Mit model (#28)

* Use new model

* Black fixes

* Fix examples

* Use GPU when available

* Better handling of downloads

* Bump requirements

* Add link to guide

* Delete LICENSE file

* Add link to datasets

* Add examples

.gitignore

@@ -134,6 +134,7 @@ dmypy.json
 # model files
 *.pth.tar
 *.pth
+*.ark
 
 # gradio
 gradio_queue.db

LICENSE.models

@@ -1,619 +0,0 @@
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-IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
-ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
-
-  16. Limitation of Liability.
-
-  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
-WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
-THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
-GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
-USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
-DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
-PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
-EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
-SUCH DAMAGES.
-
-  17. Interpretation of Sections 15 and 16.
-
-  If the disclaimer of warranty and limitation of liability provided
-above cannot be given local legal effect according to their terms,
-reviewing courts shall apply local law that most closely approximates
-an absolute waiver of all civil liability in connection with the
-Program, unless a warranty or assumption of liability accompanies a
-copy of the Program in return for a fee.

README.md

@@ -4,8 +4,8 @@ emoji: 🐌
 colorFrom: blue
 colorTo: yellow
 sdk: gradio
-sdk_version : 3.12
-python_version: 3.9
+sdk_version : 3.14
+python_version: 3.10
 app_file: app.py
 pinned: false
 ---
@@ -20,53 +20,48 @@ Ukrainian TTS (text-to-speech) using ESPNET.
 [![chat](https://img.shields.io/badge/chat-Telegram-blue)](https://t.me/speech_recognition_uk)
 
 Link to online demo -> [https://huggingface.co/spaces/robinhad/ukrainian-tts](https://huggingface.co/spaces/robinhad/ukrainian-tts)  
-Note: online demo saves user input to improve user experience, by using it you give your consent to analyze this data.   
+Note: online demo saves user input to improve user experience; by using it, you consent to analyze this data.   
 Link to source code and models -> [https://github.com/robinhad/ukrainian-tts](https://github.com/robinhad/ukrainian-tts)  
 Telegram bot -> [https://t.me/uk_tts_bot](https://t.me/uk_tts_bot)  
 
-Code is licensed under `MIT License`, models are under `GNU GPL v3 License`. 
-
 # Features ⚙️
 - Completely offline
 - Multiple voices
 - Automatic stress with priority queue: `user-defined` > `dictionary` > `model`
 - Control speech speed
-- Python package works on Windows, Mac, Linux
+- Python package works on Windows, Mac (x86/M1), Linux(x86/ARM)
 - Inference on mobile devices (inference models through `espnet_onnx` without cleaners)
 
 
 # Support ❤️
 If you like my work, please support ❤️ -> [https://send.monobank.ua/jar/48iHq4xAXm](https://send.monobank.ua/jar/48iHq4xAXm)  
-For collaboration and question please contact me here:  
+For collaboration and questions please contact me here:  
 [Telegram https://t.me/robinhad](https://t.me/robinhad)  
 [Twitter https://twitter.com/robinhad](https://twitter.com/robinhad)  
 You're welcome to join UA Speech Recognition and Synthesis community: [Telegram https://t.me/speech_recognition_uk](https://t.me/speech_recognition_uk)
 # Examples 🤖
 
+`Tetiana (female)`:
 
-`Olena (female)`:
+https://user-images.githubusercontent.com/5759207/224504324-d8236cad-7302-4dfd-9696-7a42b9f05fce.mp4
 
-https://user-images.githubusercontent.com/5759207/190852238-366782c1-9472-45fc-8fea-31346242f927.mp4
 
 <details>
   <summary>More voices 📢🤖</summary>
 
-`Mykyta (male)`:
-
-https://user-images.githubusercontent.com/5759207/190852232-34956a1d-77a9-42b9-b96d-39d0091e3e34.mp4
-
 `Dmytro (male)`:
 
