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import csv |
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import os |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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""" Self-use Dataset""" |
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_CITATION = """\ |
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@article{nothing, |
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title={Self-use DataSets}, |
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author={Stan} |
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journal={}, |
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year={2023} |
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} |
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""" |
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_DESCRIPTION = """\ |
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Self-use DataSets |
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""" |
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_HOMEPAGE_URL = "https://arxiv.org/abs/2104.08524" |
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_DATA_URL = "https://asr-1258129568.cos.ap-shanghai.myqcloud.com/DataSets-0.zip" |
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class Minds14Config(datasets.BuilderConfig): |
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"""BuilderConfig for xtreme-s""" |
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def __init__( |
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self, name, description, homepage, data_url |
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): |
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super(Minds14Config, self).__init__( |
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name=self.name, |
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version=datasets.Version("1.0.0", ""), |
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description=self.description, |
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) |
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self.name = name |
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self.description = description |
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self.homepage = homepage |
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self.data_url = data_url |
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def _build_config(name): |
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return Minds14Config( |
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name=name, |
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description=_DESCRIPTION, |
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homepage=_HOMEPAGE_URL, |
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data_url=_DATA_URL, |
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) |
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class Minds14(datasets.GeneratorBasedBuilder): |
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DEFAULT_WRITER_BATCH_SIZE = 1000 |
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BUILDER_CONFIGS = [_build_config('demo')] |
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def _info(self): |
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task_templates = None |
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features = datasets.Features( |
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{ |
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"path": datasets.Value("string"), |
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"audio": datasets.Audio(sampling_rate=16_000), |
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"reference": datasets.Value("string"), |
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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=("audio", "reference"), |
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homepage='', |
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citation=_CITATION, |
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task_templates=task_templates, |
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) |
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def _split_generators(self, dl_manager): |
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archive_path = dl_manager.download_and_extract(_DATA_URL) |
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audio_path = dl_manager.extract( |
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os.path.join(archive_path, "DataSets-0", "audio.zip") |
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) |
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text_path = dl_manager.extract( |
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os.path.join(archive_path, "DataSets-0", "text.zip") |
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) |
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text_path ={'demo': os.path.join(text_path, f"demo.csv")} |
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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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"audio_path": audio_path, |
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"text_paths": text_path, |
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}, |
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) |
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] |
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def _generate_examples(self, audio_path, text_paths): |
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key = 0 |
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for lang in text_paths.keys(): |
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text_path = text_paths[lang] |
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with open(text_path, encoding="utf-8") as csv_file: |
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csv_reader = csv.reader(csv_file, delimiter=",", skipinitialspace=True) |
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next(csv_reader) |
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for row in csv_reader: |
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filepath, reference = row |
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filepath = os.path.join(audio_path, *filepath.split("/")) |
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yield key, { |
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"path": filepath, |
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"audio": filepath, |
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"reference": reference, |
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} |
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key += 1 |
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