+STURDIVANT  S T ER1 - D IH0 - V AH0 N T
+STURDY  S T ER1 - D IY0
+STURGELL  S T ER1 - G AH0 L
+STURGEON  S T ER1 - JH AH0 N
+STURGEON(2)  S T ER1 - JH IH0 N
+STURGEONS  S T ER1 - JH AH0 N Z
+STURGES  S T ER1 - JH IH0 Z
+STURGESS  S T ER1 - G IH0 S
+STURGILL  S T ER1 - G AH0 L
+STURGIS  S T ER1 - JH IH0 S
+STURKIE  S T ER1 - K IY0
+STURM  S T ER1 M
+STURMAN  S T ER1 - M AH0 N
+STURMANS  S T ER1 - M AH0 N Z
+STURMER  S T ER1 - M ER0
+STURN  S T ER1 N
+STURROCK  S T AO1 - R AH0 K
+STURTEVANT  S T ER1 - T AH0 - V AH0 N T
+STURTZ  S T ER1 T S
+STURZA  S T ER1 - Z AH0
+STUTES  S T UW1 T S
+STUTESMAN  S T UW1 T S - M AH0 N
+STUTEVILLE  S T UW1 T - V IH2 L
+STUTHEIT  S T AH1 - TH AY0 T
+STUTLER  S T AH1 T - L ER0
+STUTNER  S T AH1 T - N ER0
+STUTSMAN  S T AH1 T S - M AH0 N
+STUTTER  S T AH1 - T ER0
+STUTTERING  S T AH1 - T ER0 - IH0 NG
+STUTTERS  S T AH1 - T ER0 Z
+STUTTGART  S T AH1 T - G ER0 T
+STUTTGART(2)  S T UW1 T - G AA2 R T
+STUTTGART(3)  SH T UW1 T - G AA2 R T
+STUTTS  S T AH1 T S
+STUTZ  S T AH1 T S
+STUTZMAN  S T AH1 T S - M AH0 N
+STUVE  S T UW1 V
+STUVER  S T UW1 - V ER0
+STUYVESANT  S T AY1 - V AH0 - S AH0 N T
+STY  S T AY1
+STYER  S T AY1 - ER0
+STYERS  S T AY1 - ER0 Z
+STYLE  S T AY1 L
+STYLED  S T AY1 L D
+STYLES  S T AY1 L Z
+STYLING  S T AY1 - L IH0 NG
+STYLISH  S T AY1 - L IH0 SH
+STYLISHLY  S T AY1 - L IH0 SH - L IY0
+STYLIST  S T AY1 - L IH0 S T
+STYLISTIC  S T AY0 - L IH1 - S T IH0 K
+STYLISTICALLY  S T AY0 - L IH1 - S T IH0 K - L IY0
+STYLISTS  S T AY1 - L IH0 S T S
+STYLISTS(2)  S T AY1 - L IH0 S S
+STYLISTS(3)  S T AY1 - L IH0 S
+STYLITES  S T IH0 - L AY1 T S
+STYLIZE  S T AY1 - L AY2 Z
+STYLIZE(2)  S T AY1 - AH0 - L AY2 Z
+STYLIZED  S T AY1 - L AY2 Z D
+STYLUS  S T AY1 - L AH0 S
+STYMIE  S T AY1 - M IY0
+STYMIED  S T AY1 - M IY0 D
+STYMIES  S T AY1 - M IY0 Z
+STYNE  S T AY1 N
+STYRENE  S T AY1 - R IY2 N
+STYROFOAM  S T AY1 - R AH0 - F OW2 M
+STYRON  S T AY1 - R AO0 N
+STYS  S T IH1 S
+STYX  S T IH1 K S
+ST_CHARLES  S EY1 N T - CH AA1 - R AH0 L Z
+ST_CLAIR  S EY1 N T - K L EH1 R
+ST_CLAIRE  S EY1 N T - K L EH1 R
+ST_CYR  S EY1 N T - K IH1 R
+ST_CYR(2)  S EY1 N T - S IH1 R
+ST_DENIS  S EY1 N T - D EH1 - N IH0 S
+ST_DENNIS  S EY1 N T - D EH1 - N IH0 S
+ST_GEORGE  S EY1 N T - JH AO1 R JH
+ST_GERMAIN  S EY1 N T - JH ER2 - M EY1 N
+ST_GERMAINE  S EY1 N T - JH ER2 - M EY1 N
+ST_GERMAINE(2)  S AA1 N - ZH ER2 - M EY1 N
+ST_HILAIRE  S EY1 N T - HH IH0 - L EY1 R
+ST_JACQUES  S EY1 N T - JH AA1 K S
+ST_JACQUES(2)  S AA1 N - ZH AA1 K S
+ST_JAMES  S EY1 N T - JH EY1 M Z
+ST_JEAN  S EY1 N T - JH IY1 N
+ST_JOHN  S EY1 N T - JH AA1 N
+ST_JULIEN  S EY1 N T - JH UW1 - L IY0 - AH0 N
+ST_LAURENT  S EY1 N T - L AO1 - R AH0 N T
+ST_LAURENT(2)  S AA1 N - L AO2 - R AO1 N T
+ST_LAWRENCE  S EY1 N T - L AO1 - R AH0 N S
+ST_LOUIS  S EY1 N T - L UW1 - AH0 S
+ST_LOUIS(2)  S EY1 N T - L UW1 - IY0
+ST_LUCIA  S EY1 N T - L UW1 - SH AH0
+ST_LUCIA(2)  S EY1 N T - L UW2 - S IY1 - AH0
+ST_MARIE  S EY1 N T - M ER0 - IY1
+ST_MARTIN  S EY1 N T - M AA1 R - T IH0 N
+ST_MARY  S EY1 N T - M EH1 - R IY0
+ST_PETER  S EY1 N T - P IY1 - T ER0
+ST_PETERSBURG  S EY1 N T - P IY1 - T ER0 Z - B ER0 G
+ST_PIERRE  S EY1 N T - P IY0 - EH1 R
+ST_THOMAS  S EY1 N T - T AA1 - M AH0 S
+ST_THOMAS(2)  S EY1 N - T AA1 - M AH0 S
+SU  S UW1
+SU(2)  EH1 - S Y UW1
+SUARD  S UW1 - AA0 R D
+SUARD(2)  S W AA1 R D
+SUAREZ  S W AA0 - R EH1 Z
+SUASION  S W EY1 - ZH AH0 N
+SUATA  S UW0 - AA1 - T AH0
+SUATA'S  S UW0 - AA1 - T AH0 Z
+SUAVE  S W AA1 V
+SUAZO  S W AA1 - Z OW0
+SUB  S AH1 B
+SUB'S  S AH1 B Z
+SUB-WAY  S AH1 B - W EY2
+SUBA  S UW1 - B AH0
+SUBACUTE  S AH1 - B AH0 - K Y UW1 T
+SUBANDRIO  S AH0 - B AE1 N - D R IY0 - OW0
+SUBARU  S UW1 - B ER0 - UW0
+SUBASSEMBLIES  S AH2 - B AH0 - S EH1 M - B L IY0 Z
+SUBASSEMBLY  S AH2 - B AH0 - S EH1 M - B L IY0
+SUBATOMIC  S AH2 B - AH0 - T AA1 - M IH0 K
+SUBBED  S AH1 B D
+SUBBING  S AH1 - B IH0 NG
+SUBCHAPTER  S AH1 B - CH AE1 P - T ER0
+SUBCOMMANDER  S AH1 B - K AH0 - M AE2 N - D ER0
+SUBCOMMANDER'S  S AH1 B - K AH0 - M AE2 N - D ER0 Z
+SUBCOMMANDERS  S AH1 B - K AH0 - M AE2 N - D ER0 Z
+SUBCOMMITTEE  S AH1 B - K AH0 - M IH1 - T IY0
+SUBCOMMITTEE'S  S AH1 B - K AH0 - M IH1 - T IY0 Z
+SUBCOMMITTEES  S AH1 B - K AH0 - M IH1 - T IY0 Z
+SUBCOMPACT  S AH0 B - K AA1 M - P AE0 K T
+SUBCOMPACTS  S AH0 B - K AA1 M - P AE0 K T S
+SUBCONSCIOUS  S AH0 B - K AA1 N - SH AH0 S
+SUBCONSCIOUSLY  S AH0 B - K AA1 N - SH AH0 S - L IY0
+SUBCONTINENT  S AH0 B - K AA1 N - T IH0 - N AH0 N T
+SUBCONTINENTS  S AH0 B - K AA1 N - T IH0 - N AH0 N T S
+SUBCONTRACT  S AH0 B - K AA1 N - T R AE2 K T
+SUBCONTRACTED  S AH0 B - K AA1 N - T R AE0 K - T IH0 D
+SUBCONTRACTING  S AH2 B - K AH0 N - T R AE1 K - T IH0 NG
+SUBCONTRACTOR  S AH0 B - K AA1 N - T R AE2 K - T ER0
+SUBCONTRACTORS  S AH0 B - K AA1 N - T R AE0 K - T ER0 Z
+SUBCONTRACTS  S AH0 B - K AA1 N - T R AE2 K T S
+SUBCULTURE  S AH1 B - K AH2 L - CH ER0
+SUBCULTURES  S AH1 B - K AH2 L - CH ER0 Z
+SUBDIVIDE  S AH2 B - D AH0 - V AY1 D
+SUBDIVIDED  S AH2 B - D IH0 - V AY1 - D IH0 D
+SUBDIVISION  S AH1 B - D IH0 - V IH2 - ZH AH0 N
+SUBDIVISIONS  S AH1 B - D IH0 - V IH2 - ZH AH0 N Z
+SUBDUE  S AH0 B - D UW1
+SUBDUED  S AH0 B - D UW1 D
+SUBDUING  S AH0 B - D UW1 - IH0 NG
+SUBER  S UW1 - B ER0
+SUBFAMILIES  S AH1 B - F AE2 - M AH0 - L IY0 Z
+SUBFAMILY  S AH1 B - F AE2 - M AH0 - L IY0
+SUBGROUP  S AH1 B - G R UW2 P
+SUBGROUPS  S AH1 B - G R UW2 P S
+SUBHLOK  S AH1 B - L AA2 K
+SUBHUMAN  S AH2 B - HH Y UW1 - M AH0 N
+SUBIA  S UW0 - B IY1 - AH0
+SUBIC  S UW1 - B IH0 K
+SUBJECT  S AH0 B - JH EH1 K T
+SUBJECT'S  S AH1 B - JH IH0 K T S
+SUBJECT(2)  S AH1 B - JH IH0 K T
+SUBJECTED  S AH0 B - JH EH1 K - T IH0 D
+SUBJECTING  S AH0 B - JH EH1 K - T IH0 NG
+SUBJECTIVE  S AH0 B - JH EH1 K - T IH0 V
+SUBJECTIVITY  S AH0 B - JH EH0 K - T IH1 - V IH0 - T IY0
+SUBJECTS  S AH1 B - JH IH0 K T S
+SUBJECTS'  S AH1 B - JH EH0 K T S
+SUBJECTS'(2)  S AH1 B - JH EH0 K S
+SUBJECTS(2)  S AH0 B - JH EH1 K T S
+SUBJECTS(3)  S AH0 B - JH EH1 K S
+SUBJUGATE  S AH1 B - JH AH0 - G EY2 T
+SUBJUGATED  S AH1 B - JH AH0 - G EY2 - T IH0 D
+SUBKINGDOM  S AH0 B - K IH1 NG - D AH0 M
+SUBLEASE  S AH1 B - L IY2 S
+SUBLEASING  S AH0 B - L IY1 - S IH0 NG
+SUBLET  S AH1 - B L EH2 T
+SUBLETT  S UW1 - B L IH0 T
+SUBLIME  S AH0 - B L AY1 M
+SUBLIMINAL  S AH0 B - L IH1 - M IH0 - N AH0 L
+SUBLIMINALLY  S AH0 B - L IH1 - M IH0 - N AH0 - L IY0
+SUBLUXATION  S AH0 - B L AH0 K - S EY1 - SH AH0 N
+SUBLUXATIONS  S AH0 - B L AH0 K - S EY1 - SH AH0 N Z
+SUBMACHINE  S AH2 B - M AH0 - SH IY1 N
+SUBMARINE  S AH1 B - M ER0 - IY2 N
+SUBMARINE'S  S AH1 B - M ER0 - IY2 N Z
+SUBMARINE'S(2)  S AH0 B - M ER0 - IY1 N Z
+SUBMARINE(2)  S AH2 B - M ER0 - IY1 N
+SUBMARINES  S AH1 B - M ER0 - IY2 N Z
+SUBMARINES'S  S AH1 B - M ER0 - IY2 N - Z IH0 Z
+SUBMARINES(2)  S AH0 B - M ER0 - IY1 N Z
+SUBMERGE  S AH0 B - M ER1 JH
+SUBMERGED  S AH0 B - M ER1 JH D
+SUBMERGENCE  S AH0 B - M ER1 - JH AH0 N S
+SUBMERSE  S AH0 B - M ER1 S
+SUBMERSED  S AH0 B - M ER1 S T
+SUBMERSIBLE  S AH0 B - M ER1 - S IH0 - B AH0 L
+SUBMERSION  S AH0 B - M ER1 - ZH AH0 N
+SUBMINIMUM  S AH0 B - M IH1 - N IH0 - M AH0 M
+SUBMISSION  S AH0 B - M IH1 - SH AH0 N
+SUBMISSIONS  S AH0 B - M IH1 - SH AH0 N Z
+SUBMISSIVE  S AH0 B - M IH1 - S IH0 V
+SUBMIT  S AH0 B - M IH1 T
+SUBMITS  S AH2 B - M IH1 T S
+SUBMITTED  S AH0 B - M IH1 - T AH0 D
+SUBMITTING  S AH0 B - M IH1 - T IH0 NG
+SUBNOTEBOOK  S AH1 B - N OW1 T - B UH2 K
+SUBORDINATE  S AH0 - B AO1 R - D AH0 - N EY2 T
+SUBORDINATE(2)  S AH0 - B AO1 R - D AH0 N - AH0 T
+SUBORDINATED  S AH0 - B AO1 R - D AH0 - N EY2 - T IH0 D
+SUBORDINATES  S AH0 - B AO1 R - D AH0 - N EY2 T S
+SUBORDINATES(2)  S AH0 - B AO1 R - D AH0 N - AH0 T S
+SUBORDINATING  S AH0 - B AO1 R - D AH0 - N EY2 - T IH0 NG
+SUBORDINATION  S AH0 - B AO2 R - D AH0 - N EY1 - SH AH0 N
+SUBOTNICK  S AH0 - B AA1 T - N IH0 K
+SUBPAR  S AH0 B - P AA1 R
+SUBPLOT  S AH1 B - P L AA0 T
+SUBPLOTS  S AH1 B - P L AA0 T S
+SUBPOENA  S AH0 - P IY1 - N AH0
+SUBPOENAED  S AH0 - P IY1 - N AH0 D
+SUBPOENAING  S AH0 - P IY1 - N AH0 - IH0 NG
+SUBPOENAS  S AH0 - P IY1 - N AH0 Z
+SUBPRINCIPAL  S AH0 B - P R IH1 N - S AH0 - P AH0 L
+SUBPRINCIPALS  S AH0 B - P R IH1 N - S AH0 - P AH0 L Z
+SUBRAMANIAN  S UW2 - B R AH0 - M AA1 - N IY0 - AH0 N
+SUBROTO  S UW0 - B R OW1 - T OW0
+SUBS  S AH1 B Z
+SUBS'S  S AH1 B - Z IH0 Z
+SUBSAHARAN  S AH2 B - S AH0 - HH EH1 - R AH0 N
+SUBSCRIBE  S AH0 B - S K R AY1 B
+SUBSCRIBED  S AH0 B - S K R AY1 B D
+SUBSCRIBER  S AH0 B - S K R AY1 - B ER0
+SUBSCRIBER'S  S AH0 B - S K R AY1 - B ER0 Z
+SUBSCRIBERS  S AH0 B - S K R AY1 - B ER0 Z
+SUBSCRIBERS'  S AH0 B - S K R AY1 - B ER0 Z
+SUBSCRIBES  S AH0 B - S K R AY1 B Z
+SUBSCRIBING  S AH0 B - S K R AY1 - B IH0 NG
+SUBSCRIPTION  S AH0 B - S K R IH1 P - SH AH0 N
+SUBSCRIPTIONS  S AH0 B - S K R IH1 P - SH AH0 N Z
+SUBSECTION  S AH1 B - S EH0 K - SH AH0 N
+SUBSEQUENT  S AH1 B - S AH0 - K W AH0 N T
+SUBSEQUENTLY  S AH1 B - S AH0 - K W AH0 N T - L IY0
+SUBSERVIENCE  S AH0 B - S ER1 - V IY0 - AH0 N S
+SUBSERVIENT  S AH0 B - S ER1 - V IY0 - AH0 N T
+SUBSET  S AH1 B - S EH2 T
+SUBSIDE  S AH0 B - S AY1 D
+SUBSIDED  S AH0 B - S AY1 - D IH0 D
+SUBSIDENCE  S AH0 B - S AY1 - D AH0 N S
+SUBSIDES  S AH0 B - S AY1 D Z
+SUBSIDIARIES  S AH0 B - S IH1 - D IY0 - EH2 - R IY0 Z
+SUBSIDIARIES'  S AH0 B - S IH1 - D IY0 - EH2 - R IY0 Z
+SUBSIDIARY  S AH0 B - S IH1 - D IY0 - EH2 - R IY0
+SUBSIDIARY'S  S AH0 B - S IH1 - D IY0 - EH2 - R IY0 Z
+SUBSIDIES  S AH1 B - S AH0 - D IY0 Z
+SUBSIDIES(2)  S AH1 B - S IH0 - D IY0 Z
+SUBSIDING  S AH0 B - S AY1 - D IH0 NG
+SUBSIDIZATION  S AH2 B - S IH0 - D IH0 - Z EY1 - SH AH0 N
+SUBSIDIZE  S AH1 B - S IH0 - D AY2 Z
+SUBSIDIZED  S AH1 B - S IH0 - D AY2 Z D
+SUBSIDIZES  S AH1 B - S IH0 - D AY2 - Z IH0 Z
+SUBSIDIZING  S AH1 B - S IH0 - D AY2 - Z IH0 NG
+SUBSIDY  S AH1 B - S IH0 - D IY0
+SUBSIST  S AH0 B - S IH1 S T
+SUBSISTENCE  S AH0 B - S IH1 - S T AH0 N S
+SUBSOIL  S AH1 B - S OY2 L
+SUBSTANCE  S AH1 B - S T AH0 N S
+SUBSTANCES  S AH1 B - S T AH0 N - S AH0 Z
+SUBSTANCES(2)  S AH1 B - S T AH0 N - S IH0 Z
+SUBSTANDARD  S AH0 B - S T AE1 N - D ER0 D
+SUBSTANTIAL  S AH0 B - S T AE1 N - CH AH0 L
+SUBSTANTIAL(2)  S AH0 B - S T AE1 N - SH AH0 L
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+SUFFER  S AH1 - F ER0
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+T'ANG  T AE1 NG
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+T.S  T IY1 Z
+TA  T AA1
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+TABLE  T EY1 - B AH0 L
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+TABLECLOTH  T EY1 - B AH0 L - K L AO2 TH
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+TABLER  T EY1 - B AH0 L - ER0
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+TABLET  T AE1 - B L AH0 T
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+TABLING  T EY1 - B AH0 L - IH0 NG
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+TABULATED  T AE1 - B Y AH0 - L EY2 - T IH0 D
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+TABULATION  T AE2 - B Y AH0 - L EY1 - SH AH0 N
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+TABULATURE  T AE1 - B Y AH0 - L AH0 - CH ER0
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+TACKS  T AE1 K S
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+TAKINGS  T EY1 - K IH0 NG Z
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+TALAL  T AH0 - L AA1 L
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+TANGE  T AE1 N JH
+TANGEMAN  T EY1 N JH - M AH0 N
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+TANGER  T AE1 - NG ER0
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+TANKE  T AE1 NG K
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+TOWARD(2)  T AO1 R D
+TOWARDS  T AH0 - W AO1 R D Z
+TOWARDS(2)  T AO1 R D Z
+TOWBIN  T OW1 - B IH2 N
+TOWBOAT  T OW1 - B OW2 T
+TOWE  T OW1
+TOWED  T OW1 D
+TOWEL  T AW1 - AH0 L
+TOWEL(2)  T AW1 L
+TOWELING  T AW1 - AH0 L - IH0 NG
+TOWELING(2)  T AW1 - L IH0 NG
+TOWELL  T AA1 - W EH0 L
+TOWELS  T AW1 - AH0 L Z
+TOWELS(2)  T AW1 L Z
+TOWER  T AW1 - ER0
+TOWER'S  T AW1 - ER0 Z
+TOWERED  T AW1 - ER0 D
+TOWERING  T AW1 - ER0 - IH0 NG
+TOWERING(2)  T AW1 - R IH0 NG
+TOWERS  T AW1 - ER0 Z
+TOWERS'  T AW1 - ER0 Z
