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import os |
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import datasets |
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import pandas as pd |
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_DESCRIPTION = """\ |
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This data is CS data |
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""" |
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_CITATION = "Some citation" |
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_data_dir = "data" |
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class CSData(datasets.GeneratorBasedBuilder): |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"path": datasets.Value("string"), |
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"filename": datasets.Audio(sampling_rate=16_000), |
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"transcription": datasets.Value("string"), |
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} |
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), |
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supervised_keys=None, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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download_dir = dl_manager.download_and_extract( |
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{ |
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"files": os.path.join(_data_dir, "files.zip"), |
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"metadata": os.path.join(_data_dir, "metadata.zip") |
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} |
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) |
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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={ |
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"split": datasets.Split.TRAIN, |
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"data_dir": os.path.join(download_dir["files"], "files"), |
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"metapath": os.path.join(download_dir["metadata"], "metadata", "data.csv"), |
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}, |
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), |
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] |
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def _generate_examples(self, data_dir, metapath, split): |
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metadata = pd.read_csv(metapath) |
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for key, row in metadata.iterrows(): |
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audio_path = os.path.join(data_dir, row["filename"]) |
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yield key, { |
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"filename": audio_path, |
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"transcription": row["transcription"], |
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"path": audio_path, |
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} |