-https://user-images.githubusercontent.com/5759207/190852251-db105567-52ba-47b5-8ec6-5053c3baac8c.mp4
+https://user-images.githubusercontent.com/5759207/224504354-f84f74d3-fa46-497c-9604-4b63ba45989f.mp4
 
-`Olha (female)`:
-
-https://user-images.githubusercontent.com/5759207/190852259-c6746172-05c4-4918-8286-a459c654eef1.mp4
 
 `Lada (female)`:
 
+https://user-images.githubusercontent.com/5759207/224504360-ec198ac2-647c-4238-99ef-b6f074d633fd.mp4
+
+
+`Mykyta (male)`:
 
-https://user-images.githubusercontent.com/5759207/190852270-7aed2db9-dc08-4a9f-8775-07b745657ca1.mp4
+https://user-images.githubusercontent.com/5759207/224504363-0227e8bf-8c1c-49ad-8602-8cbf8feaa82b.mp4
 
 </details>
 
@@ -76,13 +71,13 @@ https://user-images.githubusercontent.com/5759207/190852270-7aed2db9-dc08-4a9f-8
 See example notebook: [tts_example.ipynb](./tts_example.ipynb)  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/robinhad/ukrainian-tts/blob/main/tts_example.ipynb)
 
 # How to train: 🏋️
-TBD
+Link to guide: [training/STEPS.md](training/STEPS.md)
 
 
 # Attribution 🤝
 
 - Model training - [Yurii Paniv @robinhad](https://github.com/robinhad)   
-- Mykyta, Olena, Lada, Dmytro, Olha dataset - [Yehor Smoliakov @egorsmkv](https://github.com/egorsmkv)   
+- [Open Source Ukrainian Text-to-Speech dataset](https://github.com/egorsmkv/ukrainian-tts-datasets) - [Yehor Smoliakov @egorsmkv](https://github.com/egorsmkv)   
 - Dmytro voice - [Dmytro Chaplynskyi @dchaplinsky](https://github.com/dchaplinsky)  
 - Silence cutting using [HMM-GMM](https://github.com/proger/uk) - [Volodymyr Kyrylov @proger](https://github.com/proger)  
 - Autostress (with dictionary) using [ukrainian-word-stress](https://github.com/lang-uk/ukrainian-word-stress) - [Oleksiy Syvokon @asivokon](https://github.com/asivokon)    

app.py

@@ -38,46 +38,33 @@ if getenv("HF_API_TOKEN") is not None:
     t.start()
 
 
-class StressOption(Enum):
-    AutomaticStress = "Автоматичні наголоси (за словником) 📖"
-    AutomaticStressWithModel = "Автоматичні наголоси (за допомогою моделі) 🧮"
-
-
 class VoiceOption(Enum):
-    Olena = "Олена (жіночий) 👩"
+    Tetiana = "Тетяна (жіночий) 👩"
     Mykyta = "Микита (чоловічий) 👨"
     Lada = "Лада (жіночий) 👩"
     Dmytro = "Дмитро (чоловічий) 👨"
-    Olga = "Ольга (жіночий) 👩"
 
 
 print(f"CUDA available? {is_available()}")
 
 
-ukr_tts = TTS()
+ukr_tts = TTS(device="cuda" if is_available() else "cpu")
 
 
-def tts(text: str, voice: str, stress: str, speed: float):
+def tts(text: str, voice: str, speed: float):
     print("============================")
     print("Original text:", text)
     print("Voice", voice)
-    print("Stress:", stress)
     print("Time:", datetime.utcnow())
 
     voice_mapping = {
-        VoiceOption.Olena.value: Voices.Olena.value,
+        VoiceOption.Tetiana.value: Voices.Tetiana.value,
         VoiceOption.Mykyta.value: Voices.Mykyta.value,
         VoiceOption.Lada.value: Voices.Lada.value,
         VoiceOption.Dmytro.value: Voices.Dmytro.value,
-        VoiceOption.Olga.value: Voices.Olga.value,
-    }
-    stress_mapping = {
-        StressOption.AutomaticStress.value: Stress.Dictionary.value,
-        StressOption.AutomaticStressWithModel.value: Stress.Model.value,
     }
 