+TOWERY  T OW0 - ER1 - IY0
+TOWEY  T OW1 - IY0
+TOWING  T OW1 - IH0 NG
+TOWLE  T AW1 L
+TOWLE'S  T AW1 L Z
+TOWLER  T OW1 - L ER0
+TOWLES  T OW1 - AH0 L Z
+TOWN  T AW1 N
+TOWN'S  T AW1 N Z
+TOWNE  T AW1 N
+TOWNER  T AW1 - N ER0
+TOWNERS  T AW1 - N ER0 Z
+TOWNES  T AW1 N Z
+TOWNHOUSE  T AW1 N - HH AW2 S
+TOWNHOUSES  T AW1 N - HH AW2 - S IH0 Z
+TOWNIE  T AW1 - N IY0
+TOWNLEY  T AW1 N - L IY0
+TOWNS  T AW1 N Z
+TOWNSEL  T AW1 N - S AH0 L
+TOWNSELL  T AW1 N - S AH0 L
+TOWNSEND  T AW1 N - Z AH0 N D
+TOWNSEND'S  T AW1 N - Z AH0 N D Z
+TOWNSFOLK  T AW1 N Z - F OW2 K
+TOWNSHEND  T AW1 N - SH EH2 N D
+TOWNSHIP  T AW1 N - SH IH0 P
+TOWNSHIP'S  T AW1 N - SH IH2 P S
+TOWNSHIPS  T AW1 N - SH IH0 P S
+TOWNSLEY  T AW1 N S - L IY0
+TOWNSMAN  T AW1 N Z - M AH0 N
+TOWNSON  T AW1 N - S AH0 N
+TOWNSPEOPLE  T AW1 N Z - P IY2 - P AH0 L
+TOWRY  T AO1 - R IY0
+TOWS  T OW1 Z
+TOWSLEY  T OW1 S - L IY0
+TOWSON  T OW1 - S AH0 N
+TOXIC  T AA1 K - S IH0 K
+TOXICITY  T AA0 K - S IH1 - S AH0 - T IY0
+TOXICOLOGICAL  T AA2 K - S AH0 - K AH0 - L AA1 - JH IH0 - K AH0 L
+TOXICOLOGIST  T AA2 K - S IH0 - K AA1 - L AH0 - JH IH0 S T
+TOXICOLOGISTS  T AA2 K - S IH0 - K AA1 - L AH0 - JH IH0 S T S
+TOXICOLOGISTS(2)  T AA2 K - S IH0 - K AA1 - L AH0 - JH IH0 S S
+TOXICOLOGISTS(3)  T AA2 K - S IH0 - K AA1 - L AH0 - JH IH0 S
+TOXICOLOGY  T AA2 K - S IH0 - K AA1 - L AH0 - JH IY0
+TOXICS  T AA1 K - S IH0 K S
+TOXIN  T AA1 K - S AH0 N
+TOXINS  T AA1 K - S AH0 N Z
+TOY  T OY1
+TOY'S  T OY1 Z
+TOYA  T OY1 - AH0
+TOYAMA  T OW0 - Y AA1 - M AH0
+TOYE  T OY1
+TOYED  T OY1 D
+TOYING  T OY1 - IH0 NG
+TOYKO  T OY1 - K OW0
+TOYMAKER  T OY1 - M EY2 - K ER0
+TOYMAKERS  T OY1 - M EY2 - K ER0 Z
+TOYO  T OW1 - Y OW0
+TOYOBO  T OW0 - Y OW1 - B OW0
+TOYODA  T OW0 - Y OW1 - D AH0
+TOYOO  T OY0 - UW1
+TOYOTA  T OW0 - Y OW1 - T AH0
+TOYOTA'S  T OW0 - Y OW1 - T AH0 Z
+TOYOTAS  T OY2 - OW1 - T AH0 Z
+TOYS  T OY1 Z
+TOYS'  T OY1 Z
+TOYSTORE  T OY1 - S T AO2 R
+TOYSTORES  T OY1 - S T AO2 R Z
+TOZER  T OW1 - Z ER0
+TOZIER  T OW1 - Z IY0 - ER0
+TOZZI  T AA1 - Z IY0
+TRABER  T R EY1 - B ER0
+TRABERT  T R AE1 - B ER0 T
+TRABUCCO  T R AA0 - B UW1 - K OW0
+TRABUE  T R AA1 B - W EH0
+TRAC  T R AE1 K
+TRACE  T R EY1 S
+TRACEABLE  T R EY1 - S AH0 - B AH0 L
+TRACED  T R EY1 S T
+TRACER  T R EY1 - S ER0
+TRACERS  T R EY1 - S ER0 Z
+TRACES  T R EY1 - S AH0 Z
+TRACES(2)  T R EY1 - S IH0 Z
+TRACEY  T R EY1 - S IY0
+TRACHEA  T R EY1 - K IY0 - AH0
+TRACHEAL  T R EY1 - K IY0 - AH0 L
+TRACHEOPHYTE  T R EY1 - K IY0 - AH0 - F AY0 T
+TRACHEOPHYTES  T R EY1 - K IY0 - AH0 - F AY0 T S
+TRACHSEL  T R AE1 K - S AH0 L
+TRACHT  T R AE1 K T
+TRACHTENBERG  T R AE1 K - T AH0 N - B ER0 G
+TRACIE  T R EY1 - S IY0
+TRACINDA  T R AH0 - S IH1 N - D AH0
+TRACINDA'S  T R AH0 - S IH1 N - D AH0 Z
+TRACING  T R EY1 - S IH0 NG
+TRACK  T R AE1 K
+TRACK'S  T R AE1 K S
+TRACKAGE  T R AE1 - K IH0 JH
+TRACKBALL  T R AE1 K - B AO2 L
+TRACKBALLS  T R AE1 K - B AO2 L Z
+TRACKED  T R AE1 K T
+TRACKER  T R AE1 - K ER0
+TRACKERS  T R AE1 - K ER0 Z
+TRACKING  T R AE1 - K IH0 NG
+TRACKS  T R AE1 K S
+TRACOR  T R EY1 - S ER0
+TRACOR(2)  T R EH1 - K ER0
+TRACOR(3)  T R EY1 - K AO2 R
+TRACOR(4)  T R AE1 - K AO2 R
+TRACT  T R AE1 K T
+TRACTABLE  T R AE1 K - T AH0 - B AH0 L
+TRACTEBEL  T R AE1 K - T AH0 - B AH0 L
+TRACTION  T R AE1 K - SH AH0 N
+TRACTOR  T R AE1 K - T ER0
+TRACTORS  T R AE1 K - T ER0 Z
+TRACTS  T R AE1 K T S
+TRACY  T R EY1 - S IY0
+TRACY'S  T R EY1 - S IY0 Z
+TRACZ  T R AA1 CH
+TRACZYK  T R AA1 - CH IH2 K
+TRADABLE  T R EY1 - D AH0 - B AH0 L
+TRADE  T R EY1 D
+TRADE'S  T R EY1 D Z
+TRADEABLE  T R EY1 - D AH0 - B AH0 L
+TRADED  T R EY1 - D IH0 D
+TRADEMARK  T R EY1 D - M AA2 R K
+TRADEMARKED  T R EY1 D - M AA2 R K T
+TRADEMARKS  T R EY1 D - M AA2 R K S
+TRADEOFF  T R EY1 - D AO2 F
+TRADEOFFS  T R EY1 - D AO2 F S
+TRADER  T R EY1 - D ER0
+TRADER'S  T R EY1 - D ER0 Z
+TRADERS  T R EY1 - D ER0 Z
+TRADERS'  T R EY1 - D ER0 Z
+TRADES  T R EY1 D Z
+TRADESMEN  T R EY1 D Z - M AH0 N
+TRADING  T R EY1 - D IH0 NG
+TRADING'S  T R EY1 - D IH0 NG Z
+TRADINGS  T R EY1 - D IH0 NG Z
+TRADITION  T R AH0 - D IH1 - SH AH0 N
+TRADITIONAL  T R AH0 - D IH1 - SH AH0 - N AH0 L
+TRADITIONALIST  T R AH0 - D IH1 - SH AH0 N - AH0 - L IH0 S T
+TRADITIONALISTS  T R AH0 - D IH1 SH - N AH0 - L AH0 S T S
+TRADITIONALLY  T R AH0 - D IH1 - SH AH0 N - AH0 - L IY0
+TRADITIONALLY(2)  T R AH0 - D IH1 SH - N AH0 - L IY0
+TRADITIONS  T R AH0 - D IH1 - SH AH0 N Z
+TRAEGER  T R EH1 - G ER0
+TRAER  T R EH1 R
+TRAFALGAR  T R AH0 - F AE1 L - G ER0
+TRAFFIC  T R AE1 - F IH0 K
+TRAFFIC'S  T R AE1 - F IH0 K S
+TRAFFICKER  T R AE1 - F IH0 - K ER0
+TRAFFICKERS  T R AE1 - F IH0 - K ER0 Z
+TRAFFICKING  T R AE1 - F IH0 - K IH0 NG
+TRAFFORD  T R AE1 - F ER0 D
+TRAFICANT  T R AE1 - F IH0 - K AH0 N T
+TRAFICANTE  T R AA0 - F IY0 - K AA1 N - T IY0
+TRAFILLIO  T R AH0 - F IY1 - L IY0 - OW0
+TRAFILLIO'S  T R AH0 - F IY1 - L IY0 - OW0 Z
+TRAFTON  T R AE1 F - T AH0 N
+TRAGEDIES  T R AE1 - JH AH0 - D IY0 Z
+TRAGEDY  T R AE1 - JH AH0 - D IY0
+TRAGER  T R EY1 - G ER0
+TRAGESER  T R AE1 - G IY0 - Z ER0
+TRAGIC  T R AE1 - JH IH0 K
+TRAGICALLY  T R AE1 - JH IH0 K - L IY0
+TRAGICOMIC  T R AE2 - JH IH0 - K AA1 - M IH0 K
+TRAGOS  T R AE1 - G OW0 Z
+TRAHAN  T R AE1 - HH AH0 N
+TRAHERN  T R AE1 - HH ER0 N
+TRAIL  T R EY1 L
+TRAILBLAZER  T R EY1 L - B L EY2 - Z ER0
+TRAILBLAZERS  T R EY1 L - B L EY2 - Z ER0 Z
+TRAILED  T R EY1 L D
+TRAILER  T R EY1 - L ER0
+TRAILERS  T R EY1 - L ER0 Z
+TRAILHEAD  T R EY1 L - HH EH2 D
+TRAILING  T R EY1 - L IH0 NG
+TRAILS  T R EY1 L Z
+TRAILS'  T R EY1 L Z
+TRAILWAYS  T R EY1 L - W EY2 Z
+TRAILWAYS'  T R EY1 L - W EY2 Z
+TRAIN  T R EY1 N
+TRAIN'S  T R EY1 N Z
+TRAINA  T R EY1 - N AH0
+TRAINABLE  T R EY1 - N AH0 - B AH0 L
+TRAINED  T R EY1 N D
+TRAINEE  T R EY1 - N IY1
+TRAINEES  T R EY1 - N IY1 Z
+TRAINER  T R EY1 - N ER0
+TRAINERS  T R EY1 - N ER0 Z
+TRAINING  T R EY1 - N IH0 NG
+TRAINMEN  T R EY1 N - M AH0 N
+TRAINOR  T R EY1 - N ER0
+TRAINS  T R EY1 N Z
+TRAIPSE  T R EY1 P S
+TRAIPSING  T R EY1 P - S IH0 NG
+TRAISTER  T R EY1 - S T ER0
+TRAIT  T R EY1 T
+TRAITOR  T R EY1 - T ER0
+TRAITOROUS  T R EY1 - T ER0 - AH0 S
+TRAITORS  T R EY1 - T ER0 Z
+TRAITS  T R EY1 T S
+TRAJAN  T R EY1 - JH AH0 N
+TRAJAN'S  T R EY1 - JH AH0 N Z
+TRAJECTORY  T R AH0 - JH EH1 K - T ER0 - IY0
+TRAK  T R AE1 K
+TRAKAS  T R AA1 - K AH0 Z
+TRAM  T R AE1 M
+TRAMBLE  T R AE1 M - B AH0 L
+TRAMCO  T R AE1 M - K OW0
+TRAMEL  T R AE1 - M AH0 L
+TRAMELL  T R AA0 - M EY1 L
+TRAMIEL  T R AE1 - M IY0 - AH0 L
+TRAMMEL  T R AE1 - M AH0 L
+TRAMMELL  T R AE1 - M AH0 L
+TRAMONTANA  T R AA0 - M OW0 N - T AE1 - N AH0
+TRAMONTANO  T R AA0 - M OW0 N - T AA1 - N OW0
+TRAMONTE  T R AA0 - M OW1 N - T IY0
+TRAMONTIN  T R AH0 - M AA1 N - T IH0 N
+TRAMP  T R AE1 M P
+TRAMPE  T R AE1 M P
+TRAMPING  T R AE1 M - P IH0 NG
+TRAMPLE  T R AE1 M - P AH0 L
+TRAMPLED  T R AE1 M - P AH0 L D
+TRAMPLES  T R AE1 M - P AH0 L Z
+TRAMPLING  T R AE1 M - P L IH0 NG
+TRAMPOLINE  T R AE2 M - P AH0 - L IY1 N
+TRAMPS  T R AE1 M P Z
+TRAMS  T R AE1 M Z
+TRAN  T R AE1 N
+TRANBERG  T R AE1 N - B ER0 G
+TRANCE  T R AE1 N S
+TRANCHE  T R AE1 N CH
+TRANCHES  T R AE1 N - CH EH0 Z
+TRANCHINA  T R AA0 N - K IY1 - N AH0
+TRANE  T R EY1 N
+TRANG  T R AE1 NG
+TRANI  T R AA1 - N IY0
+TRANQUIL  T R AE1 NG - K W AH0 L
+TRANQUIL(2)  T R AE1 NG - K W IH0 L
+TRANQUILITY  T R AE0 NG - K W IH1 - L IH0 - T IY0
+TRANQUILIZE  T R AE1 NG - K W AH0 - L AY2 Z
+TRANQUILIZE(2)  T R AE1 NG - K W AH0 - L AY2 Z
+TRANQUILIZER  T R AE1 NG - K W AH0 - L AY2 - Z ER0
+TRANQUILIZERS  T R AE1 NG - K W AH0 - L AY2 - Z ER0 Z
+TRANQUILIZING  T R AE1 NG - K W AH0 - L AY2 - Z IH0 NG
+TRANS  T R AE1 N Z
+TRANSACT  T R AE0 N - Z AE1 K T
+TRANSACTED  T R AE0 N - S AE1 K - T IH0 D
+TRANSACTED(2)  T R AE0 N - Z AE1 K - T IH0 D
+TRANSACTION  T R AE0 N - Z AE1 K - SH AH0 N
+TRANSACTION'S  T R AE0 N - Z AE1 K - SH AH0 N Z
+TRANSACTIONS  T R AE0 N - Z AE1 K - SH AH0 N Z
+TRANSAFRICA  T R AE2 N - Z AE1 - F R IH0 - K AH0
+TRANSALASKA  T R AE2 N - Z AH0 - L AE1 S - K AH0
+TRANSALTA  T R AE2 N - Z AO1 L - T AH0
+TRANSAMERICA  T R AE2 N - S AH0 - M EH1 - R IH0 - K AH0
+TRANSAMERICA'S  T R AE2 N - Z AH0 - M EH1 - R IH0 - K AH0 Z
+TRANSAMERICAN  T R AE2 N - Z AH0 - M EH1 - R IH0 - K AH0 N
+TRANSAMERICAN'S  T R AE2 N - Z AH0 - M EH1 - R IH0 - K AH0 N Z
+TRANSATLANTIC  T R AE2 N Z - AH0 T - L AE1 N - T IH0 K
+TRANSATLANTIC(2)  T R AE2 N Z - AH0 T - L AE1 - N IH0 K
+TRANSCANADA  T R AE2 N Z - K AE1 - N AH0 - T AH0
+TRANSCANADA'S  T R AE2 N Z - K AE1 - N AH0 - D AH0 Z
+TRANSCAPITAL  T R AE2 N Z - K AE1 - P IH0 - T AH0 L
+TRANSCEND  T R AE0 N - S EH1 N D
+TRANSCENDED  T R AE0 N - S EH1 N - D IH0 D
+TRANSCENDENCE  T R AE0 N - S EH1 N - D AH0 N S
+TRANSCENDENT  T R AE0 N - S EH1 N - D AH0 N T
+TRANSCENDENTAL  T R AE2 N - S AH0 N - D EH1 N - T AH0 L
+TRANSCENDENTAL(2)  T R AE2 N - S AH0 N - D EH1 - N AH0 L
+TRANSCENDING  T R AE0 N - S EH1 N - D IH0 NG
+TRANSCENDS  T R AE0 N - S EH1 N D Z
+TRANSCHANNEL  T R AH1 N S - CH AE1 - N AH0 L
+TRANSCHANNEL'S  T R AH1 N S - CH AE1 - N AH0 L Z
+TRANSCISCO  T R AE2 N - S IH1 - S K OW0
+TRANSCO  T R AE1 N - S K OW0
+TRANSCON  T R AE1 N Z - K AA0 N
+TRANSCONTINENTAL  T R AE2 N Z - K AA2 N - T IH0 - N EH1 N - T AH0 L
+TRANSCONTINENTAL'S  T R AE2 N Z - K AA2 N - T IH0 - N EH1 N - T AH0 L Z
+TRANSCONTINENTAL'S(2)  T R AE2 N Z - K AA2 - N IH0 - N EH1 N - T AH0 L Z
+TRANSCONTINENTAL'S(3)  T R AE2 N Z - K AA2 N - T IH0 - N EH1 - N AH0 L Z
+TRANSCONTINENTAL'S(4)  T R AE2 N Z - K AA2 - N IH0 - N EH1 - N AH0 L Z
+TRANSCONTINENTAL(2)  T R AE2 N Z - K AA2 - N IH0 - N EH1 N - T AH0 L
+TRANSCONTINENTAL(3)  T R AE2 N Z - K AA2 N - T IH0 - N EH1 - N AH0 L
+TRANSCONTINENTAL(4)  T R AE2 N Z - K AA2 - N IH0 - N EH1 - N AH0 L
+TRANSCRIBE  T R AE0 N - S K R AY1 B
+TRANSCRIBED  T R AE0 N - S K R AY1 B D
+TRANSCRIBER  T R AE0 N - S K R AY1 - B ER0
+TRANSCRIBERS  T R AE0 N - S K R AY1 - B ER0 Z
+TRANSCRIBES  T R AE0 N - S K R AY1 B Z
+TRANSCRIBING  T R AE0 N - S K R AY1 - B IH0 NG
+TRANSCRIPT  T R AE1 N - S K R IH2 P T
+TRANSCRIPTION  T R AE2 N - S K R IH1 P - SH AH0 N
+TRANSCRIPTIONS  T R AE2 N - S K R IH1 P - SH AH0 N Z
+TRANSCRIPTS  T R AE1 N - S K R IH2 P T S
+TRANSDUCER  T R AE0 N S - D UW1 - S ER0
+TRANSDUCERS  T R AE0 N S - D UW1 - S ER0 Z
+TRANSECT  T R AE1 N - S EH2 K T
+TRANSECTED  T R AE1 N - S EH2 K - T IH0 D
+TRANSECTION  T R AE1 N - S EH2 K - SH AH0 N
+TRANSFER  T R AE0 N S - F ER1
+TRANSFER(2)  T R AE1 N S - F ER0
+TRANSFERABILITY  T R AE2 N S - F ER0 - AH0 - B IH1 - L IH0 - T IY0
+TRANSFERABLE  T R AE0 N S - F ER1 - AH0 - B AH0 L
+TRANSFERED  T R AE0 N S - F ER1 D
+TRANSFERENCE  T R AE0 N S - F ER1 - AH0 N S
+TRANSFERING  T R AE0 N S - F ER1 - IH0 NG
+TRANSFERRABLE  T R AE2 N S - F ER1 - AH0 - B AH0 L
+TRANSFERRED  T R AE0 N S - F ER1 D
+TRANSFERRED(2)  T R AE1 N S - F ER0 D
+TRANSFERRING  T R AE0 N S - F ER1 - IH0 NG
+TRANSFERS  T R AE0 N S - F ER1 Z
+TRANSFERS(2)  T R AE1 N S - F ER0 Z
+TRANSFIX  T R AE0 N S - F IH1 K S
+TRANSFIXED  T R AE0 N S - F IH1 K S T
+TRANSFORM  T R AE0 N S - F AO1 R M
+TRANSFORM(2)  T R AE1 N S - F AO0 R M
+TRANSFORMATION  T R AE2 N S - F ER0 - M EY1 - SH AH0 N
+TRANSFORMATIONAL  T R AE2 N S - F ER0 - M EY1 - SH AH0 - N AH0 L
+TRANSFORMATIONS  T R AE2 N S - F ER0 - M EY1 - SH AH0 N Z
+TRANSFORMED  T R AE0 N S - F AO1 R M D
+TRANSFORMER  T R AE0 N S - F AO1 R - M ER0
+TRANSFORMERS  T R AE0 N S - F AO1 R - M ER0 Z
+TRANSFORMING  T R AE0 N S - F AO1 R - M IH0 NG
+TRANSFORMS  T R AE0 N S - F AO1 R M Z
+TRANSFUSE  T R AE0 N S - F Y UW1 Z
+TRANSFUSED  T R AE0 N S - F Y UW1 Z D
+TRANSFUSION  T R AE0 N S - F Y UW1 - ZH AH0 N
+TRANSFUSIONS  T R AE0 N S - F Y UW1 - ZH AH0 N Z
+TRANSGENIC  T R AE2 N Z - JH EH1 - N IH0 K
+TRANSGRESS  T R AE0 N Z - G R EH1 S
+TRANSGRESSED  T R AE0 N Z - G R EH1 S T
+TRANSGRESSION  T R AE0 N Z - G R EH1 - SH AH0 N
+TRANSGRESSIONS  T R AE0 N Z - G R EH1 - SH AH0 N Z
+TRANSGRESSOR  T R AE0 N Z - G R EH1 - S ER0
+TRANSIENCE  T R AE1 N - Z IY0 - AH0 N S
+TRANSIENT  T R AE1 N - ZH AH0 N T
+TRANSIENTS  T R AE1 N - Z IY0 - AH0 N T S
+TRANSILLUMINATION  T R AE2 N - Z AH0 - L UW2 - M AH0 - N EY1 - SH AH0 N
+TRANSIMAGE  T R AE2 N - Z IH1 - M IH0 JH
