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import json |
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import datasets |
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_DESCRIPTION = """\ |
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This is a public domain speech dataset consisting of 13,100 short audio |
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clips of a single speaker reading passages from 7 non-fiction books. A |
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transcription is provided for each clip. Clips vary in length from 1 to 10 |
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seconds and have a total length of approximately 24 hours. |
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""" |
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_BASE_URL = "https://huggingface.co/datasets/flexthink/librig2p-nostress-space/resolve/main" |
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_HOMEPAGE_URL = "https://huggingface.co/datasets/flexthink/ljspeech" |
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_PHONEMES = [ |
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"AA", |
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"AE", |
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"AH", |
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"AO", |
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"AW", |
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"AY", |
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"B", |
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"CH", |
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"D", |
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"DH", |
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"EH", |
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"ER", |
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"EY", |
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"F", |
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"G", |
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"HH", |
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"IH", |
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"IY", |
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"JH", |
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"K", |
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"L", |
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"M", |
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"N", |
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"NG", |
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"OW", |
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"OY", |
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"P", |
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"R", |
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"S", |
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"SH", |
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"T", |
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"TH", |
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"UH", |
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"UW", |
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"V", |
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"W", |
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"Y", |
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"Z", |
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"ZH", |
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" " |
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] |
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_SPLITS = ["train", "valid", "test"] |
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class LJSpeech(datasets.GeneratorBasedBuilder): |
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def __init__(self, base_url=None, splits=None, *args, **kwargs): |
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super().__init__(*args, **kwargs) |
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self.base_url = base_url or _BASE_URL |
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self.splits = splits or _SPLITS |
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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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"char": datasets.Value("string"), |
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"phn_raw": datasets.Sequence(datasets.Value("string")), |
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"phn": datasets.Sequence(datasets.ClassLabel(names=_PHONEMES)), |
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"wav": datasets.Value("string"), |
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}, |
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), |
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supervised_keys=None, |
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homepage=_HOMEPAGE_URL, |
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) |
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def _get_url(self, split): |
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return f'{self.base_url}/ljspeech_{split}.json' |
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def _split_generator(self, dl_manager, split): |
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url = self._get_url(split) |
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path = dl_manager.download_and_extract(url) |
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return datasets.SplitGenerator( |
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name=split, |
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gen_kwargs={"datapath": path, "datatype": split}, |
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) |
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def _split_generators(self, dl_manager): |
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return [ |
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self._split_generator(dl_manager, split) |
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for split in self.splits |
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] |
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def _generate_examples(self, datapath, datatype): |
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with open(datapath, encoding="utf-8") as f: |
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data = json.load(f) |
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for item_id, item in data.items(): |
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resp = { |
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"char": item["char"], |
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"phn": item["phn"], |
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"phn_raw": item["phn"], |
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"wav": item["wav"] |
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} |
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yield item_id, resp |
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