     speaker_name = voice_mapping[voice]
-    stress_selected = stress_mapping[stress]
     text_limit = 7200
     text = (
         text if len(text) < text_limit else text[0:text_limit]
@@ -85,11 +72,11 @@ def tts(text: str, voice: str, stress: str, speed: float):
 
     if getenv("HF_API_TOKEN") is not None:
         log_queue.put(
-            [text, speaker_name, stress_selected, speed, str(datetime.utcnow())]
+            [text, speaker_name, Stress.Dictionary.value, speed, str(datetime.utcnow())]
         )
 
     with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
-        _, text = ukr_tts.tts(text, speaker_name, stress_selected, fp, speed)
+        _, text = ukr_tts.tts(text, speaker_name, Stress.Dictionary.value, fp, speed)
         return fp.name, text
 
 
@@ -103,20 +90,15 @@ iface = gr.Interface(
     inputs=[
         gr.components.Textbox(
             label="Input",
-            value="Введіть, будь ласка, своє р+ечення.",
+            value="Введіть, будь ласка, своє речення.",
         ),
         gr.components.Radio(
             label="Голос",
             choices=[option.value for option in VoiceOption],
-            value=VoiceOption.Olena.value,
-        ),
-        gr.components.Radio(
-            label="Наголоси",
-            choices=[option.value for option in StressOption],
-            value=StressOption.AutomaticStress.value,
+            value=VoiceOption.Tetiana.value,
         ),
         gr.components.Slider(
-            label="Швидкість", minimum=0.5, maximum=2, value=1, step=0.1
+            label="Швидкість", minimum=0.5, maximum=2, value=1, step=0.05
         ),
     ],
     outputs=[
@@ -128,48 +110,36 @@ iface = gr.Interface(
     article=article,
     examples=[
         [
-            "Вв+едіть, будь ласка, св+оє реч+ення.",
+            "Привіт, як тебе звати?",
+            VoiceOption.Tetiana.value,
+            1,
+        ],
+        [
+            "Введіть, будь ласка, св+оє реч+ення.",
             VoiceOption.Dmytro.value,
-            StressOption.AutomaticStress.value,
             1,
         ],
         [
-            "Вв+едіть, будь ласка, св+оє реч+ення.",
+            "Введіть, будь ласка, своє речення.",
             VoiceOption.Dmytro.value,
-            StressOption.AutomaticStress.value,
             1.3,
         ],
         [
             "Введіть, будь ласка, своє речення.",
             VoiceOption.Mykyta.value,
-            StressOption.AutomaticStress.value,
             1,
         ],
         [
             "Введіть, будь ласка, своє речення.",
             VoiceOption.Mykyta.value,
-            StressOption.AutomaticStress.value,
             0.7,
         ],
-        [
-            "Введіть, будь ласка, своє речення.",
-            VoiceOption.Olena.value,
-            StressOption.AutomaticStress.value,
-            1,
-        ],
-        [
-            "Привіт, як тебе звати?",
-            VoiceOption.Olga.value,
-            StressOption.AutomaticStress.value,
-            1,
-        ],
         [
             "Договір підписано 4 квітня 1949 року.",
             VoiceOption.Lada.value,
-            StressOption.AutomaticStress.value,
-            1,
+            0.9,
         ],
     ],
 )
-iface.queue(concurrency_count=6)
+iface.queue(concurrency_count=6)  # for HF specifically
 iface.launch()