+TRANSISTOR  T R AE0 N - Z IH1 - S T ER0
+TRANSISTORS  T R AE0 N - Z IH1 - S T ER0 Z
+TRANSIT  T R AE1 N - Z AH0 T
+TRANSITION  T R AE0 N - Z IH1 - SH AH0 N
+TRANSITIONAL  T R AE0 N - S IH1 - SH AH0 - N AH0 L
+TRANSITIONAL(2)  T R AE0 N - Z IH1 - SH AH0 - N AH0 L
+TRANSITIONING  T R AE0 N - Z IH1 - SH AH0 N - IH0 NG
+TRANSITIONS  T R AE0 N - Z IH1 - SH AH0 N Z
+TRANSITORY  T R AE1 N - Z AH0 - T AO2 - R IY0
+TRANSKEI  T R AE1 N Z - K EY2
+TRANSLATE  T R AE0 N Z - L EY1 T
+TRANSLATE(2)  T R AE0 N S - L EY1 T
+TRANSLATED  T R AE0 N Z - L EY1 - T AH0 D
+TRANSLATED(2)  T R AE0 N S - L EY1 - T IH0 D
+TRANSLATES  T R AE0 N Z - L EY1 T S
+TRANSLATES(2)  T R AE1 N S - L EY2 T S
+TRANSLATING  T R AE0 N Z - L EY1 - T IH0 NG
+TRANSLATING(2)  T R AE1 N S - L EY2 - T IH0 NG
+TRANSLATION  T R AE0 N Z - L EY1 - SH AH0 N
+TRANSLATION(2)  T R AE0 N S - L EY1 - SH AH0 N
+TRANSLATIONS  T R AE0 N Z - L EY1 - SH AH0 N Z
+TRANSLATIONS(2)  T R AE0 N S - L EY1 - SH AH0 N Z
+TRANSLATOR  T R AE0 N S - L EY1 - T ER0
+TRANSLATOR(2)  T R AE0 N Z - L EY1 - T ER0
+TRANSLATORS  T R AE0 N S - L EY1 - T ER0 Z
+TRANSLATORS(2)  T R AE0 N Z - L EY1 - T ER0 Z
+TRANSLOGIC  T R AE2 N Z - L AA1 - JH IH0 K
+TRANSLUCENT  T R AE0 N S - L UW1 - S AH0 N T
+TRANSMARK  T R AE1 N Z - M AA2 R K
+TRANSMEDIA  T R AE2 N Z - M IY1 - D IY0 - AH0
+TRANSMISSION  T R AE0 N S - M IH1 - SH AH0 N
+TRANSMISSION(2)  T R AE0 N Z - M IH1 - SH AH0 N
+TRANSMISSIONS  T R AE0 N Z - M IH1 - SH AH0 N Z
+TRANSMIT  T R AE0 N Z - M IH1 T
+TRANSMITS  T R AE0 N Z - M IH1 T S
+TRANSMITTABLE  T R AE0 N Z - M IH1 - T AH0 - B AH0 L
+TRANSMITTAL  T R AE0 N S - M IH1 - T AH0 L
+TRANSMITTED  T R AE0 N S - M IH1 - T IH0 D
+TRANSMITTED(2)  T R AE0 N Z - M IH1 - T AH0 D
+TRANSMITTER  T R AE0 N S - M IH1 - T ER0
+TRANSMITTERS  T R AE0 N S - M IH1 - T ER0 Z
+TRANSMITTING  T R AE0 N S - M IH1 - T IH0 NG
+TRANSNATIONAL  T R AE0 N S - N AE1 - SH AH0 - N AH0 L
+TRANSOCEANIC  T R AE2 N Z - OW0 - SH IY0 - AE1 - N IH0 K
+TRANSOHIO  T R AE2 N Z - OW0 - HH AY1 - OW0
+TRANSOM  T R AE1 N - S AH0 M
+TRANSOMS  T R AE1 N - S AH0 M Z
+TRANSOU  T R AE1 N - Z UW2
+TRANSPAC  T R AE1 N Z - P AE2 K
+TRANSPACIFIC  T R AE2 N S - P AH0 - S IH1 - F IH0 K
+TRANSPARENCIES  T R AE0 N - S P EH1 - R AH0 N - S IY0 Z
+TRANSPARENCY  T R AE0 N - S P EH1 - R AH0 N - S IY0
+TRANSPARENT  T R AE0 N - S P EH1 - R AH0 N T
+TRANSPARENTLY  T R AE0 N - S P EH1 - R AH0 N T - L IY0
+TRANSPARK  T R AE1 N S - P AA1 R K
+TRANSPIRE  T R AE0 N - S P AY1 - ER0
+TRANSPIRED  T R AE0 N - S P AY1 - ER0 D
+TRANSPIRES  T R AE0 N - S P AY1 - ER0 Z
+TRANSPIRING  T R AE0 N - S P AY1 - ER0 - IH0 NG
+TRANSPLANT  T R AE0 N S - P L AE1 N T
+TRANSPLANTATION  T R AE2 N Z - P L AE0 N - T EY1 - SH AH0 N
+TRANSPLANTED  T R AE0 N S - P L AE1 N - T IH0 D
+TRANSPLANTING  T R AE0 N S - P L AE1 N - T IH0 NG
+TRANSPLANTS  T R AE0 N S - P L AE1 N T S
+TRANSPONDER  T R AE0 N S - P AA1 N - D ER0
+TRANSPONDERS  T R AE0 N S - P AA1 N - D ER0 Z
+TRANSPORT  T R AE0 N S - P AO1 R T
+TRANSPORT(2)  T R AE1 N S - P AO0 R T
+TRANSPORTABLE  T R AE0 N S - P AO1 R - T AH0 - B AH0 L
+TRANSPORTATION  T R AE2 N S - P ER0 - T EY1 - SH AH0 N
+TRANSPORTATION'S  T R AE2 N S - P ER0 - T EY1 - SH AH0 N Z
+TRANSPORTED  T R AE0 N S - P AO1 R - T AH0 D
+TRANSPORTER  T R AE0 N S - P AO1 R - T ER0
+TRANSPORTERS  T R AE0 N S - P AO1 R - T ER0 Z
+TRANSPORTING  T R AE0 N S - P AO1 R - T IH0 NG
+TRANSPORTS  T R AE0 N S - P AO1 R T S
+TRANSPORTS(2)  T R AE1 N S - P AO0 R T S
+TRANSPOSE  T R AE0 N S - P OW1 Z
+TRANSPOSED  T R AE0 N S - P OW1 Z D
+TRANSRACIAL  T R AE2 N Z - R EY1 - SH AH0 L
+TRANSRAPID  T R AE1 N Z - R AE1 - P IH0 D
+TRANSSEXUAL  T R AE0 N - S EH1 K - SH Y UW0 - AH0 L
+TRANSSEXUALS  T R AE0 N - S EH1 K - SH Y UW0 - AH0 L Z
+TRANSTAR  T R AE0 N S - T AA1 R
+TRANSTECHNOLOGY  T R AE2 N Z - T AH0 K - N AA1 - L AH0 - JH IY0
+TRANSTECTOR  T R AE2 N Z - T EH1 K - T ER0
+TRANSUE  T R AE1 N - Z UW0
+TRANSVAAL  T R AE0 N Z - V AA1 L
+TRANSVERSE  T R AE0 N Z - V ER1 S
+TRANSVESTITE  T R AE0 N Z - V EH1 - S T AY0 T
+TRANSVESTITES  T R AE0 N Z - V EH1 - S T AY0 T S
+TRANSWAY  T R AE1 N Z - W EY2
+TRANSWESTERN  T R AE2 N Z - W EH1 - S T ER0 N
+TRANSWORLD  T R AE0 N S - W ER1 L D
+TRANSYLVANIA  T R AE2 N - Z IY0 L - V EY1 - N IY0 - AH0
+TRANSYLVANIA(2)  T R AE2 N - S IH0 L - V EY1 - N Y AH0
+TRANT  T R AE1 N T
+TRANTER  T R AE1 N - T ER0
+TRANTHAM  T R AE1 N - TH AH0 M
+TRANUM  T R AE1 - N AH0 M
+TRANZONIC  T R AE0 N - Z AA1 - N IH0 K
+TRAP  T R AE1 P
+TRAPANI  T R AA0 - P AA1 - N IY0
+TRAPASSO  T R AA0 - P AA1 - S OW0
+TRAPELO  T R AH0 - P EH1 - L OW0
+TRAPEZE  T R AH0 - P IY1 Z
+TRAPHAGEN  T R AE1 - F AH0 - G AH0 N
+TRAPNELL  T R AE1 P - N AH0 L
+TRAPP  T R AE1 P
+TRAPPE  T R AE1 P
+TRAPPED  T R AE1 P T
+TRAPPERS  T R AE1 - P ER0 Z
+TRAPPING  T R AE1 - P IH0 NG
+TRAPPINGS  T R AE1 - P IH0 NG Z
+TRAPPIST  T R AE1 - P IH0 S T
+TRAPS  T R AE1 P S
+TRASH  T R AE1 SH
+TRASHED  T R AE1 SH T
+TRASHES  T R AE1 - SH IH0 Z
+TRASHING  T R AE1 - SH IH0 NG
+TRASHY  T R AE1 - SH IY0
+TRASK  T R AE1 S K
+TRAUB  T R AO1 B
+TRAUDT  T R AO1 D T
+TRAUGER  T R AW1 - G ER0
+TRAUGH  T R AO1
+TRAUGHBER  T R AO1 - B ER0
+TRAUGOTT  T R AW1 - G AH0 T
+TRAUM  T R AO1 M
+TRAUMA  T R AO1 - M AH0
+TRAUMAS  T R AO1 - M AH0 Z
+TRAUMATIC  T R AO0 - M AE1 - T IH0 K
+TRAUMATIZE  T R AO1 - M AH0 - T AY2 Z
+TRAUMATIZED  T R AO1 - M AH0 - T AY2 Z D
+TRAUSCH  T R AW1 SH
+TRAUT  T R AO1 T
+TRAUTH  T R AO1 TH
+TRAUTMAN  T R AW1 T - M AH0 N
+TRAUTMANN  T R AW1 T - M AH0 N
+TRAUTNER  T R AW1 T - N ER0
+TRAUTWEIN  T R AW1 T - W AY2 N
+TRAVAGLINI  T R AA0 - V AA0 G - L IY1 - N IY0
+TRAVAIL  T R AH0 - V EY1 L
+TRAVAILS  T R AH0 - V EY1 L Z
+TRAVEL  T R AE1 - V AH0 L
+TRAVELDAY  T R AE1 - V AH0 L - D EY2
+TRAVELDAYS  T R AE1 - V AH0 L - D EY2 Z
+TRAVELED  T R AE1 - V AH0 L D
+TRAVELER  T R AE1 - V AH0 - L ER0
+TRAVELER'S  T R AE1 - V AH0 - L ER0 Z
+TRAVELER(2)  T R AE1 V - L ER0
+TRAVELERS  T R AE1 - V AH0 - L ER0 Z
+TRAVELERS'  T R AE1 - V AH0 - L ER0 Z
+TRAVELERS(2)  T R AE1 V - L ER0 Z
+TRAVELGATE  T R AE1 - V AH0 L - G EY2 T
+TRAVELING  T R AE1 - V AH0 L - IH0 NG
+TRAVELING(2)  T R AE1 - V L IH0 NG
+TRAVELLED  T R AE1 - V AH0 L D
+TRAVELLER  T R AE1 - V AH0 - L ER0
+TRAVELLERS  T R AE1 - V AH0 - L ER0 Z
+TRAVELLING  T R AE1 - V AH0 L - IH0 NG
+TRAVELLING(2)  T R AE1 - V L IH0 NG
+TRAVELODGE  T R AE1 - V AH0 - L AA1 JH
+TRAVELOGUE  T R AE1 - V AH0 - L AO2 G
+TRAVELS  T R AE1 - V AH0 L Z
+TRAVELSTEAD  T R AE1 - V AH0 L - S T EH2 D
+TRAVENOL  T R AE1 - V AH0 - N AH0 L
+TRAVER  T R EY1 - V ER0
+TRAVERS  T R AE1 - V ER0 Z
+TRAVERSE  T R AE1 - V ER0 S
+TRAVERSE(2)  T R AH0 - V ER1 S
+TRAVERSED  T R AE1 - V ER0 S T
+TRAVERSED(2)  T R AH0 - V ER1 S T
+TRAVERSING  T R AH0 - V ER1 - S IH0 NG
+TRAVERSO  T R AA0 - V EH1 R - S OW0
+TRAVESTIES  T R AE1 - V AH0 - S T IY0 Z
+TRAVESTY  T R AE1 - V AH0 - S T IY0
+TRAVIATA  T R AA0 - V IY0 - AA1 - T AH0
+TRAVIESO  T R AA0 - V IY1 - S OW0
+TRAVIS  T R AE1 - V IH0 S
+TRAVISANO  T R AE2 - V IH0 - S AA1 - N OW0
+TRAVNIK  T R AE1 V - N IH0 K
+TRAVOLTA  T R AH0 - V OW1 L - T AH0
+TRAVOLTA'S  T R AH0 - V OW1 L - T AH0 Z
+TRAVOLTAS  T R AH0 - V OW1 L - T AH0 Z
+TRAWEEK  T R AO1 - IY2 K
+TRAWICK  T R AO1 - IH0 K
+TRAWLER  T R AO1 - L ER0
+TRAWLERS  T R AO1 - L ER0 Z
+TRAX  T R AE1 K S
+TRAXLER  T R AE1 K S - L ER0
+TRAY  T R EY1
+TRAYER  T R EY1 - ER0
+TRAYLOR  T R EY1 - L ER0
+TRAYNHAM  T R EY1 N - HH AH0 M
+TRAYNOR  T R EY1 - N ER0
+TRAYS  T R EY1 Z
+TRAYWICK  T R EY1 - W IH2 K
+TRBOVICH  T ER0 - B AA1 - V IH0 CH
+TREACHEROUS  T R EH1 - CH ER0 - AH0 S
+TREACHERY  T R EH1 - CH ER0 - IY0
+TREACY  T R EY1 - S IY0
+TREAD  T R EH1 D
+TREADAWAY  T R EH1 D - AH0 - W EY2
+TREADING  T R EH1 - D IH0 NG
+TREADMILL  T R EH1 D - M IH2 L
+TREADMILLS  T R EH1 D - M IH2 L Z
+TREADS  T R EH1 D Z
+TREADWAY  T R EH1 D - W EY2
+TREADWELL  T R EH1 D - W EH2 L
+TREADWHEEL  T R EH1 D - W IY2 L
+TREANOR  T R IY1 - N ER0
+TREASE  T R IY1 Z
+TREASON  T R IY1 - Z AH0 N
+TREASTER  T R IY1 - S T ER0
+TREASURE  T R EH1 - ZH ER0
+TREASURED  T R EH1 - ZH ER0 D
+TREASURER  T R EH1 - ZH ER0 - ER0
+TREASURER'S  T R EH1 - ZH ER0 - ER0 Z
+TREASURERS  T R EH1 - ZH ER0 - ER0 Z
+TREASURES  T R EH1 - ZH ER0 Z
+TREASURIES  T R EH1 - ZH ER0 - IY0 Z
+TREASURY  T R EH1 - ZH ER0 - IY0
+TREASURY'S  T R EH1 - ZH ER0 - IY0 Z
+TREASURYS  T R EH1 - ZH ER0 - IY0 Z
+TREAT  T R IY1 T
+TREATABLE  T R IY1 - T AH0 - B AH0 L
+TREATED  T R IY1 - T AH0 D
+TREATED(2)  T R IY1 - T IH0 D
+TREATER  T R IY1 - T ER0
+TREATERS  T R IY1 - T ER0 Z
+TREATIES  T R IY1 - T IY0 Z
+TREATING  T R IY1 - T IH0 NG
+TREATISE  T R IY1 - T AH0 S
+TREATISES  T R IY1 - T AH0 - S AH0 Z
+TREATMENT  T R IY1 T - M AH0 N T
+TREATMENTS  T R IY1 T - M AH0 N T S
+TREATS  T R IY1 T S
+TREATY  T R IY1 - T IY0
+TREATY'S  T R IY1 - T IY0 Z
+TREBILCOCK  T R IH0 - B IH1 L - K AH0 K
+TREBLE  T R EH1 - B AH0 L
+TREBLED  T R EH1 - B AH0 L D
+TREBLINKA  T R EH0 B - L IH1 NG - K ER0
+TREBLINKA(2)  T R EH0 B - L IH1 NG - K AH0
+TRECKER  T R EH1 - K ER0
+TREDER  T R IY1 - D ER0
+TREDWAY  T R EH1 D - W EY2
+TREE  T R IY1
+TREECE  T R IY1 S
+TREELESS  T R IY1 - L AH0 S
+TREEN  T R IY1 N
+TREES  T R IY1 Z
+TREESE  T R IY1 Z
+TREESH  T R IY1 SH
+TREESWEET  T R IY1 S - W IY2 T
+TREETOP  T R IY1 - T AO2 P
+TREETOPS  T R IY1 - T AO2 P S
+TREFETHEN  T R EH1 - F IH0 - TH AH0 N
+TREFGARNE  T R EH1 F - G AA0 R N
+TREFRY  T R EH1 - F R IY0
+TREFZ  T R EH1 F Z
+TREGLIA  T R EH1 G - L IY0 - AH0
+TREGO  T R EH1 - G OW0
+TREGONING  T R EH1 - G AH0 - N IH0 NG
+TREGRE  T R EH1 - G ER0
+TREGURTHA  T R EH0 - G ER1 - TH AH0
+TREHARNE  T R EH1 - HH AA0 R N
+TREIBER  T R AY1 - B ER0
+TREICHEL  T R AY1 - K AH0
+TREICHLER  T R AY1 - K AH0 - L ER0
+TREICHLER(2)  T R AY1 - K L ER0
+TREINEN  T R AY1 - N AH0 N
+TREJO  T R EY1 - Y OW0
+TREK  T R EH1 K
+TREKKED  T R EH1 K T
+TREKKING  T R EH1 - K IH0 NG
+TREKS  T R EH1 K S
+TRELA  T R EH1 - L AH0
+TRELLA  T R EH1 - L AH0
+TRELLEBORG  T R EH1 - L AH0 - B AO0 R G
+TRELLEBORG'S  T R EH1 - L AH0 - B AO0 R G Z
+TRELLIS  T R EH1 - L AH0 S
+TRELOAR  T R EH1 - L AO0 R
+TREMAIN  T R EH1 - M AY0 N
+TREMAINE  T R IH0 - M EY1 N
+TREMAYNE  T R EH1 - M EY0 N
+TREMBATH  T R EH1 M - B AH0 TH
+TREMBLAY  T R EH1 M - B L EY0
+TREMBLE  T R EH1 M - B AH0 L
+TREMBLED  T R EH1 M - B AH0 L D
+TREMBLEY  T R EH1 M - B L IY0
+TREMBLING  T R EH1 M - B AH0 L - IH0 NG
+TREMBLING(2)  T R EH1 M - B L IH0 NG
+TREMBLY  T R EH1 M - B L IY0
+TREMEL  T R EH1 - M AH0 L
+TREMENDOUS  T R AH0 - M EH1 N - D AH0 S
+TREMENDOUS(2)  T R IH0 - M EH1 N - D AH0 S
+TREMENDOUSLY  T R AH0 - M EH1 N - D AH0 S - L IY0
+TREMENDOUSLY(2)  T R IH0 - M EH1 N - D AH0 S - L IY0
+TREMENS  T R EH1 - M AH0 N Z
+TREML  T R EH1 - M AH0 L
+TREMMEL  T R EH1 - M AH0 L
+TREMONT  T R EH1 - M AH0 N T
+TREMOR  T R EH1 - M ER0
+TREMORS  T R EH1 - M ER0 Z
+TREMPER  T R EH1 M - P ER0
+TREMULOUS  T R EH1 - M Y AH0 - L AH0 S
+TREMULOUSLY  T R EH1 - M Y AH0 - L AH0 S - L IY0
+TRENARY  T R EH1 - N EH0 - R IY0
+TRENCH  T R EH1 N CH
+TRENCHANT  T R EH1 N - CH AH0 N T
+TRENCHARD  T R EH1 NG - K ER0 D
+TRENCHER  T R EH1 N - CH ER0
+TRENCHES  T R EH1 N - CH IH0 Z
+TREND  T R EH1 N D
+TRENDED  T R EH1 N - D IH0 D
+TRENDIER  T R EH1 N - D Y ER0
+TRENDIER(2)  T R EH1 N - D IY0 - ER0
+TRENDIEST  T R EH0 N - D IY1 S T
+TRENDIEST(2)  T R EH1 N - D IY0 - AH0 S T
+TRENDING  T R EH1 N - D IH0 NG
+TRENDLESS  T R EH1 N D - L AH0 S
+TRENDLINE  T R EH1 N D - L AY2 N
+TRENDS  T R EH1 N D Z
+TRENDS(2)  T R EH1 N Z
+TRENDSETTER  T R EH1 N D - S EH2 - T ER0
+TRENDY  T R EH1 N - D IY0
+TRENHOLM  T R EH1 N - HH OW2 L M
+TRENKAMP  T R EH1 N - K AE2 M P
+TRENKLE  T R EH1 NG - K AH0 L
+TRENT  T R EH1 N T
+TRENT'S  T R EH1 N T S
+TRENTE-ET-QUARANTE  T R EY1 N - T EY0 - K W AA2 - R EH1 N - T EY0
+TRENTHAM  T R EH1 N - TH AH0 M
+TRENTMAN  T R EH1 N T - M AH0 N
+TRENTON  T R EH1 N - T AH0 N
+TRENTON'S  T R EH1 N - T AH0 N Z
+TREON  T R IY1 - AH0 N
+TREPAGNIER  T R EH1 - P AH0 G - N IY0 - ER0
+TREPANIER  T R EH1 - P AH0 - N IY0 - ER0
+TREPIDATION  T R EH2 - P IH0 - D EY1 - SH AH0 N
+TREPPEL  T R EH1 - P AH0 L
+TREPTOW  T R EH1 P - T OW0
+TRESCH  T R EH1 SH
+TRESCOTT  T R EH1 S - K AH0 T
+TRESPASS  T R EH1 S - P AE2 S
+TRESPASS(2)  T R EH1 S - P AH0 S
