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""" Common Language Dataset""" |
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import os |
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import datasets |
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_DATA_URL = "data/CommonLanguage.zip" |
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_CITATION = """\ |
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@dataset{ganesh_sinisetty_2021_5036977, |
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author = {Ganesh Sinisetty and |
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Pavlo Ruban and |
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Oleksandr Dymov and |
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Mirco Ravanelli}, |
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title = {CommonLanguage}, |
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month = jun, |
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year = 2021, |
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publisher = {Zenodo}, |
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version = {0.1}, |
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doi = {10.5281/zenodo.5036977}, |
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url = {https://doi.org/10.5281/zenodo.5036977} |
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} |
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""" |
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_DESCRIPTION = """\ |
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This dataset is composed of speech recordings from languages that were carefully selected from the CommonVoice database. |
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The total duration of audio recordings is 45.1 hours (i.e., 1 hour of material for each language). |
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The dataset has been extracted from CommonVoice to train language-id systems. |
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""" |
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_HOMEPAGE = "https://zenodo.org/record/5036977" |
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_LICENSE = "https://creativecommons.org/licenses/by/4.0/legalcode" |
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_LANGUAGES = [ |
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"Arabic", |
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"Basque", |
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"Breton", |
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"Catalan", |
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"Chinese_China", |
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"Chinese_Hongkong", |
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"Chinese_Taiwan", |
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"Chuvash", |
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"Czech", |
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"Dhivehi", |
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"Dutch", |
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"English", |
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"Esperanto", |
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"Estonian", |
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"French", |
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"Frisian", |
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"Georgian", |
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"German", |
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"Greek", |
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"Hakha_Chin", |
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"Indonesian", |
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"Interlingua", |
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"Italian", |
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"Japanese", |
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"Kabyle", |
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"Kinyarwanda", |
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"Kyrgyz", |
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"Latvian", |
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"Maltese", |
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"Mangolian", |
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"Persian", |
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"Polish", |
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"Portuguese", |
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"Romanian", |
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"Romansh_Sursilvan", |
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"Russian", |
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"Sakha", |
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"Slovenian", |
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"Spanish", |
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"Swedish", |
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"Tamil", |
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"Tatar", |
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"Turkish", |
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"Ukranian", |
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"Welsh", |
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] |
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class CommonLanguage(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("0.1.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="full", version=VERSION, description="The entire Common Language dataset"), |
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] |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"client_id": datasets.Value("string"), |
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"path": datasets.Value("string"), |
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"audio": datasets.Audio(sampling_rate=48_000), |
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"sentence": datasets.Value("string"), |
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"age": datasets.Value("string"), |
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"gender": datasets.Value("string"), |
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"language": datasets.ClassLabel(names=_LANGUAGES), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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dl_path = dl_manager.download_and_extract(_DATA_URL) |
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archive_path = os.path.join(dl_path, "common_voice_kpd") |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"archive_path": archive_path, "split": "train"}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={"archive_path": archive_path, "split": "dev"}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"archive_path": archive_path, "split": "test"}, |
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), |
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] |
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def _generate_examples(self, archive_path, split): |
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"""Yields examples.""" |
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key = 0 |
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for language in _LANGUAGES: |
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csv_path = os.path.join(archive_path, language, f"{split}.csv") |
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with open(csv_path, encoding="utf-16") as fin: |
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next(fin) |
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for line in fin: |
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client_id, wav_name, sentence, age, gender = line.strip().split("\t")[1:] |
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path = os.path.join(archive_path, language, split, client_id, wav_name) |
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yield key, { |
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"client_id": client_id, |
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"path": path, |
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"audio": path, |
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"sentence": sentence, |
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"age": age, |
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"gender": gender, |
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"language": language, |
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} |
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key += 1 |
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