config.yaml

@@ -3,10 +3,10 @@ print_config: false
 log_level: INFO
 dry_run: false
 iterator_type: sequence
-output_dir: /mnt/tts-storage/exp/22k/tts_train_vits_raw_char
+output_dir: exp/22k/tts_train_vits_raw_char
 ngpu: 1
 seed: 3407
-num_workers: 1
+num_workers: 4
 num_att_plot: 3
 dist_backend: nccl
 dist_init_method: env://
@@ -24,7 +24,7 @@ cudnn_benchmark: false
 cudnn_deterministic: false
 collect_stats: false
 write_collected_feats: false
-max_epoch: 300
+max_epoch: 1000
 patience: null
 val_scheduler_criterion:
 - valid
@@ -65,14 +65,14 @@ freeze_param: []
 num_iters_per_epoch: null
 batch_size: 20
 valid_batch_size: null
-batch_bins: 1900000
+batch_bins: 1500000
 valid_batch_bins: null
 train_shape_file:
-- /mnt/tts-storage/exp/22k/tts_stats_raw_linear_spectrogram_char/train/text_shape.char
-- /mnt/tts-storage/exp/22k/tts_stats_raw_linear_spectrogram_char/train/speech_shape
+- exp/22k/tts_stats_raw_linear_spectrogram_char/train/text_shape.char
+- exp/22k/tts_stats_raw_linear_spectrogram_char/train/speech_shape
 valid_shape_file:
-- /mnt/tts-storage/exp/22k/tts_stats_raw_linear_spectrogram_char/valid/text_shape.char
-- /mnt/tts-storage/exp/22k/tts_stats_raw_linear_spectrogram_char/valid/speech_shape
+- exp/22k/tts_stats_raw_linear_spectrogram_char/valid/text_shape.char
+- exp/22k/tts_stats_raw_linear_spectrogram_char/valid/speech_shape
 batch_type: numel
 valid_batch_type: null
 fold_length:
@@ -91,9 +91,9 @@ train_data_path_and_name_and_type:
 -   - dump/22k/raw/tr_no_dev/wav.scp
     - speech
     - sound
--   - dump/22k/raw/tr_no_dev/utt2sid
-    - sids
-    - text_int
+-   - dump/22k/xvector/tr_no_dev/xvector.scp
+    - spembs
+    - kaldi_ark
 valid_data_path_and_name_and_type:
 -   - dump/22k/raw/dev/text
     - text
@@ -101,13 +101,15 @@ valid_data_path_and_name_and_type:
 -   - dump/22k/raw/dev/wav.scp
     - speech
     - sound
--   - dump/22k/raw/dev/utt2sid
-    - sids
-    - text_int
+-   - dump/22k/xvector/dev/xvector.scp
+    - spembs
+    - kaldi_ark
 allow_variable_data_keys: false
 max_cache_size: 0.0
 max_cache_fd: 32
 valid_max_cache_size: null
+exclude_weight_decay: false
+exclude_weight_decay_conf: {}
 optim: adamw
 optim_conf:
     lr: 0.0002
@@ -141,51 +143,46 @@ token_list:
 - и
 - н
 - в
-- і
-- т
 - е
+- т
+- і
 - с
 - р
+- д
 - л
 - у
-- д
 - к
 - м
 - п
+- .
 - я
 - з
 - ','
 - б
 - ь
-- г
 - ч
+- г
 - й
-- х
 - ж
+- х
 - ш
 - ю
 - ц
 - щ
-- —
-- є
-- ї
 - '?'
-- .
-- ф
-- «
-- »
+- '-'
+- ї
+- є
 - '!'
 - ''''
+- ф
+- '"'
 - ':'
-- …
-- '-'
 - ґ
-- ―
-- –
-- '"'
-- ;
-- “
-- ”
+- (
+- )
+- „
+- /
 - <sos/eos>
 odim: null
 model_conf: {}
@@ -194,7 +191,7 @@ token_type: char
 bpemodel: null
 non_linguistic_symbols: null
 cleaner: null
-g2p: g2p_en_no_space
+g2p: g2p_en
 feats_extract: linear_spectrogram
 feats_extract_conf:
     n_fft: 1024
@@ -207,7 +204,8 @@ tts_conf:
     generator_type: vits_generator
     generator_params:
         hidden_channels: 192
-        spks: 128
+        spks: -1
+        spk_embed_dim: 192
         global_channels: 256
         segment_size: 32
         text_encoder_attention_heads: 2
@@ -269,7 +267,7 @@ tts_conf:
         stochastic_duration_predictor_dropout_rate: 0.5
         stochastic_duration_predictor_flows: 4
         stochastic_duration_predictor_dds_conv_layers: 3
-        vocabs: 55
+        vocabs: 50
         aux_channels: 513
     discriminator_type: hifigan_multi_scale_multi_period_discriminator
     discriminator_params:
@@ -367,5 +365,5 @@ energy_normalize_conf: {}
 required:
 - output_dir
 - token_list
-version: '202209'
+version: '202301'
 distributed: false