+TRESPASSING  T R EH1 S - P AE2 - S IH0 NG
+TRESPASSING(2)  T R EH1 S - P AH0 - S IH0 NG
+TRESS  T R EH1 S
+TRESSEL  T R EH1 - S AH0 L
+TRESSES  T R EH1 - S IH0 Z
+TRESSLER  T R EH1 S - L ER0
+TREST  T R EH1 S T
+TRESTER  T R EH1 - S T ER0
+TRESTLE  T R EH1 - S AH0 L
+TRETHEWEY  T R EH1 - TH Y UW0 - IY0
+TRETINOIN  T R EH1 - T IH0 - N OY2 N
+TRETTEL  T R EH1 - T AH0 L
+TRETTER  T R EH1 - T ER0
+TRETTIN  T R EH1 - T IH0 N
+TREU  T R UW1
+TREUHAND  T R UW1 - HH AE2 N D
+TREUHANDANSTALT  T R UW2 - HH AE1 N - D AH0 N - S T AA2 L T
+TREURNICHT  T R UW1 R - N IH0 K T
+TREVATHAN  T R EH1 - V AH0 - TH AH0 N
+TREVELYAN  T R AH0 - V EH1 L - Y AH0 N
+TREVINO  T R AH0 - V IY1 - N OW0
+TREVISO  T R EH0 - V IY1 - S OW0
+TREVIZO  T R EH0 - V IY1 - Z OW0
+TREVOR  T R EH1 - V ER0
+TREW  T R UW1
+TREXLER  T R EH1 K S - L ER0
+TREY  T R EY1
+TREYBIG  T R EY1 - B IH0 G
+TREZISE  T R EH1 - Z AY0 Z
+TREZZA  T R EH1 - Z AH0
+TRI  T R AY1
+TRI-STATE  T R AY1 - S T EY1 T
+TRIAD  T R AY1 - AE2 D
+TRIAD'S  T R AY1 - AE2 D Z
+TRIADS  T R AY1 - AE2 D Z
+TRIAGE  T R AY1 - IH0 JH
+TRIAL  T R AY1 - AH0 L
+TRIAL'S  T R AY1 - AH0 L Z
+TRIAL(2)  T R AY1 L
+TRIALS  T R AY1 - AH0 L Z
+TRIALS(2)  T R AY1 L Z
+TRIANA  T R IY0 - AE1 - N AH0
+TRIANGLE  T R AY1 - AE2 NG - G AH0 L
+TRIANGLE'S  T R AY1 - AE2 NG - G AH0 L Z
+TRIANGLES  T R AY1 - AE2 NG - G AH0 L Z
+TRIANGULAR  T R AY0 - AE1 NG - G Y AH0 - L ER0
+TRIANGULATION  T R AY0 - AE2 NG - G Y UW0 - L EY1 - SH AH0 N
+TRIANO  T R IY0 - AA1 - N OW0
+TRIARC  T R AY1 - AA2 R K
+TRIATHLON  T R AY2 - AE1 TH - L AH0 N
+TRIB  T R IH1 B
+TRIBAL  T R AY1 - B AH0 L
+TRIBALISM  T R AY1 - B AH0 - L IH0 Z M
+TRIBALISM(2)  T R AY1 - B AH0 - L IH0 - Z AH0 M
+TRIBASA  T R AY1 - B AE1 - S AH0
+TRIBBETT  T R IH1 - B IH0 T
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+TRIBBLES  T R IH1 - B AH0 L Z
+TRIBBY  T R IH1 - B IY0
+TRIBE  T R AY1 B
+TRIBE'S  T R AY1 B Z
+TRIBECA  T R IH0 - B EH1 - K AH0
+TRIBES  T R AY1 B Z
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+TRIBESMEN  T R AY1 B Z - M IH0 N
+TRIBLE  T R IH1 - B AH0 L
+TRIBOROUGH  T R AY1 - B ER0 - OW0
+TRIBULATION  T R IH2 - B Y AH0 - L EY1 - SH AH0 N
+TRIBULATIONS  T R IH2 - B Y AH0 - L EY1 - SH AH0 N Z
+TRIBULL  T R IH1 - B AH0 L
+TRIBUNAL  T R AH0 - B Y UW1 - N AH0 L
+TRIBUNALS  T R AY2 - B Y UW1 - N AH0 L Z
+TRIBUNE  T R IH1 - B Y UW0 N
+TRIBUNE'S  T R IH1 - B Y UW0 N Z
+TRIBUTARIES  T R IH1 - B Y AH0 - T EH2 - R IY0 Z
+TRIBUTARY  T R IH1 - B Y AH0 - T EH2 - R IY0
+TRIBUTE  T R IH1 - B Y UW0 T
+TRIBUTES  T R IH1 - B Y UW0 T S
+TRICARICO  T R IY0 - K AA0 - R IY1 - K OW0
+TRICE  T R AY1 S
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+TRICENTROL'S  T R AY2 - S EH1 N - T R AA0 L Z
+TRICEPS  T R AY1 - S EH2 P S
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+TRICHE  T R IH1 CH
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+TRICIA'S  T R IH1 - SH AH0 Z
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+TRICKERY  T R IH1 - K ER0 - IY0
+TRICKETT  T R IH1 - K IH0 T
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+TRICKSTERS  T R IH1 K - S T ER0 Z
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+TRIPODS  T R AY1 - P AA2 D Z
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+TRIPPE  T R IH1 P
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+WHEN(3)  W IH1 N
+WHEN(4)  HH W IH1 N
+WHENCE  W EH1 N S
+WHENCE(2)  HH W EH1 N S
+WHENEVER  W EH0 N - EH1 - V ER0
+WHENEVER(2)  HH W EH0 - N EH1 - V ER0
+WHERE  W EH1 R
+WHERE'D  W EH1 R D
+WHERE'D(2)  HH W EH1 R D
+WHERE'S  W EH1 R Z
+WHERE'S(2)  HH W EH1 R Z
+WHERE(2)  HH W EH1 R
+WHEREABOUTS  W EH1 - R AH0 - B AW2 T S
+WHEREABOUTS(2)  HH W EH1 - R AH0 - B AW2 T S
+WHEREAS  W EH0 - R AE1 Z
+WHEREAS(2)  HH W EH0 - R AE1 Z
+WHEREBY  W EH0 R - B AY1
+WHEREBY(2)  HH W EH0 R - B AY1
+WHEREIN  W EH0 - R IH1 N
+WHEREIN(2)  HH W EH0 - R IH1 N
+WHEREUPON  W EH1 - R AH0 - P AA1 N
+WHEREUPON(2)  HH W EH1 - R AH0 - P AA1 N
+WHEREVER  W EH0 - R EH1 - V ER0
+WHEREVER(2)  HH W EH0 - R EH1 - V ER0
+WHEREWITHAL  W EH1 R - W IH0 - DH AO2 L
+WHEREWITHAL(2)  HH W EH1 R - W IH0 - DH AO2 L
+WHERLEY  W ER1 - L IY0
+WHERLEY(2)  HH W ER1 - L IY0
+WHERRY  W EH1 - R IY0
+WHERRY(2)  HH W EH1 - R IY0
+WHET  W EH1 T
+WHET(2)  HH W EH1 T
+WHETHER  W EH1 - DH ER0
+WHETHER(2)  HH W EH1 - DH ER0
+WHETSEL  W EH1 T - S AH0 L
+WHETSEL(2)  HH W EH1 T - S AH0 L
+WHETSELL  W EH1 T - S AH0 L
+WHETSELL(2)  HH W EH1 T - S AH0 L
+WHETSTINE  W EH1 T - S T IY0 N
+WHETSTINE(2)  HH W EH1 T - S T IY0 N
+WHETSTONE  W EH1 T - S T OW2 N
+WHETSTONE(2)  HH W EH1 T - S T OW2 N
+WHETTED  W EH1 - T IH0 D
+WHETTED(2)  HH W EH1 - T IH0 D
+WHETZEL  W EH1 T - Z AH0 L
+WHETZEL(2)  HH W EH1 T - Z AH0 L
+WHEW  W UW1
+WHEW(2)  HH W UW1
+WHEW(3)  HH Y UW1
+WHEY  W EY1
+WHEY(2)  HH W EY1
+WHICH  W IH1 CH
+WHICH'RE  W IH1 - CH ER0
+WHICH'RE(2)  HH W IH1 - CH ER0
+WHICH'S  W IH1 - CH IH0 Z
+WHICH'S(2)  HH W IH1 - CH IH0 Z
+WHICH(2)  HH W IH1 CH
+WHICHARD  W IH1 - CH ER0 D
+WHICHARD(2)  HH W IH1 - CH ER0 D
+WHICHEVER  W IH0 CH - EH1 - V ER0
+WHICHEVER(2)  HH W IH0 CH - EH1 - V ER0
+WHICKER  W IH1 - K ER0
+WHICKER(2)  HH W IH1 - K ER0
+WHIDBY  W IH1 D - B IY0
+WHIDBY(2)  HH W IH1 D - B IY0
+WHIDDEN  W IH1 - D AH0 N
+WHIDDEN(2)  HH W IH1 - D AH0 N
+WHIDDON  W IH1 - D AH0 N
+WHIDDON(2)  HH W IH1 - D AH0 N
+WHIFF  W IH1 F
+WHIFF(2)  HH W IH1 F
+WHIG  W IH1 G
+WHIG(2)  HH W IH1 G
+WHIGHAM  W IH1 - G AH0 M
+WHIGHAM(2)  HH W IH1 - G AH0 M
+WHIGS  W IH1 G Z
+WHIGS(2)  HH W IH1 G Z
+WHILDEN  W AY1 L - D AH0 N
+WHILDEN(2)  HH W AY1 L - D AH0 N
+WHILE  W AY1 L
+WHILE(2)  HH W AY1 L
+WHILES  W AY1 L Z
+WHILES(2)  HH W AY1 L Z
+WHILST  W AY1 L S T
+WHIM  W IH1 M
+WHIM(2)  HH W IH1 M
+WHIMPER  W IH1 M - P ER0
+WHIMPER(2)  HH W IH1 M - P ER0
+WHIMPERING  W IH1 M - P ER0 - IH0 NG
+WHIMPERING(2)  HH W IH1 M - P ER0 - IH0 NG
+WHIMS  W IH1 M Z
+WHIMS(2)  HH W IH1 M Z
+WHIMSICAL  W IH1 M - Z IH0 - K AH0 L
+WHIMSICAL(2)  HH W IH1 M - Z IH0 - K AH0 L
+WHIMSY  W IH1 M - S IY0
+WHIMSY(2)  HH W IH1 M - S IY0
+WHINE  W AY1 N
+WHINE(2)  HH W AY1 N
+WHINER  W AY1 - N ER0
+WHINER(2)  HH W AY1 - N ER0
+WHINERS  W AY1 - N ER0 Z
+WHINERS(2)  HH W AY1 - N ER0 Z
+WHINERY  W AY1 - N ER0 - IY0
+WHINERY(2)  HH W AY1 - N ER0 - IY0
+WHINES  W AY1 N Z
+WHINES(2)  HH W AY1 N Z
+WHINING  W AY1 - N IH0 NG
+WHINING(2)  HH W AY1 - N IH0 NG
+WHINNERY  W IH1 - N ER0 - IY0
+WHINNERY(2)  HH W IH1 - N ER0 - IY0
+WHINNEY  W IH1 - N IY0
+WHINNEY(2)  HH W IH1 - N IY0
+WHINY  W AY1 - N IY0
+WHINY(2)  HH W AY1 - N IY0
+WHIP  W IH1 P
+WHIP(2)  HH W IH1 P
+WHIPKEY  W IH1 P - K IY2
+WHIPKEY(2)  HH W IH1 P - K IY2
+WHIPLASH  W IH1 P - L AE2 SH
+WHIPLASH(2)  HH W IH1 P - L AE2 SH
+WHIPLASHES  W IH1 P - L AE2 - SH AH0 Z
+WHIPLASHES(2)  HH W IH1 P - L AE2 - SH AH0 Z
+WHIPP  W IH1 P
+WHIPP(2)  HH W IH1 P
+WHIPPANY  W IH1 - P AH0 - N IY0
+WHIPPANY(2)  HH W IH1 - P AH0 - N IY0
+WHIPPED  W IH1 P T
+WHIPPED(2)  HH W IH1 P T
+WHIPPING  W IH1 - P IH0 NG
+WHIPPING(2)  HH W IH1 - P IH0 NG
+WHIPPLE  W IH1 - P AH0 L
+WHIPPLE'S  W IH1 - P AH0 L Z
+WHIPPLE'S(2)  HH W IH1 - P AH0 L Z
+WHIPPLE(2)  HH W IH1 - P AH0 L
+WHIPPOORWILLS  W IH1 P - ER0 - W IH2 L Z
+WHIPPOORWILLS(2)  HH W IH1 P - ER0 - W IH2 L Z
+WHIPPS  W IH1 P S
+WHIPPS(2)  HH W IH1 P S
+WHIPS  W IH1 P S
+WHIPS(2)  HH W IH1 P S
+WHIPSAW  W IH1 P - S AO2
+WHIPSAW(2)  HH W IH1 P - S AO2
+WHIPSAWED  W IH1 P - S AO2 D
+WHIPSAWED(2)  HH W IH1 P - S AO2 D
+WHIPSAWING  W IH1 P - S AO2 - IH0 NG
+WHIPSAWING(2)  HH W IH1 P - S AO2 - IH0 NG
+WHIRL  W ER1 L
+WHIRL(2)  HH W ER1 L
+WHIRLED  W ER1 L D
+WHIRLED(2)  HH W ER1 L D
+WHIRLEY  W ER1 - L IY0
+WHIRLEY(2)  HH W ER1 - L IY0
+WHIRLING  W ER1 - L IH0 NG
+WHIRLING(2)  HH W ER1 - L IH0 NG
+WHIRLPOOL  W ER1 L - P UW2 L
+WHIRLPOOL'S  W ER1 L - P UW2 L Z
+WHIRLPOOL'S(2)  HH W ER1 L - P UW2 L Z
+WHIRLPOOL(2)  HH W ER1 L - P UW2 L
+WHIRLPOOLS  W ER1 L - P UW2 L Z
+WHIRLPOOLS(2)  HH W ER1 L - P UW2 L Z
+WHIRLWIND  W ER1 L - W IH2 N D
+WHIRLWIND(2)  HH W ER1 L - W IH2 N D
+WHIRRING  W ER1 - IH0 NG
+WHIRRING(2)  HH W ER1 - IH0 NG
+WHISENAND  W IH1 - S IH0 - N AE0 N D
+WHISENAND(2)  HH W IH1 - S IH0 - N AE0 N D
+WHISENANT  W IH1 - S IH0 - N AH0 N T
+WHISENANT(2)  HH W IH1 - S IH0 - N AH0 N T
+WHISENHUNT  W AY1 - Z AH0 N - HH AH2 N T
+WHISENHUNT(2)  HH W AY1 - Z AH0 N - HH AH2 N T
+WHISK  W IH1 S K
+WHISK(2)  HH W IH1 S K
+WHISKED  W IH1 S K T
+WHISKED(2)  HH W IH1 S K T
+WHISKER  W IH1 - S K ER0
+WHISKER(2)  HH W IH1 - S K ER0
+WHISKERS  W IH1 - S K ER0 Z
+WHISKERS(2)  HH W IH1 - S K ER0 Z
+WHISKEY  W IH1 S - K IY0
+WHISKEY(2)  HH W IH1 S - K IY0
+WHISKEYS  W IH1 - S K IY0 Z
+WHISKEYS(2)  HH W IH1 - S K IY0 Z
+WHISKS  W IH1 S K S
+WHISKS(2)  HH W IH1 S K S
+WHISKY  W IH1 S - K IY0
+WHISKY(2)  HH W IH1 S - K IY0
+WHISLER  W IH1 S - L ER0
+WHISLER(2)  HH W IH1 S - L ER0
+WHISMAN  W IH1 S - M AH0 N
+WHISMAN(2)  HH W IH1 S - M AH0 N
+WHISNANT  W IH1 S - N AH0 N T
+WHISNANT(2)  HH W IH1 S - N AH0 N T
+WHISNER  W IH1 S - N ER0
+WHISNER(2)  HH W IH1 S - N ER0
+WHISONANT  W IH1 - S AH0 - N AH0 N T
+WHISPER  W IH1 - S P ER0
+WHISPER(2)  HH W IH1 - S P ER0
+WHISPERED  W IH1 - S P ER0 D
+WHISPERED(2)  HH W IH1 - S P ER0 D
+WHISPERING  W IH1 - S P ER0 - IH0 NG
+WHISPERING(2)  HH W IH1 - S P ER0 - IH0 NG
+WHISPERS  W IH1 - S P ER0 Z
+WHISPERS(2)  HH W IH1 - S P ER0 Z
+WHISTLE  W IH1 - S AH0 L
+WHISTLE(2)  HH W IH1 - S AH0 L
+WHISTLEBLOWER  W IH1 - S AH0 L - B L OW2 - ER0
+WHISTLEBLOWER(2)  HH W IH1 - S AH0 L - B L OW2 - ER0
+WHISTLEBLOWERS  W IH1 - S AH0 L - B L OW2 - ER0 Z
+WHISTLEBLOWERS(2)  HH W IH1 - S AH0 L - B L OW2 - ER0 Z
+WHISTLED  W IH1 - S AH0 L D
+WHISTLED(2)  HH W IH1 - S AH0 L D
+WHISTLER  W IH1 S - L ER0
+WHISTLER(2)  HH W IH1 S - L ER0
+WHISTLERS  W IH1 S - L ER0 Z
+WHISTLERS(2)  HH W IH1 S - L ER0 Z
+WHISTLES  W IH1 - S AH0 L Z
+WHISTLES(2)  HH W IH1 - S AH0 L Z
+WHISTLING  W IH1 - S L IH0 NG
+WHISTLING(2)  HH W IH1 - S L IH0 NG
+WHISTON  W IH1 - S T AH0 N
+WHISTON(2)  HH W IH1 - S T AH0 N
+WHIT  W IH1 T
+WHIT(2)  HH W IH1 T
+WHITACRE  W IH1 - T AH0 - K ER0
+WHITACRE(2)  HH W IH1 - T AH0 - K ER0
+WHITAKER  W IH1 - T AH0 - K ER0
+WHITAKER(2)  HH W IH1 - T AH0 - K ER0
+WHITBECK  W IH1 T - B EH2 K
+WHITBECK(2)  HH W IH1 T - B EH2 K
+WHITBREAD  W IH1 T - B R EH2 D
+WHITBREAD(2)  HH W IH1 T - B R EH2 D
+WHITBY  W IH1 T - B IY0
+WHITBY(2)  HH W IH1 T - B IY0
+WHITCHER  W IH1 - CH ER0
+WHITCHER(2)  HH W IH1 - CH ER0
+WHITCHURCH  W IH1 T - CH ER2 CH
+WHITCHURCH(2)  HH W IH1 T - CH ER2 CH
+WHITCOMB  W IH1 T - K AH0 M
+WHITCOMB(2)  HH W IH1 T - K AH0 M
+WHITCRAFT  W IH1 T - K R AE2 F T
+WHITCRAFT(2)  HH W IH1 T - K R AE2 F T
+WHITE  W AY1 T
+WHITE'S  W AY1 T S
+WHITE'S(2)  HH W AY1 T S
+WHITE(2)  HH W AY1 T
+WHITEAKER  W IH1 - T AH0 - K ER0
+WHITEAKER(2)  HH W IH1 - T AH0 - K ER0
+WHITEBREAD  W AY1 T - B R EH2 D
+WHITEBREAD(2)  HH W AY1 T - B R EH2 D
+WHITECOTTON  W AY1 T - K AA2 - T AH0 N
+WHITECOTTON(2)  HH W AY1 T - K AA2 - T AH0 N
+WHITED  W AY1 - T IH0 D
+WHITED(2)  HH W AY1 - T IH0 D
+WHITEFIELD  W AY1 T - F IY2 L D
+WHITEFIELD(2)  HH W AY1 T - F IY2 L D
+WHITEFISH  W AY1 T - F IH2 SH
+WHITEFISH(2)  HH W AY1 T - F IH2 SH
+WHITEFORD  W AY1 T - F AO0 R D
+WHITEFORD(2)  HH W AY1 T - F AO0 R D
+WHITEHAIR  W AY1 T - HH EH1 R
+WHITEHAIR(2)  HH W AY1 T - HH EH1 R
+WHITEHALL  W AY1 T - HH AO2 L
+WHITEHALL'S  W AY1 T - HH AO2 L Z
+WHITEHALL'S(2)  HH W AY1 T - HH AO2 L Z
+WHITEHALL(2)  HH W AY1 T - HH AO2 L
+WHITEHEAD  W AY1 T - HH EH2 D
+WHITEHEAD'S  W AY1 T - HH EH2 D Z
+WHITEHEAD'S(2)  HH W AY1 T - HH EH2 D Z
+WHITEHEAD(2)  HH W AY1 T - HH EH2 D
+WHITEHILL  W AY1 T - HH IH2 L
+WHITEHILL(2)  HH W AY1 T - HH IH2 L
+WHITEHORN  W AY1 T - HH AO2 R N
+WHITEHORN(2)  HH W AY1 T - HH AO2 R N
+WHITEHORSE  W AY1 T - HH AO2 R S
+WHITEHORSE(2)  HH W AY1 T - HH AO2 R S
+WHITEHOUSE  W AY1 T - HH AW2 S
+WHITEHOUSE(2)  HH W AY1 T - HH AW2 S
+WHITEHURST  W AY1 T - HH ER2 S T
+WHITEHURST'S  W AY1 T - HH ER2 S T
+WHITEHURST(2)  HH W AY1 T - HH ER2 S T
+WHITELAW  W AY1 T - L AO2
+WHITELAW(2)  HH W AY1 T - L AO2
+WHITELEY  W AY1 T - L IY0
+WHITELEY(2)  HH W AY1 T - L IY0
+WHITELOCK  W AY1 T - L AA2 K
+WHITELOCK(2)  HH W AY1 T - L AA2 K
+WHITELY  W AY1 T - L IY0
+WHITELY(2)  HH W AY1 T - L IY0
+WHITEMAN  W AY1 T - M AH0 N
