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