requirements.txt

@@ -1,9 +1,8 @@
 # requirements for HuggingFace demo. Installs local package.
 torch
---extra-index-url https://download.pytorch.org/whl/cpu
-espnet==202209
+espnet>=202301
 num2words==0.5.12
 ukrainian-word-stress==1.0.1
 git+https://github.com/egorsmkv/ukrainian-accentor.git@5b7971c4e135e3ff3283336962e63fc0b1c80f4c
-gradio==3.12
+gradio==3.14
 huggingface_hub==0.11.1

training/STEPS.md

@@ -1,25 +1,35 @@
-Setup env
+# Setup environment
 Link: https://espnet.github.io/espnet/installation.html
 
-0. `sudo apt-get install cmake sox libsndfile1-dev ffmpeg`
-1. `git clone --branch v.202209 https://github.com/espnet/espnet`
-2. `cd ./espnet/tools`
+```sh
+sudo apt-get install cmake sox libsndfile1-dev ffmpeg
+git clone --branch v.202301 https://github.com/espnet/espnet
+cd ./espnet/tools
 ./setup_anaconda.sh anaconda espnet 3.8
-3. `CONDA_TOOLS_DIR=$(dirname ${CONDA_EXE})/..`
-./setup_anaconda.sh ${CONDA_TOOLS_DIR} espnet 3.8
-5. `make`
+. ./activate_python.sh
+make
 pip install --upgrade torch torchaudio # or setup same versions
 make
-7. `. ./activate_python.sh; python3 check_install.py`
+. ./activate_python.sh; python3 check_install.py
+```
 
-# run training
+# Run training
 
-cd ../egs2/ljspeech/tts1
-./run.sh 
+ESPNET is a dynamic framework. For the latest guide, please refer to https://github.com/espnet/espnet/tree/master/egs2/TEMPLATE/tts1
+
+This page provides general launching steps on how training was performed for reference, and this doesn't cover data preparation.
 
+NOTE: before running the script below, copy [./train_vits.yaml](./train_vits.yaml) to your `<espnet_root>/egs2/ljspeech/tts1/conf/tuning/train_vits.yaml`
+
+
+```sh
+cd ../egs2/ljspeech/tts1
+pip install torchvision # to save figures
+pip install speechbrain
 ./run.sh \
     --stage 2 \
-    --use_sid true \
+    --use_xvector true \
+    --xvector_tool speechbrain \
     --fs 22050 \
     --n_fft 1024 \
     --n_shift 256 \
@@ -30,4 +40,5 @@ cd ../egs2/ljspeech/tts1
     --feats_extract linear_spectrogram \
     --feats_normalize none \
     --train_config ./conf/tuning/train_vits.yaml \
-    --inference_config ./conf/tuning/decode_vits.yaml
+    --inference_config ./conf/tuning/decode_vits.yaml
+```