+WHITEMAN(2)  HH W AY1 T - M AH0 N
+WHITEMONT  W AY1 T - M AA2 N T
+WHITEMONT(2)  HH W AY1 T - M AA2 N T
+WHITEN  W AY1 - T AH0 N
+WHITEN(2)  HH W AY1 - T AH0 N
+WHITENACK  W AY1 T - N AE2 K
+WHITENACK(2)  HH W AY1 T - N AE2 K
+WHITENEIR  W AY1 T - N IH2 R
+WHITENEIR(2)  HH W AY1 T - N IH2 R
+WHITENER  W AY1 T - N ER0
+WHITENER(2)  HH W AY1 T - N ER0
+WHITENESS  W AY1 T - N AH0 S
+WHITENESS(2)  HH W AY1 T - N AH0 S
+WHITENIGHT  W AY1 T - N AY2 T
+WHITENIGHT(2)  HH W AY1 T - N AY2 T
+WHITENING  W AY1 - T IH0 - N IH0 NG
+WHITENING(2)  W AY1 T - N IH0 NG
+WHITENING(3)  HH W AY1 - T IH0 - N IH0 NG
+WHITENING(4)  HH W AY1 T - N IH0 NG
+WHITER  W AY1 - T ER0
+WHITER(2)  HH W AY1 - T ER0
+WHITES  W AY1 T S
+WHITES(2)  HH W AY1 T S
+WHITESCARVER  W AY1 T - S K AA2 R - V ER0
+WHITESCARVER(2)  HH W AY1 T - S K AA2 R - V ER0
+WHITESEL  W AY1 T - S EH2 L
+WHITESEL(2)  HH W AY1 T - S EH2 L
+WHITESELL  W AY1 T - S EH2 L
+WHITESELL(2)  HH W AY1 T - S EH2 L
+WHITESIDE  W AY1 T - S AY2 D
+WHITESIDE(2)  HH W AY1 T - S AY2 D
+WHITESIDES  W AY1 T - S AY2 D Z
+WHITESIDES(2)  HH W AY1 T - S AY2 D Z
+WHITEST  W AY1 - T IH0 S T
+WHITEST(2)  HH W AY1 - T IH0 S T
+WHITESTONE  W AY1 T - S T OW2 N
+WHITESTONE(2)  HH W AY1 T - S T OW2 N
+WHITETAIL  W AY1 T - T EY2 L
+WHITETAIL(2)  HH W AY1 T - T EY2 L
+WHITETAIL(3)  HH W AY1 - T EY2 L
+WHITEWASH  W AY1 T - W AA2 SH
+WHITEWASH(2)  HH W AY1 T - W AA2 SH
+WHITEWASHED  W AY1 T - W AA2 SH T
+WHITEWASHED(2)  HH W AY1 T - W AA2 SH T
+WHITEWATER  W AY1 T - W AO2 - T ER0
+WHITEWATER'S  W AY1 T - W AO2 - T ER0 Z
+WHITEWATER'S(2)  HH W AY1 T - W AO2 - T ER0 Z
+WHITEWATER(2)  HH W AY1 T - W AO2 - T ER0
+WHITEY  W AY1 - T IY2
+WHITEY(2)  HH W AY1 - T IY2
+WHITEY(3)  HH W AY1 - T IY0
+WHITFIELD  W IH1 T - F IY0 L D
+WHITFIELD(2)  HH W IH1 T - F IY0 L D
+WHITFILL  W IH1 T - F IH2 L
+WHITFILL(2)  HH W IH1 T - F IH2 L
+WHITFORD  W IH1 T - F ER0 D
+WHITFORD(2)  HH W IH1 T - F ER0 D
+WHITHAM  W IH1 - TH AH0 M
+WHITHAM(2)  HH W IH1 - TH AH0 M
+WHITHAM(3)  HH W IH1 - T AH0 M
+WHITHER  W IH1 - DH ER0
+WHITHER(2)  HH W IH1 - DH ER0
+WHITING  W AY1 - T IH0 NG
+WHITING(2)  HH W AY1 - T IH0 NG
+WHITINGS  W AY1 - T IH0 NG Z
+WHITINGS(2)  HH W AY1 - T IH0 NG Z
+WHITIS  W AY1 - T IH0 S
+WHITIS(2)  HH W AY1 - T IH0 S
+WHITISH  W AY1 - T IH0 SH
+WHITISH(2)  HH W AY1 - T IH0 SH
+WHITLATCH  W IH1 T - L AE2 CH
+WHITLATCH(2)  HH W IH1 T - L AE2 CH
+WHITLEDGE  W IH1 T - L EH2 JH
+WHITLEDGE(2)  HH W IH1 T - L EH2 JH
+WHITLEY  W IH1 T - L IY0
+WHITLEY(2)  HH W IH1 T - L IY0
+WHITLING  W IH1 T - L IH0 NG
+WHITLING(2)  HH W IH1 T - L IH0 NG
+WHITLOCK  W IH1 T - L AA2 K
+WHITLOCK(2)  HH W IH1 T - L AA2 K
+WHITLOW  W IH1 T - L OW2
+WHITLOW(2)  HH W IH1 T - L OW2
+WHITLY  W IH1 T - L IY0
+WHITLY(2)  HH W IH1 T - L IY0
+WHITMAN  W IH1 T - M AH0 N
+WHITMAN'S  W IH1 T - M AH0 N Z
+WHITMAN'S(2)  HH W IH1 T - M AH0 N Z
+WHITMAN(2)  HH W IH1 T - M AH0 N
+WHITMARSH  W IH1 T - M AA2 R SH
+WHITMARSH(2)  HH W IH1 T - M AA2 R SH
+WHITMER  W IH1 T - M ER0
+WHITMER(2)  HH W IH1 T - M ER0
+WHITMILL  W IH1 T - M IH2 L
+WHITMILL(2)  HH W IH1 T - M IH2 L
+WHITMIRE  W IH1 T - M AY2 R
+WHITMIRE(2)  HH W IH1 T - M AY2 R
+WHITMORE  W IH1 T - M AO0 R
+WHITMORE(2)  HH W IH1 T - M AO0 R
+WHITMOYER  W IH1 T - M OY2 - ER0
+WHITMOYER(2)  HH W IH1 T - M OY2 - ER0
+WHITMYER  W IH1 T - M AY2 - ER0
+WHITMYER(2)  HH W IH1 T - M AY2 - ER0
+WHITNER  W IH1 T - N ER0
+WHITNER(2)  HH W IH1 T - N ER0
+WHITNEY  W IH1 T - N IY0
+WHITNEY'S  W IH1 T - N IY0 Z
+WHITNEY'S(2)  HH W IH1 T - N IY0 Z
+WHITNEY(2)  HH W IH1 T - N IY0
+WHITON  W IH1 - T AH0 N
+WHITON(2)  HH W IH1 - T AH0 N
+WHITROW  W IH1 - T R OW2
+WHITROW(2)  HH W IH1 - T R OW2
+WHITSEL  W IH1 T - S AH0 L
+WHITSEL(2)  HH W IH1 T - S AH0 L
+WHITSELL  W IH1 T - S AH0 L
+WHITSELL(2)  HH W IH1 T - S AH0 L
+WHITSETT  W IH1 T - S IH0 T
+WHITSETT(2)  HH W IH1 T - S IH0 T
+WHITSITT  W IH1 T - S IH0 T
+WHITSITT(2)  HH W IH1 T - S IH0 T
+WHITSON  W IH1 T - S AH0 N
+WHITSON(2)  HH W IH1 T - S AH0 N
+WHITT  W IH1 T
+WHITT(2)  HH W IH1 T
+WHITTAKER  W IH1 - T AH0 - K ER0
+WHITTAKER(2)  HH W IH1 - T AH0 - K ER0
+WHITTED  W IH1 - T IH0 D
+WHITTED(2)  HH W IH1 - T IH0 D
+WHITTEMORE  W IH1 T - M AO0 R
+WHITTEMORE(2)  HH W IH1 T - M AO0 R
+WHITTEN  W IH1 - T AH0 N
+WHITTEN(2)  HH W IH1 - T AH0 N
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+ZIMBALIST  Z IH1 M - B AH0 - L IH0 S T
+ZIMBELMAN  Z IH1 M - B AH0 L - M AH0 N
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+ZINGARO  Z IH0 NG - G AA1 - R OW0
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+ZINGG  Z IH1 NG G
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+ZINGLER(2)  Z IH1 NG - G L ER0
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+ZINNER  Z IH1 - N ER0
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+ZIOBRO  Z IY0 - OW1 - B R OW0
+ZIOLKOWSKI  Z IY0 - OW0 L - K AO1 F S - K IY0
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+ZIONISTS  Z AY1 - AH0 - N IH0 S T S
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+ZIPF  Z IH1 P F
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+ZIPKIN  Z IH1 P - K IH0 N
+ZIPLESS  Z IH1 P - L AH0 S
+ZIPP  Z IH1 P
+ZIPPED  Z IH1 P T
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+ZIPPERING  Z IH1 - P ER0 - IH0 NG
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+ZIPPING  Z IH1 - P IH0 NG
+ZIPPO  Z IH1 - P OW0
+ZIPPORA  Z IY0 - P AO1 - R AH0
+ZIPPY  Z IH1 - P IY0
+ZIPS  Z IH1 P S
+ZIRBEL  Z ER1 - B AH0 L
+ZIRBES  Z ER1 B Z
+ZIRCON  Z ER1 - K AH0 N
+ZIRCONIUM  Z ER0 - K OW1 - N IY0 - AH0 M
+ZIRCONIUMS  Z ER0 - K OW1 - N IY0 - AH0 M Z
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+ZIRKLE  Z ER1 - K AH0 L
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+ZISSON  Z IH1 - S AH0 N
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+ZIYANG  ZH IY0 - AE1 NG
+ZIYANG(2)  ZH IY0 - AA1 NG
+ZIZZO  Z IH1 - Z OW0
+ZLATA  Z L AA1 - T AH2
+ZLATA'S  Z L AA1 - T AH2 Z
+ZLATA'S(2)  Z L AA1 - T AH0 Z
+ZLATA(2)  Z L AA1 - T AH0
+ZLIN  Z L IH1 N
+ZLOBIN  Z L AO1 - B IH0 N
+ZLOGAR  Z L OW1 - G ER0
+ZLOMSOWITCH  Z L AA1 M - S OW0 - IH0 CH
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+ZLOTY  Z L AO1 - T IY0
+ZLOTYS  Z L AO1 - T IY0 Z
+ZMIJEWSKI  Z M IY0 - UW1 - S K IY0
+ZOBEL  Z OW1 - B AH0 L
+ZOBRIST  Z AA1 - B R IH0 S T
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+ZOCOR(2)  Z OW1 - K AO2 R
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+ZOLLO  Z AA1 - L OW0
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+ZOLTAN  Z OW1 L - T AH0 N
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+ZOMBIES  Z AA1 M - B IY0 Z
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+ZOOLOGY  Z OW0 - AA1 - L AH0 - JH IY0
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+ZORICH  Z AO1 - R IH0 K
+ZORINA  Z AO0 - R IY1 - N AH0
+ZORINE  Z AO0 - R IY1 - N IY0
+ZORINSKY  Z AO0 - R IH1 N S - K IY0
+ZORKIN  Z AO1 R - K IH0 N
+ZORN  Z AO1 R N
+ZORNES  Z AO1 R N Z
+ZORNOW  Z AO1 R - N AW0
+ZORRO  Z AO1 - R OW2
+ZORTMAN  Z AO1 R T - M AH0 N
+ZORZ  Z AO1 R Z
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+ZOSEN  Z OW1 - Z AH0 N
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+ZOSTER  Z AA1 - S T ER0
+ZOTOS  Z OW1 - T OW0 Z
+ZOTTER  Z AA1 - T ER0
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+ZUBE  Z UW1 B
+ZUBER  Z UW1 - B ER0
+ZUBIA  Z UW1 - B IY0 - AH0
+ZUBILLAGA  Z UW2 - B IH0 - L AA1 - G AH0
+ZUBIN  Z UW1 - B IH0 N
+ZUBOFF  Z UW1 - B AO0 F
+ZUBROD  Z AH1 - B R AH0 D
+ZUCCARELLI  Z UW0 - K ER0 - EH1 - L IY0
+ZUCCARO  Z UW0 - K AA1 - R OW0
+ZUCCHINI  Z UW0 - K IY1 - N IY0
+ZUCCO  Z UW1 - K OW0
+ZUCH  Z AH1 CH
+ZUCHOWSKI  Z AH0 - HH AO1 F S - K IY0
+ZUCHOWSKI(2)  Z UW0 - K AO1 F S - K IY0
+ZUCK  Z AH1 K
+ZUCKER  Z AH1 - K ER0
+ZUCKER'S  Z AH1 - K ER0 Z
+ZUCKER'S(2)  Z UW1 - K ER0 Z
+ZUCKER(2)  Z UW1 - K ER0
+ZUCKERMAN  Z AH1 - K ER0 - M AH0 N
+ZUCKERMAN'S  Z AH1 - K ER0 - M AH0 N Z
+ZUCKERMAN'S(2)  Z UW1 - K ER0 - M AH0 N Z
+ZUCKERMAN(2)  Z UW1 - K ER0 - M AH0 N
+ZUE  Z UW1
+ZUE'S  Z UW1 Z
+ZUEGE  Z UW1 JH
+ZUEHLKE  Z UH1 L K
+ZUELKE  Z UW1 L K
+ZUERCHER  Z UH1 R - K ER0
+ZUFALL  Z UW1 - F AH0 L
+ZUFELT  Z AH1 - F IH0 L T
+ZUG  Z AH1 G
+ZUG'S  Z AH1 G Z
+ZUGANOV  Z UW1 - G AH0 - N AO2 V
+ZUGANOV'S  Z UW1 - G AH0 - N AO2 V S
+ZUGANOV'S(2)  Z UW1 - G AH0 - N AO2 F S
+ZUGANOV(2)  Z UW1 - G AH0 - N AO2 F
+ZUHLKE  Z UW1 L K
+ZUIDEMA  Z UW0 - IH0 - D EH1 - M AH0
+ZUK  Z AH1 K
+ZUKAS  Z UW1 - K AH0 Z
+ZUKER  Z UW1 - K ER0
+ZUKERMAN  Z UW1 - K ER0 - M AH0 N
+ZUKIN  Z UW1 - K IH0 N
+ZUKOWSKI  Z AH0 - K AO1 F S - K IY0
+ZULAUF  Z UW1 - L AW0 F
+ZULEGER  Z UW1 - L IH0 - G ER0
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+ZULUAGA  Z UW2 - L UW0 - AA1 - G AH0
+ZULUS  Z UW1 - L UW0 Z
+ZUMBRO  Z AH1 M - B R OW0
+ZUMBRUN  Z AH1 M - B R AH0 N
+ZUMEL  Z UW2 - M EH1 L
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+ZUMPANO  Z UW0 M - P AA1 - N OW0
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+ZUMSTEIN(2)  Z AH1 M - S T AY2 N
+ZUMWALT  Z AH1 M - W AH0 L T
+ZUNDEL  Z AH1 N - D AH0 L
+ZUNGU  Z AH2 - NG UW1
+ZUNI  Z UW1 - N IY2
+ZUNIGA  Z UW0 - N IY1 - G AH0
+ZUNINO  Z UW0 - N IY1 - N OW0
+ZUNKER  Z AH1 NG - K ER0
+ZUPAN  Z UW1 - P AH0 N
+ZUPANCIC  Z AH0 - P AE1 NG - K IH0 K
+ZUPANJA  Z AH0 - P AE1 N - JH AH0
+ZUPKO  Z AH1 P - K OW0
+ZURAWSKI  Z ER0 - AA1 F S - K IY0
+ZURCHER  Z ER1 - K ER0
+ZUREK  Z UH1 - R EH0 K
+ZURFLUH  Z ER1 - F L UW0
+ZURI  Z UH1 - R IY0
+ZURICH  Z UH1 - R IH0 K
+ZURICH'S  Z UH1 - R IH0 K S
+ZURITA  Z ER0 - AY1 - T AH0
+ZURKUHLEN  Z ER0 - K Y UW1 - L AH0 N
+ZURN  Z ER1 N
+ZUROWSKI  Z ER0 - AO1 F S - K IY0
+ZUVER  Z UW1 - V ER0
+ZUZANA  Z UW2 - Z AA1 - N AH0
+ZVORNIK  Z V AO1 R - N IH0 K
+ZWACK  Z W AO1 K
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+ZWART  Z W AO1 R T
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+ZWEIFEL  Z W AY1 - F AH0 L
+ZWEIG  Z W AY1 G
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+ZYSKOWSKI  Z IH0 - S K AO1 F S - K IY0
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+ZYUGANOV'S  Z Y UW1 - G AA0 - N AA0 V Z
+ZYUGANOV'S(2)  Z Y UW1 - G AA0 - N AA0 F S
+ZYUGANOV'S(3)  Z UW1 - G AA0 - N AA0 V Z
+ZYUGANOV'S(4)  Z UW1 - G AA0 - N AA0 F S
+ZYUGANOV(2)  Z Y UW1 - G AA0 - N AA0 F
+ZYUGANOV(3)  Z UW1 - G AA0 - N AA0 V
+ZYUGANOV(4)  Z UW1 - G AA0 - N AA0 F
+ZYWICKI  Z IH0 - W IH1 - K IY0
+ZZZZ  Z IY0 Z
+ZZZZ(2)  Z Z
+{BRACE  B R EY1 S
+{LEFT-BRACE  L EH1 F T - B R EY1 S
+}CLOSE-BRACE  K L OW1 Z - B R EY1 S
+}RIGHT-BRACE  R AY1 T - B R EY1 S
diff --git a/text/cmudict_cache.pickle b/text/cmudict_cache.pickle
new file mode 100644
index 0000000000000000000000000000000000000000..cab7f7d732affe0bd8d860a81e770b9bf1f72064
--- /dev/null
+++ b/text/cmudict_cache.pickle
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b9b21b20325471934ba92f2e4a5976989e7d920caa32e7a286eacb027d197949
+size 6212655
diff --git a/text/english.py b/text/english.py
new file mode 100644
index 0000000000000000000000000000000000000000..bf48db11fd0af30f0bb8142f97e31ea8996e3fc2
--- /dev/null
+++ b/text/english.py
@@ -0,0 +1,109 @@
+import pickle
+import os
+import re
+from g2p_en import G2p
+
+from string import punctuation
+
+from text import symbols
+
+current_file_path = os.path.dirname(__file__)
+CMU_DICT_PATH = os.path.join(current_file_path, 'cmudict.rep')
+CACHE_PATH = os.path.join(current_file_path, 'cmudict_cache.pickle')
+_g2p = G2p()
+
+arpa = {'AH0', 'S', 'AH1', 'EY2', 'AE2', 'EH0', 'OW2', 'UH0', 'NG', 'B', 'G', 'AY0', 'M', 'AA0', 'F', 'AO0', 'ER2', 'UH1', 'IY1', 'AH2', 'DH', 'IY0', 'EY1', 'IH0', 'K', 'N', 'W', 'IY2', 'T', 'AA1', 'ER1', 'EH2', 'OY0', 'UH2', 'UW1', 'Z', 'AW2', 'AW1', 'V', 'UW2', 'AA2', 'ER', 'AW0', 'UW0', 'R', 'OW1', 'EH1', 'ZH', 'AE0', 'IH2', 'IH', 'Y', 'JH', 'P', 'AY1', 'EY0', 'OY2', 'TH', 'HH', 'D', 'ER0', 'CH', 'AO1', 'AE1', 'AO2', 'OY1', 'AY2', 'IH1', 'OW0', 'L', 'SH'}
+
+
+def replace_phs(phs):
+    rep_map = {
+        ';': ',',
+        ':': ',',
+        '\'': '-',
+        '"': '-'
+    }
+    phs_new = []
+    for ph in phs:
+        if ph in symbols:
+            phs_new.append(ph)
+        elif ph in rep_map.keys():
+            phs_new.append(rep_map[ph])
