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import json |
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import os |
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from datasets import load_dataset, DatasetInfo, DatasetDict, SplitGenerator, Split, Features, Value, Audio |
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_DESCRIPTION = """ |
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Custom version of the Common Voice dataset with additional test_freq split including custom audio and metadata. |
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""" |
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_CITATION = """ |
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@inproceedings{commonvoice:2020, |
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author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.}, |
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title = {Common Voice: A Massively-Multilingual Speech Corpus}, |
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booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)}, |
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year = 2020 |
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} |
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""" |
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_HOMEPAGE = "https://commonvoice.mozilla.org/en/datasets" |
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_LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/" |
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class CustomCommonVoice(datasets.GeneratorBasedBuilder): |
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"""Builder for a modified Common Voice dataset including a custom test_freq split.""" |
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VERSION = datasets.Version("1.0.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="test_freq", description="Custom rare test split of the Common Voice dataset."), |
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] |
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DEFAULT_CONFIG_NAME = "test_freq" |
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def _info(self): |
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return DatasetInfo( |
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description=_DESCRIPTION, |
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features=Features({ |
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"id": Value("string"), |
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"utterance": Value("int32"), |
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"from": Value("string"), |
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"value": Value("string"), |
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"emotion": Value("string"), |
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"file_name": Value("string"), |
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"audio": Audio(sampling_rate=16_000), |
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}), |
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supervised_keys=("audio", "value"), |
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homepage=_HOMEPAGE, |
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citation=_CITATION, |
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license=_LICENSE, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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test_freq_dir = os.path.abspath("test_freq") |
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test_freq_metadata = os.path.join(test_freq_dir, "metadata.jsonl") |
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return [ |
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SplitGenerator( |
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name=Split.TEST, |
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gen_kwargs={"metadata_path": test_freq_metadata, "audio_dir": test_freq_dir}), |
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] |
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def _generate_examples(self, metadata_path, audio_dir): |
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"""Yields examples.""" |
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with open(metadata_path, 'r', encoding='utf-8') as f: |
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for line in f: |
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metadata = json.loads(line) |
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audio_path = os.path.join(audio_dir, metadata['file_name']) |
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yield metadata['id'], { |
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"id": metadata['id'], |
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"utterance": metadata['utterance'], |
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"from": metadata['from'], |
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"value": metadata['value'], |
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"emotion": metadata['emotion'], |
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"file_name": metadata['file_name'], |
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"audio": audio_path, |
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} |
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