training/train_vits.yaml

@@ -16,7 +16,8 @@ tts_conf:
     generator_type: vits_generator
     generator_params:
         hidden_channels: 192
-        spks: 128
+        spks: -1
+        spk_embed_dim: 192
         global_channels: 256
         segment_size: 32
         text_encoder_attention_heads: 2
@@ -159,18 +160,16 @@ generator_first: false # whether to start updating generator first
 #                OTHER TRAINING SETTING                  #
 ##########################################################
 #num_iters_per_epoch: 1000 # number of iterations per epoch
-max_epoch: 30           # number of epochs
+max_epoch: 1000           # number of epochs
 accum_grad: 1             # gradient accumulation
-batch_bins: 1900000       # batch bins (feats_type=raw)
+batch_bins: 1500000       # batch bins (feats_type=raw)
 batch_type: numel         # how to make batch
-#batch_type: sorted           # how to make batchbatch_size: 1
 grad_clip: -1             # gradient clipping norm
 grad_noise: false         # whether to use gradient noise injection
 sort_in_batch: descending # how to sort data in making batch
 sort_batch: descending    # how to sort created batches
-num_workers: 1            # number of workers of data loader
+num_workers: 4            # number of workers of data loader
 use_amp: false            # whether to use pytorch amp
-train_dtype: float32
 log_interval: 50          # log interval in iterations
 keep_nbest_models: 10     # number of models to keep
 num_att_plot: 3           # number of attention figures to be saved in every check

ukrainian_tts/tts.py

@@ -9,16 +9,16 @@ from torch import no_grad
 import numpy as np
 import time
 import soundfile as sf
+from kaldiio import load_ark
 
 
 class Voices(Enum):
     """List of available voices for the model."""
 
-    Olena = 4
-    Mykyta = 3
-    Lada = 2
-    Dmytro = 1
-    Olga = 5
+    Tetiana = "tetiana"
+    Mykyta = "mykyta"
+    Lada = "lada"
+    Dmytro = "dmytro"
 
 
 class Stress(Enum):
@@ -41,7 +41,7 @@ class TTS:
         self.device = device
         self.__setup_cache(cache_folder)
 
-    def tts(self, text: str, voice: int, stress: str, output_fp=BytesIO(), speed=1.0):
+    def tts(self, text: str, voice: str, stress: str, output_fp=BytesIO(), speed=1.0):
         """
         Run a Text-to-Speech engine and output to `output_fp` BytesIO-like object.
         - `text` - your model input text.
@@ -71,7 +71,7 @@ class TTS:
         with no_grad():
             start = time.time()
             wav = self.synthesizer(
-                text, sids=np.array(voice), decode_conf={"alpha": 1 / speed}
+                text, spembs=self.xvectors[voice][0], decode_conf={"alpha": 1 / speed}
             )["wav"]
 
         rtf = (time.time() - start) / (len(wav) / self.synthesizer.fs)
@@ -91,19 +91,25 @@ class TTS:
 
     def __setup_cache(self, cache_folder=None):
         """Downloads models and stores them into `cache_folder`. By default stores in current directory."""
-        print("downloading uk/mykyta/vits-tts")
-        release_number = "v4.0.0"
+        release_number = "v5.0.0"
+        print(
+            f"downloading https://github.com/robinhad/ukrainian-tts/releases/download/{release_number}"
+        )
         model_link = f"https://github.com/robinhad/ukrainian-tts/releases/download/{release_number}/model.pth"
         config_link = f"https://github.com/robinhad/ukrainian-tts/releases/download/{release_number}/config.yaml"
+        speakers_link = f"https://github.com/robinhad/ukrainian-tts/releases/download/{release_number}/spk_xvector.ark"
 
         if cache_folder is None:
             cache_folder = "."
 
         model_path = join(cache_folder, "model.pth")
         config_path = join(cache_folder, "config.yaml")
+        speakers_path = join(cache_folder, "spk_xvector.ark")
 
         self.__download(model_link, model_path)
         self.__download(config_link, config_path)
+        self.__download(speakers_link, speakers_path)
+        print("downloaded.")
 
         self.synthesizer = Text2Speech(
             train_config="config.yaml",
@@ -113,6 +119,7 @@ class TTS:
             noise_scale=0.333,
             noise_scale_dur=0.333,
         )
+        self.xvectors = {k: v for k, v in load_ark(speakers_path)}
 
     def __download(self, url, file_name):
         """Downloads file from `url` into local `file_name` file."""