+        else:
+            print('ph not in symbols: ', ph)
+    return phs_new
+
+def read_dict():
+    g2p_dict = {}
+    start_line = 49
+    with open(CMU_DICT_PATH) as f:
+        line = f.readline()
+        line_index = 1
+        while line:
+            if line_index >= start_line:
+                line = line.strip()
+                word_split = line.split('  ')
+                word = word_split[0]
+
+                syllable_split = word_split[1].split(' - ')
+                g2p_dict[word] = []
+                for syllable in syllable_split:
+                    phone_split = syllable.split(' ')
+                    g2p_dict[word].append(phone_split)
+
+            line_index = line_index + 1
+            line = f.readline()
+
+    return g2p_dict
+
+
+def cache_dict(g2p_dict, file_path):
+    with open(file_path, 'wb') as pickle_file:
+        pickle.dump(g2p_dict, pickle_file)
+
+
+def get_dict():
+    if os.path.exists(CACHE_PATH):
+        with open(CACHE_PATH, 'rb') as pickle_file:
+            g2p_dict = pickle.load(pickle_file)
+    else:
+        g2p_dict = read_dict()
+        cache_dict(g2p_dict, CACHE_PATH)
+
+    return g2p_dict
+
+eng_dict = get_dict()
+
+
+def text_normalize(text):
+    # todo: eng text normalize
+    return text.replace(";", ",")
+
+def g2p(text):
+
+    phones = []
+    words = re.split(r"([,;.\-\?\!\s+])", text)
+    for w in words:
+        if w.upper() in eng_dict:
+            phns = eng_dict[w.upper()]
+            for ph in phns:
+                phones += ph
+        else:
+            phone_list = list(filter(lambda p: p != " ", _g2p(w)))
+            for ph in phone_list:
+                if ph in arpa:
+                    phones.append(ph)
+                else:
+                    phones.append(ph)
+
+    return replace_phs(phones)
+
+if __name__ == "__main__":
+    # print(get_dict())
+    print(g2p("hello"))
+    print(g2p("In this; paper, we propose 1 DSPGAN, a GAN-based universal vocoder."))
+    # all_phones = set()
+    # for k, syllables in eng_dict.items():
+    #     for group in syllables:
+    #         for ph in group:
+    #             all_phones.add(ph)
+    # print(all_phones)
\ No newline at end of file
diff --git a/text/japanese.py b/text/japanese.py
new file mode 100644
index 0000000000000000000000000000000000000000..f1263e46087daa54d5b0ba30823d92f3b0aeb3d4
--- /dev/null
+++ b/text/japanese.py
@@ -0,0 +1,98 @@
+# modified from https://github.com/CjangCjengh/vits/blob/main/text/japanese.py
+import re
+import sys
+
+import pyopenjtalk
+
+from text import symbols
+
+# Regular expression matching Japanese without punctuation marks:
+_japanese_characters = re.compile(
+    r'[A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]')
+
+# Regular expression matching non-Japanese characters or punctuation marks:
+_japanese_marks = re.compile(
+    r'[^A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]')
+
+# List of (symbol, Japanese) pairs for marks:
+_symbols_to_japanese = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('％', 'パーセント')
+]]
+
+
+# List of (consonant, sokuon) pairs:
+_real_sokuon = [(re.compile('%s' % x[0]), x[1]) for x in [
+    (r'Q([↑↓]*[kg])', r'k#\1'),
+    (r'Q([↑↓]*[tdjʧ])', r't#\1'),
+    (r'Q([↑↓]*[sʃ])', r's\1'),
+    (r'Q([↑↓]*[pb])', r'p#\1')
+]]
+
+# List of (consonant, hatsuon) pairs:
+_real_hatsuon = [(re.compile('%s' % x[0]), x[1]) for x in [
+    (r'N([↑↓]*[pbm])', r'm\1'),
+    (r'N([↑↓]*[ʧʥj])', r'n^\1'),
+    (r'N([↑↓]*[tdn])', r'n\1'),
+    (r'N([↑↓]*[kg])', r'ŋ\1')
+]]
+
+
+
+def post_replace_ph(ph):
+    rep_map = {
+        '：': ',',
+        '；': ',',
+        '，': ',',
+        '。': '.',
+        '！': '!',
+        '？': '?',
+        '\n': '.',
+        "·": ",",
+        '、': ",",
+        '...': '…'
+    }
+    if ph in rep_map.keys():
+        ph = rep_map[ph]
+    if ph in symbols:
+        return ph
+    if ph not in symbols:
+        ph = 'UNK'
+    return ph
+
+def symbols_to_japanese(text):
+    for regex, replacement in _symbols_to_japanese:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def preprocess_jap(text):
+    '''Reference https://r9y9.github.io/ttslearn/latest/notebooks/ch10_Recipe-Tacotron.html'''
+    text = symbols_to_japanese(text)
+    sentences = re.split(_japanese_marks, text)
+    marks = re.findall(_japanese_marks, text)
+    text = []
+    for i, sentence in enumerate(sentences):
+        if re.match(_japanese_characters, sentence):
+            p = pyopenjtalk.g2p(sentence)
+            text += p.split(" ")
+
+        if i < len(marks):
+            text += [marks[i].replace(' ', '')]
+    return text
+
+def text_normalize(text):
+    # todo: jap text normalize
+    return text
+
+def g2p(norm_text):
+    phones = preprocess_jap(norm_text)
+    phones = [post_replace_ph(i) for i in phones]
+    # todo: implement tones and word2ph
+    return phones
+
+
+if __name__ == '__main__':
+    for line in open("../../../Downloads/transcript_utf8.txt").readlines():
+        text = line.split(":")[1]
+        phones = g2p(text)
+        print(phones)
diff --git a/text/opencpop-strict.txt b/text/opencpop-strict.txt
new file mode 100644
index 0000000000000000000000000000000000000000..1bede89a429e34b1a58781ee570fc313b80c0aee
--- /dev/null
+++ b/text/opencpop-strict.txt
@@ -0,0 +1,429 @@
+a	AA a
+ai	AA ai
+an	AA an
+ang	AA ang
+ao	AA ao
+ba	b a
+bai	b ai
+ban	b an
+bang	b ang
+bao	b ao
+bei	b ei
+ben	b en
+beng	b eng
+bi	b i
+bian	b ian
+biao	b iao
+bie	b ie
+bin	b in
+bing	b ing
+bo	b o
+bu	b u
+ca	c a
+cai	c ai
+can	c an
+cang	c ang
+cao	c ao
+ce	c e
+cei	c ei
+cen	c en
+ceng	c eng
+cha	ch a
+chai	ch ai
+chan	ch an
+chang	ch ang
+chao	ch ao
+che	ch e
+chen	ch en
+cheng	ch eng
+chi	ch ir
+chong	ch ong
+chou	ch ou
+chu	ch u
+chua	ch ua
+chuai	ch uai
+chuan	ch uan
+chuang	ch uang
+chui	ch ui
+chun	ch un
+chuo	ch uo
+ci	c i0
+cong	c ong
+cou	c ou
+cu	c u
+cuan	c uan
+cui	c ui
+cun	c un
+cuo	c uo
+da	d a
+dai	d ai
+dan	d an
+dang	d ang
+dao	d ao
+de	d e
+dei	d ei
+den	d en
+deng	d eng
+di	d i
+dia	d ia
+dian	d ian
+diao	d iao
+die	d ie
+ding	d ing
+diu	d iu
+dong	d ong
+dou	d ou
+du	d u
+duan	d uan
+dui	d ui
+dun	d un
+duo	d uo
+e	EE e
+ei	EE ei
+en	EE en
+eng	EE eng
+er	EE er
+fa	f a
+fan	f an
+fang	f ang
+fei	f ei
+fen	f en
+feng	f eng
+fo	f o
+fou	f ou
+fu	f u
+ga	g a
+gai	g ai
+gan	g an
+gang	g ang
+gao	g ao
+ge	g e
+gei	g ei
+gen	g en
+geng	g eng
+gong	g ong
+gou	g ou
+gu	g u
+gua	g ua
+guai	g uai
+guan	g uan
+guang	g uang
+gui	g ui
+gun	g un
+guo	g uo
+ha	h a
+hai	h ai
+han	h an
+hang	h ang
+hao	h ao
+he	h e
+hei	h ei
+hen	h en
+heng	h eng
+hong	h ong
+hou	h ou
+hu	h u
+hua	h ua
+huai	h uai
+huan	h uan
+huang	h uang
+hui	h ui
+hun	h un
+huo	h uo
+ji	j i
+jia	j ia
+jian	j ian
+jiang	j iang
+jiao	j iao
+jie	j ie
+jin	j in
+jing	j ing
+jiong	j iong
+jiu	j iu
+ju	j v
+jv	j v
+juan	j van
+jvan	j van
+jue	j ve
+jve	j ve
+jun	j vn
+jvn	j vn
+ka	k a
+kai	k ai
+kan	k an
+kang	k ang
+kao	k ao
+ke	k e
+kei	k ei
+ken	k en
+keng	k eng
+kong	k ong
+kou	k ou
+ku	k u
+kua	k ua
+kuai	k uai
+kuan	k uan
+kuang	k uang
+kui	k ui
+kun	k un
+kuo	k uo
+la	l a
+lai	l ai
+lan	l an
+lang	l ang
+lao	l ao
+le	l e
+lei	l ei
+leng	l eng
+li	l i
+lia	l ia
+lian	l ian
+liang	l iang
+liao	l iao
+lie	l ie
+lin	l in
+ling	l ing
+liu	l iu
+lo	l o
+long	l ong
+lou	l ou
+lu	l u
+luan	l uan
+lun	l un
+luo	l uo
+lv	l v
+lve	l ve
+ma	m a
+mai	m ai
+man	m an
+mang	m ang
+mao	m ao
+me	m e
+mei	m ei
+men	m en
+meng	m eng
+mi	m i
+mian	m ian
+miao	m iao
+mie	m ie
+min	m in
+ming	m ing
+miu	m iu
+mo	m o
+mou	m ou
+mu	m u
+na	n a
+nai	n ai
+nan	n an
+nang	n ang
+nao	n ao
+ne	n e
+nei	n ei
+nen	n en
+neng	n eng
+ni	n i
+nian	n ian
+niang	n iang
+niao	n iao
+nie	n ie
+nin	n in
+ning	n ing
+niu	n iu
+nong	n ong
+nou	n ou
+nu	n u
+nuan	n uan
+nun	n un
+nuo	n uo
+nv	n v
+nve	n ve
+o	OO o
+ou	OO ou
+pa	p a
+pai	p ai
+pan	p an
+pang	p ang
+pao	p ao
+pei	p ei
+pen	p en
+peng	p eng
+pi	p i
+pian	p ian
+piao	p iao
+pie	p ie
+pin	p in
+ping	p ing
+po	p o
+pou	p ou
+pu	p u
+qi	q i
+qia	q ia
+qian	q ian
+qiang	q iang
+qiao	q iao
+qie	q ie
+qin	q in
+qing	q ing
+qiong	q iong
+qiu	q iu
+qu	q v
+qv	q v
+quan	q van
+qvan	q van
+que	q ve
+qve	q ve
+qun	q vn
+qvn	q vn
+ran	r an
+rang	r ang
+rao	r ao
+re	r e
+ren	r en
+reng	r eng
+ri	r ir
+rong	r ong
+rou	r ou
+ru	r u
+rua	r ua
+ruan	r uan
+rui	r ui
+run	r un
+ruo	r uo
+sa	s a
+sai	s ai
+san	s an
+sang	s ang
+sao	s ao
+se	s e
+sen	s en
+seng	s eng
+sha	sh a
+shai	sh ai
+shan	sh an
+shang	sh ang
+shao	sh ao
+she	sh e
+shei	sh ei
+shen	sh en
+sheng	sh eng
+shi	sh ir
+shou	sh ou
+shu	sh u
+shua	sh ua
+shuai	sh uai
+shuan	sh uan
+shuang	sh uang
+shui	sh ui
+shun	sh un
+shuo	sh uo
+si	s i0
+song	s ong
+sou	s ou
+su	s u
+suan	s uan
+sui	s ui
+sun	s un
+suo	s uo
+ta	t a
+tai	t ai
+tan	t an
+tang	t ang
+tao	t ao
+te	t e
+tei	t ei
+teng	t eng
+ti	t i
+tian	t ian
+tiao	t iao
+tie	t ie
+ting	t ing
+tong	t ong
+tou	t ou
+tu	t u
+tuan	t uan
+tui	t ui
+tun	t un
+tuo	t uo
+wa	w a
+wai	w ai
+wan	w an
+wang	w ang
+wei	w ei
+wen	w en
+weng	w eng
+wo	w o
+wu	w u
+xi	x i
+xia	x ia
+xian	x ian
+xiang	x iang
+xiao	x iao
+xie	x ie
+xin	x in
+xing	x ing
+xiong	x iong
+xiu	x iu
+xu	x v
+xv	x v
+xuan	x van
+xvan	x van
+xue	x ve
+xve	x ve
+xun	x vn
+xvn	x vn
+ya	y a
+yan	y En
+yang	y ang
+yao	y ao
+ye	y E
+yi	y i
+yin	y in
+ying	y ing
+yo	y o
+yong	y ong
+you	y ou
+yu	y v
+yv	y v
+yuan	y van
+yvan	y van
+yue	y ve
+yve	y ve
+yun	y vn
+yvn	y vn
+za	z a
+zai	z ai
+zan	z an
+zang	z ang
+zao	z ao
+ze	z e
+zei	z ei
+zen	z en
+zeng	z eng
+zha	zh a
+zhai	zh ai
+zhan	zh an
+zhang	zh ang
+zhao	zh ao
+zhe	zh e
+zhei	zh ei
+zhen	zh en
+zheng	zh eng
+zhi	zh ir
+zhong	zh ong
+zhou	zh ou
+zhu	zh u
+zhua	zh ua
+zhuai	zh uai
+zhuan	zh uan
+zhuang	zh uang
+zhui	zh ui
+zhun	zh un
+zhuo	zh uo
+zi	z i0
+zong	z ong
+zou	z ou
+zu	z u
+zuan	z uan
+zui	z ui
+zun	z un
+zuo	z uo
diff --git a/text/symbols.py b/text/symbols.py
new file mode 100644
index 0000000000000000000000000000000000000000..5322a928a19f98b4ee2a5673e55fc3d8172977f7
--- /dev/null
+++ b/text/symbols.py
@@ -0,0 +1,24 @@
+import os
+
+# punctuation = ['!', '?', '…', ",", ".","@"]#@是SP停顿
+punctuation = ['!', '?', '…', ",", "."]#@是SP停顿
+punctuation.append("-")
+pu_symbols = punctuation + ["SP", 'SP2', 'SP3', "UNK"]
+# pu_symbols = punctuation + ["SP", 'SP2', 'SP3','SP4', "UNK"]
+pad = '_'
+
+c = ['AA', 'EE', 'OO', 'b', 'c', 'ch', 'd', 'f', 'g', 'h', 'j', 'k', 'l', 'm', 'n', 'p', 'q', 'r', 's', 'sh', 't', 'w', 'x', 'y', 'z', 'zh']
+v = ['E1', 'En1', 'a1', 'ai1', 'an1', 'ang1', 'ao1', 'e1', 'ei1', 'en1', 'eng1', 'er1', 'i1', 'i01', 'ia1', 'ian1', 'iang1', 'iao1', 'ie1', 'in1', 'ing1', 'iong1', 'ir1', 'iu1', 'o1', 'ong1', 'ou1', 'u1', 'ua1', 'uai1', 'uan1', 'uang1', 'ui1', 'un1', 'uo1', 'v1', 'van1', 've1', 'vn1', 'E2', 'En2', 'a2', 'ai2', 'an2', 'ang2', 'ao2', 'e2', 'ei2', 'en2', 'eng2', 'er2', 'i2', 'i02', 'ia2', 'ian2', 'iang2', 'iao2', 'ie2', 'in2', 'ing2', 'iong2', 'ir2', 'iu2', 'o2', 'ong2', 'ou2', 'u2', 'ua2', 'uai2', 'uan2', 'uang2', 'ui2', 'un2', 'uo2', 'v2', 'van2', 've2', 'vn2', 'E3', 'En3', 'a3', 'ai3', 'an3', 'ang3', 'ao3', 'e3', 'ei3', 'en3', 'eng3', 'er3', 'i3', 'i03', 'ia3', 'ian3', 'iang3', 'iao3', 'ie3', 'in3', 'ing3', 'iong3', 'ir3', 'iu3', 'o3', 'ong3', 'ou3', 'u3', 'ua3', 'uai3', 'uan3', 'uang3', 'ui3', 'un3', 'uo3', 'v3', 'van3', 've3', 'vn3', 'E4', 'En4', 'a4', 'ai4', 'an4', 'ang4', 'ao4', 'e4', 'ei4', 'en4', 'eng4', 'er4', 'i4', 'i04', 'ia4', 'ian4', 'iang4', 'iao4', 'ie4', 'in4', 'ing4', 'iong4', 'ir4', 'iu4', 'o4', 'ong4', 'ou4', 'u4', 'ua4', 'uai4', 'uan4', 'uang4', 'ui4', 'un4', 'uo4', 'v4', 'van4', 've4', 'vn4', 'E5', 'En5', 'a5', 'ai5', 'an5', 'ang5', 'ao5', 'e5', 'ei5', 'en5', 'eng5', 'er5', 'i5', 'i05', 'ia5', 'ian5', 'iang5', 'iao5', 'ie5', 'in5', 'ing5', 'iong5', 'ir5', 'iu5', 'o5', 'ong5', 'ou5', 'u5', 'ua5', 'uai5', 'uan5', 'uang5', 'ui5', 'un5', 'uo5', 'v5', 'van5', 've5', 'vn5']
+
+v_without_tone = ['E', 'En', 'a', 'ai', 'an', 'ang', 'ao', 'e', 'ei', 'en', 'eng', 'er', 'i', 'i0', 'ia', 'ian', 'iang', 'iao', 'ie', 'in', 'ing', 'iong', 'ir', 'iu', 'o', 'ong', 'ou', 'u', 'ua', 'uai', 'uan', 'uang', 'ui', 'un', 'uo', 'v', 'van', 've', 'vn']
