Datasets:
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.
"""sil-ai/audio-keyword-spotting is a subset of MLCommons/ml_spoken_words focusing on keywords found in the Bible"""
import json
import os
import datasets
_CITATION = """\
@InProceedings{huggingface:audio-keyword-spotting,
title = {audio-keyword-spotting},
author={Joshua Nemecek
},
year={2022}
}
"""
_DESCRIPTION = 'sil-ai/audio-keyword-spotting is a subset of MLCommons/ml_spoken_words focusing on keywords found in the Bible'
_LANGUAGES = ['eng', 'ind', 'spa']
_LANG_ISO_DICT = {'en':'eng','es':'spa','id':'ind'}
_HOMEPAGE = 'https://ai.sil.org'
_URLS = {"metadata": "bible-keyword.json",
"files": {lang: f'https://audio-keyword-spotting.s3.amazonaws.com/HF/{lang}.tar.gz' for lang in _LANGUAGES},
}
_LICENSE = 'CC-BY 4.0'
_GENDERS = ["MALE", "FEMALE", "OTHER", "NAN"]
class AudioKeywordSpottingConfig(datasets.BuilderConfig):
"""BuilderConfig for Audio-Keyword-Spotting"""
def __init__(self, language='', **kwargs):
super(AudioKeywordSpottingConfig, self).__init__(**kwargs)
self.language = _LANG_ISO_DICT.get(language, language)
class AudioKeywordSpotting(datasets.GeneratorBasedBuilder):
"""Audio-Keyword-Spotting class"""
BUILDER_CONFIGS = [AudioKeywordSpottingConfig(name=x, description=f'Audio keyword spotting for language code {x}', language=x) for x in _LANGUAGES]
DEFAULT_CONFIG_NAME = ''
BUILDER_CONFIG_CLASS = AudioKeywordSpottingConfig
VERSION = datasets.Version("0.0.1")
def _info(self):
features = datasets.Features(
{
"file": datasets.Value("string"),
"is_valid": datasets.Value("bool"),
"language": datasets.ClassLabel(names=self.config.languages),
"speaker_id": datasets.Value("string"),
"gender": datasets.ClassLabel(names=_GENDERS),
"keyword": datasets.Value("string"),
"audio": datasets.Audio(sampling_rate=16_000),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
if self.config.language == '':
raise ValueError('Please specify a language.')
elif self.config.language not in _LANGUAGES:
raise ValueError(f'{self.config.language} does not appear in the list of languages: {_LANGUAGES}')
data_dir = dl_manager.download(_URLS['metadata'])
with open(data_dir, 'r') as f:
filemeta = json.load(f)
audio_dir = dl_manager.download_and_extract(_URLS['files'][self.config.name])
langmeta = filemeta[self.config.language]
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"audio_dir": audio_dir,
"data": langmeta,
"split": "train",
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"audio_dir": audio_dir,
"data": langmeta,
"split": "dev",
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"audio_dir": audio_dir,
"data": langmeta,
"split": "test",
},
),
]
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
def _generate_examples(self, audio_dir, data, split):
for key, row in enumerate(data):
try:
tfile = os.path.join(audio_dir, ''.join(row['file'][2:]))
if not tfile.endswith('.wav'):
os.rename(tfile, tfile + '.wav')
tfile += '.wav'
yield key, {
"file": tfile,
"is_valid": datasets.Value("bool"),
"language": row['language name'],
"speaker_id": row['speaker_id'],
"gender": row['gender'],
"keyword": row['keyword'],
"audio": tfile,
}
except Exception as e:
print(e)
print(f'In split {split}: {row["file"]} failed to download. Data may be missing.')
pass |