flexthink
Change "id" to "sample_id", to avoid conflict with SpeechBrain's DynamicItemDataset
95b81be
| # coding=utf-8 | |
| # Copyright 2021 Artem Ploujnikov | |
| # Lint as: python3 | |
| import json | |
| import datasets | |
| _DESCRIPTION = """\ | |
| Grapheme-to-Phoneme training, validation and test sets | |
| """ | |
| _BASE_URL = "https://huggingface.co/datasets/flexthink/librig2p-nostress-space/resolve/main/dataset" | |
| _HOMEPAGE_URL = "https://huggingface.co/datasets/flexthink/librig2p-nostress-space" | |
| _ORIGINS = ["librispeech", "librispeech-lex", "wikipedia-homograph"] | |
| _NA = "N/A" | |
| _SPLIT_TYPES = ["train", "valid", "test"] | |
| _DATA_TYPES = ["lexicon", "sentence", "homograph"] | |
| _SPLITS = [ | |
| f"{data_type}_{split_type}" | |
| for data_type in _DATA_TYPES | |
| for split_type in _SPLIT_TYPES] | |
| class GraphemeToPhoneme(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( | |
| { | |
| "sample_id": datasets.Value("string"), | |
| "speaker_id": datasets.Value("string"), | |
| "origin": datasets.Value("string"), | |
| "char": datasets.Value("string"), | |
| "phn": datasets.Sequence(datasets.Value("string")), | |
| "homograph": datasets.Value("string"), | |
| "homograph_wordid": datasets.Value("string"), | |
| "homograph_char_start": datasets.Value("int32"), | |
| "homograph_char_end": datasets.Value("int32"), | |
| "homograph_phn_start": datasets.Value("int32"), | |
| "homograph_phn_end": datasets.Value("int32"), | |
| }, | |
| ), | |
| supervised_keys=None, | |
| homepage=_HOMEPAGE_URL, | |
| ) | |
| def _get_url(self, split): | |
| return f'{self.base_url}/{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 sentence_counter, (sample_id, item) in enumerate(data.items()): | |
| resp = { | |
| "sample_id": sample_id, | |
| "speaker_id": str(item.get("speaker_id") or _NA), | |
| "origin": item["origin"], | |
| "char": item["char"], | |
| "phn": item["phn"], | |
| "homograph": item.get("homograph", _NA), | |
| "homograph_wordid": item.get("homograph_wordid", _NA), | |
| "homograph_char_start": item.get("homograph_char_start", 0), | |
| "homograph_char_end": item.get("homograph_char_end", 0), | |
| "homograph_phn_start": item.get("homograph_phn_start", 0), | |
| "homograph_phn_end": item.get("homograph_phn_end", 0) | |
| } | |
| yield sentence_counter, resp | |