+
+# japanese
+ja_symbols = ['I', 'N', 'U', 'a', 'b', 'by', 'ch', 'cl', 'd', 'dy', 'e', 'f', 'g', 'gy', 'h', 'hy', 'i', 'j', 'k', 'ky',
+              'm', 'my', 'n', 'ny', 'o', 'p', 'py', 'r', 'ry', 's', 'sh', 't', 'ts', 'u', 'v', 'w', 'y', 'z']
+
+arpa = {'AH0', 'S', 'AH1', 'EY2', 'AE2', 'EH0', 'OW2', 'UH0', 'NG', 'B', 'G', 'AY0', 'M', 'AA0', 'F', 'AO0', 'ER2', 'UH1', 'IY1', 'AH2', 'DH', 'IY0', 'EY1', 'IH0', 'K', 'N', 'W', 'IY2', 'T', 'AA1', 'ER1', 'EH2', 'OY0', 'UH2', 'UW1', 'Z', 'AW2', 'AW1', 'V', 'UW2', 'AA2', 'ER', 'AW0', 'UW0', 'R', 'OW1', 'EH1', 'ZH', 'AE0', 'IH2', 'IH', 'Y', 'JH', 'P', 'AY1', 'EY0', 'OY2', 'TH', 'HH', 'D', 'ER0', 'CH', 'AO1', 'AE1', 'AO2', 'OY1', 'AY2', 'IH1', 'OW0', 'L', 'SH'}
+
+symbols = [pad] + c + v + ja_symbols + pu_symbols + list(arpa)
+symbols = sorted(set(symbols))
+if __name__ == '__main__':
+    print(len(symbols))
\ No newline at end of file
diff --git a/text/tone_sandhi.py b/text/tone_sandhi.py
new file mode 100644
index 0000000000000000000000000000000000000000..bf3893fbd5c8245fa3ccd38c239f1496f648e6c7
--- /dev/null
+++ b/text/tone_sandhi.py
@@ -0,0 +1,358 @@
+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from typing import List
+from typing import Tuple
+
+import jieba
+from pypinyin import lazy_pinyin
+from pypinyin import Style
+
+
+class ToneSandhi():
+    def __init__(self):
+        self.must_neural_tone_words = {
+            '麻烦', '麻利', '鸳鸯', '高粱', '骨头', '骆驼', '马虎', '首饰', '馒头', '馄饨', '风筝',
+            '难为', '队伍', '阔气', '闺女', '门道', '锄头', '铺盖', '铃铛', '铁匠', '钥匙', '里脊',
+            '里头', '部分', '那么', '道士', '造化', '迷糊', '连累', '这么', '这个', '运气', '过去',
+            '软和', '转悠', '踏实', '跳蚤', '跟头', '趔趄', '财主', '豆腐', '讲究', '记性', '记号',
+            '认识', '规矩', '见识', '裁缝', '补丁', '衣裳', '衣服', '衙门', '街坊', '行李', '行当',
+            '蛤蟆', '蘑菇', '薄荷', '葫芦', '葡萄', '萝卜', '荸荠', '苗条', '苗头', '苍蝇', '芝麻',
+            '舒服', '舒坦', '舌头', '自在', '膏药', '脾气', '脑袋', '脊梁', '能耐', '胳膊', '胭脂',
+            '胡萝', '胡琴', '胡同', '聪明', '耽误', '耽搁', '耷拉', '耳朵', '老爷', '老实', '老婆',
+            '老头', '老太', '翻腾', '罗嗦', '罐头', '编辑', '结实', '红火', '累赘', '糨糊', '糊涂',
+            '精神', '粮食', '簸箕', '篱笆', '算计', '算盘', '答应', '笤帚', '笑语', '笑话', '窟窿',
+            '窝囊', '窗户', '稳当', '稀罕', '称呼', '秧歌', '秀气', '秀才', '福气', '祖宗', '砚台',
+            '码头', '石榴', '石头', '石匠', '知识', '眼睛', '眯缝', '眨巴', '眉毛', '相声', '盘算',
+            '白净', '痢疾', '痛快', '疟疾', '疙瘩', '疏忽', '畜生', '生意', '甘蔗', '琵琶', '琢磨',
+            '琉璃', '玻璃', '玫瑰', '玄乎', '狐狸', '状元', '特务', '牲口', '牙碜', '牌楼', '爽快',
+            '爱人', '热闹', '烧饼', '烟筒', '烂糊', '点心', '炊帚', '灯笼', '火候', '漂亮', '滑溜',
+            '溜达', '温和', '清楚', '消息', '浪头', '活泼', '比方', '正经', '欺负', '模糊', '槟榔',
+            '棺材', '棒槌', '棉花', '核桃', '栅栏', '柴火', '架势', '枕头', '枇杷', '机灵', '本事',
+            '木头', '木匠', '朋友', '月饼', '月亮', '暖和', '明白', '时候', '新鲜', '故事', '收拾',
+            '收成', '提防', '挖苦', '挑剔', '指甲', '指头', '拾掇', '拳头', '拨弄', '招牌', '招呼',
+            '抬举', '护士', '折腾', '扫帚', '打量', '打算', '打点', '打扮', '打听', '打发', '扎实',
+            '扁担', '戒指', '懒得', '意识', '意思', '情形', '悟性', '怪物', '思量', '怎么', '念头',
+            '念叨', '快活', '忙活', '志气', '心思', '得罪', '张罗', '弟兄', '开通', '应酬', '庄稼',
+            '干事', '帮手', '帐篷', '希罕', '师父', '师傅', '巴结', '巴掌', '差事', '工夫', '岁数',
+            '屁股', '尾巴', '少爷', '小气', '小伙', '将就', '对头', '对付', '寡妇', '家伙', '客气',
+            '实在', '官司', '学问', '学生', '字号', '嫁妆', '媳妇', '媒人', '婆家', '娘家', '委屈',
+            '姑娘', '姐夫', '妯娌', '妥当', '妖精', '奴才', '女婿', '头发', '太阳', '大爷', '大方',
+            '大意', '大夫', '多少', '多么', '外甥', '壮实', '地道', '地方', '在乎', '困难', '嘴巴',
+            '嘱咐', '嘟囔', '嘀咕', '喜欢', '喇嘛', '喇叭', '商量', '唾沫', '哑巴', '哈欠', '哆嗦',
+            '咳嗽', '和尚', '告诉', '告示', '含糊', '吓唬', '后头', '名字', '名堂', '合同', '吆喝',
+            '叫唤', '口袋', '厚道', '厉害', '千斤', '包袱', '包涵', '匀称', '勤快', '动静', '动弹',
+            '功夫', '力气', '前头', '刺猬', '刺激', '别扭', '利落', '利索', '利害', '分析', '出息',
+            '凑合', '凉快', '冷战', '冤枉', '冒失', '养活', '关系', '先生', '兄弟', '便宜', '使唤',
+            '佩服', '作坊', '体面', '位置', '似的', '伙计', '休息', '什么', '人家', '亲戚', '亲家',
+            '交情', '云彩', '事情', '买卖', '主意', '丫头', '丧气', '两口', '东西', '东家', '世故',
+            '不由', '不在', '下水', '下巴', '上头', '上司', '丈夫', '丈人', '一辈', '那个', '菩萨',
+            '父亲', '母亲', '咕噜', '邋遢', '费用', '冤家', '甜头', '介绍', '荒唐', '大人', '泥鳅',
+            '幸福', '熟悉', '计划', '扑腾', '蜡烛', '姥爷', '照顾', '喉咙', '吉他', '弄堂', '蚂蚱',
+            '凤凰', '拖沓', '寒碜', '糟蹋', '倒腾', '报复', '逻辑', '盘缠', '喽啰', '牢骚', '咖喱',
+            '扫把', '惦记'
+        }
+        self.must_not_neural_tone_words = {
+            "男子", "女子", "分子", "原子", "量子", "莲子", "石子", "瓜子", "电子", "人人", "虎虎"
+        }
+        self.punc = "：，；。？！“”‘’':,;.?!"
+
+    # the meaning of jieba pos tag: https://blog.csdn.net/weixin_44174352/article/details/113731041
+    # e.g.
+    # word: "家里"
+    # pos: "s"
+    # finals: ['ia1', 'i3']
+    def _neural_sandhi(self, word: str, pos: str,
+                       finals: List[str]) -> List[str]:
+
+        # reduplication words for n. and v. e.g. 奶奶, 试试, 旺旺
+        for j, item in enumerate(word):
+            if j - 1 >= 0 and item == word[j - 1] and pos[0] in {
+                    "n", "v", "a"
+            } and word not in self.must_not_neural_tone_words:
+                finals[j] = finals[j][:-1] + "5"
+        ge_idx = word.find("个")
+        if len(word) >= 1 and word[-1] in "吧呢哈啊呐噻嘛吖嗨呐哦哒额滴哩哟喽啰耶喔诶":
+            finals[-1] = finals[-1][:-1] + "5"
+        elif len(word) >= 1 and word[-1] in "的地得":
+            finals[-1] = finals[-1][:-1] + "5"
+        # e.g. 走了, 看着, 去过
+        elif len(word) == 1 and word in "了着过" and pos in {"ul", "uz", "ug"}:
+            finals[-1] = finals[-1][:-1] + "5"
+        elif len(word) > 1 and word[-1] in "们子" and pos in {
+                "r", "n"
+        } and word not in self.must_not_neural_tone_words:
+            finals[-1] = finals[-1][:-1] + "5"
+        # e.g. 桌上, 地下, 家里
+        elif len(word) > 1 and word[-1] in "上下里" and pos in {"s", "l", "f"}:
+            finals[-1] = finals[-1][:-1] + "5"
+        # e.g. 上来, 下去
+        elif len(word) > 1 and word[-1] in "来去" and word[-2] in "上下进出回过起开":
+            finals[-1] = finals[-1][:-1] + "5"
+        # 个做量词
+        elif (ge_idx >= 1 and
+              (word[ge_idx - 1].isnumeric() or
+               word[ge_idx - 1] in "几有两半多各整每做是")) or word == '个':
+            finals[ge_idx] = finals[ge_idx][:-1] + "5"
+        else:
+            if word in self.must_neural_tone_words or word[
+                    -2:] in self.must_neural_tone_words:
+                finals[-1] = finals[-1][:-1] + "5"
+
+        word_list = self._split_word(word)
+        finals_list = [finals[:len(word_list[0])], finals[len(word_list[0]):]]
+        for i, word in enumerate(word_list):
+            # conventional neural in Chinese
+            if word in self.must_neural_tone_words or word[
+                    -2:] in self.must_neural_tone_words:
+                finals_list[i][-1] = finals_list[i][-1][:-1] + "5"
+        finals = sum(finals_list, [])
+        return finals
+
+    def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]:
+        # e.g. 看不懂
+        if len(word) == 3 and word[1] == "不":
+            finals[1] = finals[1][:-1] + "5"
+        else:
+            for i, char in enumerate(word):
+                # "不" before tone4 should be bu2, e.g. 不怕
+                if char == "不" and i + 1 < len(word) and finals[i +
+                                                                1][-1] == "4":
+                    finals[i] = finals[i][:-1] + "2"
+        return finals
+
+    def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]:
+        # "一" in number sequences, e.g. 一零零, 二一零
+        if word.find("一") != -1 and all(
+            [item.isnumeric() for item in word if item != "一"]):
+            return finals
+        # "一" between reduplication words shold be yi5, e.g. 看一看
+        elif len(word) == 3 and word[1] == "一" and word[0] == word[-1]:
+            finals[1] = finals[1][:-1] + "5"
+        # when "一" is ordinal word, it should be yi1
+        elif word.startswith("第一"):
+            finals[1] = finals[1][:-1] + "1"
+        else:
+            for i, char in enumerate(word):
+                if char == "一" and i + 1 < len(word):
+                    # "一" before tone4 should be yi2, e.g. 一段
+                    if finals[i + 1][-1] == "4":
+                        finals[i] = finals[i][:-1] + "2"
+                    # "一" before non-tone4 should be yi4, e.g. 一天
+                    else:
+                        # "一" 后面如果是标点，还读一声
+                        if word[i + 1] not in self.punc:
+                            finals[i] = finals[i][:-1] + "4"
+        return finals
+
+    def _split_word(self, word: str) -> List[str]:
+        word_list = jieba.cut_for_search(word)
+        word_list = sorted(word_list, key=lambda i: len(i), reverse=False)
+        first_subword = word_list[0]
+        first_begin_idx = word.find(first_subword)
+        if first_begin_idx == 0:
+            second_subword = word[len(first_subword):]
+            new_word_list = [first_subword, second_subword]
+        else:
+            second_subword = word[:-len(first_subword)]
+            new_word_list = [second_subword, first_subword]
+        return new_word_list
+
+    def _three_sandhi(self, word: str, finals: List[str]) -> List[str]:
+        if len(word) == 2 and self._all_tone_three(finals):
+            finals[0] = finals[0][:-1] + "2"
+        elif len(word) == 3:
+            word_list = self._split_word(word)
+            if self._all_tone_three(finals):
+                #  disyllabic + monosyllabic, e.g. 蒙古/包
+                if len(word_list[0]) == 2:
+                    finals[0] = finals[0][:-1] + "2"
+                    finals[1] = finals[1][:-1] + "2"
+                #  monosyllabic + disyllabic, e.g. 纸/老虎
+                elif len(word_list[0]) == 1:
+                    finals[1] = finals[1][:-1] + "2"
+            else:
+                finals_list = [
+                    finals[:len(word_list[0])], finals[len(word_list[0]):]
+                ]
+                if len(finals_list) == 2:
+                    for i, sub in enumerate(finals_list):
+                        # e.g. 所有/人
+                        if self._all_tone_three(sub) and len(sub) == 2:
+                            finals_list[i][0] = finals_list[i][0][:-1] + "2"
+                        # e.g. 好/喜欢
+                        elif i == 1 and not self._all_tone_three(sub) and finals_list[i][0][-1] == "3" and \
+                                finals_list[0][-1][-1] == "3":
+
+                            finals_list[0][-1] = finals_list[0][-1][:-1] + "2"
+                        finals = sum(finals_list, [])
+        # split idiom into two words who's length is 2
+        elif len(word) == 4:
+            finals_list = [finals[:2], finals[2:]]
+            finals = []
+            for sub in finals_list:
+                if self._all_tone_three(sub):
+                    sub[0] = sub[0][:-1] + "2"
+                finals += sub
+
+        return finals
+
+    def _all_tone_three(self, finals: List[str]) -> bool:
+        return all(x[-1] == "3" for x in finals)
+
+    # merge "不" and the word behind it
+    # if don't merge, "不" sometimes appears alone according to jieba, which may occur sandhi error
+    def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
+        new_seg = []
+        last_word = ""
+        for word, pos in seg:
+            if last_word == "不":
+                word = last_word + word
+            if word != "不":
+                new_seg.append((word, pos))
+            last_word = word[:]
+        if last_word == "不":
+            new_seg.append((last_word, 'd'))
+            last_word = ""
+        return new_seg
+
+    # function 1: merge "一" and reduplication words in it's left and right, e.g. "听","一","听" ->"听一听"
+    # function 2: merge single  "一" and the word behind it
+    # if don't merge, "一" sometimes appears alone according to jieba, which may occur sandhi error
+    # e.g.
+    # input seg: [('听', 'v'), ('一', 'm'), ('听', 'v')]
+    # output seg: [['听一听', 'v']]
+    def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
+        new_seg = []
+        # function 1
+        for i, (word, pos) in enumerate(seg):
+            if i - 1 >= 0 and word == "一" and i + 1 < len(seg) and seg[i - 1][
+                    0] == seg[i + 1][0] and seg[i - 1][1] == "v":
+                new_seg[i - 1][0] = new_seg[i - 1][0] + "一" + new_seg[i - 1][0]
+            else:
+                if i - 2 >= 0 and seg[i - 1][0] == "一" and seg[i - 2][
+                        0] == word and pos == "v":
+                    continue
+                else:
+                    new_seg.append([word, pos])
+        seg = new_seg
+        new_seg = []
+        # function 2
+        for i, (word, pos) in enumerate(seg):
+            if new_seg and new_seg[-1][0] == "一":
+                new_seg[-1][0] = new_seg[-1][0] + word
+            else:
+                new_seg.append([word, pos])
+        return new_seg
+
+    # the first and the second words are all_tone_three
+    def _merge_continuous_three_tones(
+            self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
+        new_seg = []
+        sub_finals_list = [
+            lazy_pinyin(
+                word, neutral_tone_with_five=True, style=Style.FINALS_TONE3)
+            for (word, pos) in seg
+        ]
+        assert len(sub_finals_list) == len(seg)
+        merge_last = [False] * len(seg)
+        for i, (word, pos) in enumerate(seg):
+            if i - 1 >= 0 and self._all_tone_three(
+                    sub_finals_list[i - 1]) and self._all_tone_three(
+                        sub_finals_list[i]) and not merge_last[i - 1]:
+                # if the last word is reduplication, not merge, because reduplication need to be _neural_sandhi
+                if not self._is_reduplication(seg[i - 1][0]) and len(
+                        seg[i - 1][0]) + len(seg[i][0]) <= 3:
+                    new_seg[-1][0] = new_seg[-1][0] + seg[i][0]
+                    merge_last[i] = True
+                else:
+                    new_seg.append([word, pos])
+            else:
+                new_seg.append([word, pos])
+
+        return new_seg
+
+    def _is_reduplication(self, word: str) -> bool:
+        return len(word) == 2 and word[0] == word[1]
+
+    # the last char of first word and the first char of second word is tone_three
+    def _merge_continuous_three_tones_2(
+            self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
+        new_seg = []
+        sub_finals_list = [
+            lazy_pinyin(
+                word, neutral_tone_with_five=True, style=Style.FINALS_TONE3)
+            for (word, pos) in seg
+        ]
+        assert len(sub_finals_list) == len(seg)
+        merge_last = [False] * len(seg)
+        for i, (word, pos) in enumerate(seg):
+            if i - 1 >= 0 and sub_finals_list[i - 1][-1][-1] == "3" and sub_finals_list[i][0][-1] == "3" and not \
+                    merge_last[i - 1]:
+                # if the last word is reduplication, not merge, because reduplication need to be _neural_sandhi
+                if not self._is_reduplication(seg[i - 1][0]) and len(
+                        seg[i - 1][0]) + len(seg[i][0]) <= 3:
+                    new_seg[-1][0] = new_seg[-1][0] + seg[i][0]
+                    merge_last[i] = True
+                else:
+                    new_seg.append([word, pos])
+            else:
+                new_seg.append([word, pos])
+        return new_seg
+
+    def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
+        new_seg = []
+        for i, (word, pos) in enumerate(seg):
+            if i - 1 >= 0 and word == "儿" and seg[i-1][0] != "#":
+                new_seg[-1][0] = new_seg[-1][0] + seg[i][0]
+            else:
+                new_seg.append([word, pos])
+        return new_seg
+
+    def _merge_reduplication(
+            self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
+        new_seg = []
+        for i, (word, pos) in enumerate(seg):
+            if new_seg and word == new_seg[-1][0]:
+                new_seg[-1][0] = new_seg[-1][0] + seg[i][0]
+            else:
+                new_seg.append([word, pos])
+        return new_seg
+
+    def pre_merge_for_modify(
+            self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
+        seg = self._merge_bu(seg)
+        try:
+            seg = self._merge_yi(seg)
+        except:
+            print("_merge_yi failed")
+        seg = self._merge_reduplication(seg)
+        try:
+            seg = self._merge_continuous_three_tones(seg)
+        except:
+            print("_merge_continuous_three_tones failed")
+        try:
+            seg = self._merge_continuous_three_tones_2(seg)
+        except:
+            print("_merge_continuous_three_tones_2 failed")
+
+        seg = self._merge_er(seg)
+        return seg
+
+    def modified_tone(self, word: str, pos: str,
+                      finals: List[str]) -> List[str]:
+        finals = self._bu_sandhi(word, finals)
+        finals = self._yi_sandhi(word, finals)
+        finals = self._neural_sandhi(word, pos, finals)
+        finals = self._three_sandhi(word, finals)
+        return finals
diff --git a/utils.py b/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..e3ed89bf7762e4fd9e91b57c4c5c04bbfebbf4ad
--- /dev/null
+++ b/utils.py
@@ -0,0 +1,298 @@
+import os
+import glob
+import sys
+import argparse
+import logging
+import json
+import subprocess
+import traceback
+
+import librosa
+import numpy as np
+from scipy.io.wavfile import read
+import torch
+import logging
+logging.getLogger('numba').setLevel(logging.ERROR)
+logging.getLogger('matplotlib').setLevel(logging.ERROR)
+
+MATPLOTLIB_FLAG = False
+
+logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
+logger = logging
+
+
+def load_checkpoint(checkpoint_path, model, optimizer=None, skip_optimizer=False):
+    assert os.path.isfile(checkpoint_path)
+    checkpoint_dict = torch.load(checkpoint_path, map_location='cpu')
+    iteration = checkpoint_dict['iteration']
+    learning_rate = checkpoint_dict['learning_rate']
+    if optimizer is not None and not skip_optimizer and checkpoint_dict['optimizer'] is not None:
+        optimizer.load_state_dict(checkpoint_dict['optimizer'])
+    saved_state_dict = checkpoint_dict['model']
+    if hasattr(model, 'module'):
+        state_dict = model.module.state_dict()
+    else:
+        state_dict = model.state_dict()
+    new_state_dict = {}
+    for k, v in state_dict.items():
+        try:
+            # assert "quantizer" not in k
+            # print("load", k)
+            new_state_dict[k] = saved_state_dict[k]
+            assert saved_state_dict[k].shape == v.shape, (saved_state_dict[k].shape, v.shape)
+        except:
+            traceback.print_exc()
+            print("error, %s is not in the checkpoint" % k)#shape不对也会，比如text_embedding当cleaner修改时
+            new_state_dict[k] = v
+    if hasattr(model, 'module'):
+        model.module.load_state_dict(new_state_dict)
+    else:
+        model.load_state_dict(new_state_dict)
+    print("load ")
+    logger.info("Loaded checkpoint '{}' (iteration {})".format(
+        checkpoint_path, iteration))
+    return model, optimizer, learning_rate, iteration
+
+
+def save_checkpoint(model, optimizer, learning_rate, iteration, checkpoint_path):
+    logger.info("Saving model and optimizer state at iteration {} to {}".format(
+        iteration, checkpoint_path))
+    if hasattr(model, 'module'):
+        state_dict = model.module.state_dict()
+    else:
+        state_dict = model.state_dict()
+    torch.save({'model': state_dict,
+                'iteration': iteration,
+                'optimizer': optimizer.state_dict(),
+                'learning_rate': learning_rate}, checkpoint_path)
+
+
+def summarize(writer, global_step, scalars={}, histograms={}, images={}, audios={}, audio_sampling_rate=22050):
+    for k, v in scalars.items():
+        writer.add_scalar(k, v, global_step)
+    for k, v in histograms.items():
+        writer.add_histogram(k, v, global_step)
+    for k, v in images.items():
+        writer.add_image(k, v, global_step, dataformats='HWC')
+    for k, v in audios.items():
+        writer.add_audio(k, v, global_step, audio_sampling_rate)
+
+
+def latest_checkpoint_path(dir_path, regex="G_*.pth"):
+    f_list = glob.glob(os.path.join(dir_path, regex))
+    f_list.sort(key=lambda f: int("".join(filter(str.isdigit, f))))
+    x = f_list[-1]
+    print(x)
+    return x
+
+
+def plot_spectrogram_to_numpy(spectrogram):
+    global MATPLOTLIB_FLAG
+    if not MATPLOTLIB_FLAG:
+        import matplotlib
+        matplotlib.use("Agg")
+        MATPLOTLIB_FLAG = True
+        mpl_logger = logging.getLogger('matplotlib')
+        mpl_logger.setLevel(logging.WARNING)
+    import matplotlib.pylab as plt
+    import numpy as np
+
+    fig, ax = plt.subplots(figsize=(10, 2))
+    im = ax.imshow(spectrogram, aspect="auto", origin="lower",
+                   interpolation='none')
+    plt.colorbar(im, ax=ax)
+    plt.xlabel("Frames")
+    plt.ylabel("Channels")
+    plt.tight_layout()
+
+    fig.canvas.draw()
+    data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
+    data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
+    plt.close()
+    return data
+
+
+def plot_alignment_to_numpy(alignment, info=None):
+    global MATPLOTLIB_FLAG
+    if not MATPLOTLIB_FLAG:
+        import matplotlib
+        matplotlib.use("Agg")
+        MATPLOTLIB_FLAG = True
+        mpl_logger = logging.getLogger('matplotlib')
+        mpl_logger.setLevel(logging.WARNING)
+    import matplotlib.pylab as plt
+    import numpy as np
+
+    fig, ax = plt.subplots(figsize=(6, 4))
+    im = ax.imshow(alignment.transpose(), aspect='auto', origin='lower',
+                   interpolation='none')
+    fig.colorbar(im, ax=ax)
+    xlabel = 'Decoder timestep'
+    if info is not None:
+        xlabel += '\n\n' + info
+    plt.xlabel(xlabel)
+    plt.ylabel('Encoder timestep')
+    plt.tight_layout()
+
+    fig.canvas.draw()
+    data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
+    data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
+    plt.close()
+    return data
+
+
+def load_wav_to_torch(full_path):
+    data, sampling_rate = librosa.load(full_path, sr=None)
+    return torch.FloatTensor(data), sampling_rate
+
+
+def load_filepaths_and_text(filename, split="|"):
+    with open(filename, encoding='utf-8') as f:
+        filepaths_and_text = [line.strip().split(split) for line in f]
+    return filepaths_and_text
+
+
+def get_hparams(init=True, stage=1):
+    parser = argparse.ArgumentParser()
+    parser.add_argument('-c', '--config', type=str, default="./configs/s2.json",help='JSON file for configuration')
+    parser.add_argument('-p', '--pretrain', type=str, required=False,default=None,help='pretrain dir')
+    parser.add_argument('-rs', '--resume_step', type=int, required=False,default=None,help='resume step')
+    # parser.add_argument('-e', '--exp_dir', type=str, required=False,default=None,help='experiment directory')
+    # parser.add_argument('-g', '--pretrained_s2G', type=str, required=False,default=None,help='pretrained sovits gererator weights')
+    # parser.add_argument('-d', '--pretrained_s2D', type=str, required=False,default=None,help='pretrained sovits discriminator weights')
+
+    args = parser.parse_args()
+
+    config_path = args.config
+    with open(config_path, "r") as f:
+        data = f.read()
+    config = json.loads(data)
+
+    hparams = HParams(**config)
+    hparams.pretrain = args.pretrain
+    hparams.resume_step = args.resume_step
+    # hparams.data.exp_dir = args.exp_dir
+    if stage ==1:
+        model_dir = hparams.s1_ckpt_dir
+    else:
+        model_dir = hparams.s2_ckpt_dir
+    config_save_path = os.path.join(model_dir, "config.json")
+
+    if not os.path.exists(model_dir):
+        os.makedirs(model_dir)
+
+    with open(config_save_path, "w") as f:
+        f.write(data)
+    return hparams
+
+
+
+def clean_checkpoints(path_to_models='logs/44k/', n_ckpts_to_keep=2, sort_by_time=True):
+    """Freeing up space by deleting saved ckpts
+
+  Arguments:
+  path_to_models    --  Path to the model directory
+  n_ckpts_to_keep   --  Number of ckpts to keep, excluding G_0.pth and D_0.pth
+  sort_by_time      --  True -> chronologically delete ckpts
+                        False -> lexicographically delete ckpts
+  """
+    import re
+    ckpts_files = [f for f in os.listdir(path_to_models) if os.path.isfile(os.path.join(path_to_models, f))]
+    name_key = (lambda _f: int(re.compile('._(\d+)\.pth').match(_f).group(1)))
+    time_key = (lambda _f: os.path.getmtime(os.path.join(path_to_models, _f)))
+    sort_key = time_key if sort_by_time else name_key
+    x_sorted = lambda _x: sorted([f for f in ckpts_files if f.startswith(_x) and not f.endswith('_0.pth')],
+                                 key=sort_key)
+    to_del = [os.path.join(path_to_models, fn) for fn in
+              (x_sorted('G')[:-n_ckpts_to_keep] + x_sorted('D')[:-n_ckpts_to_keep])]
+    del_info = lambda fn: logger.info(f".. Free up space by deleting ckpt {fn}")
+    del_routine = lambda x: [os.remove(x), del_info(x)]
+    rs = [del_routine(fn) for fn in to_del]
+
+def get_hparams_from_dir(model_dir):
+    config_save_path = os.path.join(model_dir, "config.json")
+    with open(config_save_path, "r") as f:
+        data = f.read()
+    config = json.loads(data)
+
+    hparams = HParams(**config)
+    hparams.model_dir = model_dir
+    return hparams
+
+
+def get_hparams_from_file(config_path):
+    with open(config_path, "r") as f:
+        data = f.read()
+    config = json.loads(data)
+
+    hparams = HParams(**config)
+    return hparams
+
+def check_git_hash(model_dir):
+    source_dir = os.path.dirname(os.path.realpath(__file__))
+    if not os.path.exists(os.path.join(source_dir, ".git")):
+        logger.warn("{} is not a git repository, therefore hash value comparison will be ignored.".format(
+            source_dir
+        ))
+        return
+
+    cur_hash = subprocess.getoutput("git rev-parse HEAD")
+
+    path = os.path.join(model_dir, "githash")
+    if os.path.exists(path):
+        saved_hash = open(path).read()
+        if saved_hash != cur_hash:
+            logger.warn("git hash values are different. {}(saved) != {}(current)".format(
+                saved_hash[:8], cur_hash[:8]))
+    else:
+        open(path, "w").write(cur_hash)
+
+
+def get_logger(model_dir, filename="train.log"):
+    global logger
+    logger = logging.getLogger(os.path.basename(model_dir))
+    logger.setLevel(logging.DEBUG)
+
+    formatter = logging.Formatter("%(asctime)s\t%(name)s\t%(levelname)s\t%(message)s")
+    if not os.path.exists(model_dir):
+        os.makedirs(model_dir)
+    h = logging.FileHandler(os.path.join(model_dir, filename))
+    h.setLevel(logging.DEBUG)
+    h.setFormatter(formatter)
+    logger.addHandler(h)
+    return logger
+
+
+class HParams():
+    def __init__(self, **kwargs):
+        for k, v in kwargs.items():
+            if type(v) == dict:
+                v = HParams(**v)
+            self[k] = v
+
+    def keys(self):
+        return self.__dict__.keys()
+
+    def items(self):
+        return self.__dict__.items()
+
+    def values(self):
+        return self.__dict__.values()
+
+    def __len__(self):
+        return len(self.__dict__)
+
+    def __getitem__(self, key):
+        return getattr(self, key)
+
+    def __setitem__(self, key, value):
+        return setattr(self, key, value)
+
+    def __contains__(self, key):
+        return key in self.__dict__
+
+    def __repr__(self):
+        return self.__dict__.__repr__()
+
+if __name__ == '__main__':
+    print(load_wav_to_torch('/home/fish/wenetspeech/dataset_vq/Y0000022499_wHFSeHEx9CM/S00261.flac'))
\ No newline at end of file