| import os |
| from collections import OrderedDict |
| from pathlib import Path |
| import datasets |
| import os |
| from .meta import lang2shard_cnt |
|
|
|
|
| class YodasConfig(datasets.BuilderConfig): |
| """BuilderConfig for Yodas.""" |
|
|
| def __init__(self, lang, version, **kwargs): |
| self.language = lang |
| self.base_data_path = f"data/{lang}" |
|
|
| description = ( |
| f"Youtube speech to text dataset in {self.language}." |
| ) |
| super(YodasConfig, self).__init__( |
| name=lang, |
| version=datasets.Version(version), |
| description=description, |
| **kwargs, |
| ) |
|
|
|
|
| DEFAULT_CONFIG_NAME = "all" |
| LANGS = list(lang2shard_cnt.keys()) |
| VERSION = "1.0.1" |
|
|
| class Yodas(datasets.GeneratorBasedBuilder): |
| """Yodas dataset.""" |
|
|
| BUILDER_CONFIGS = [ |
| YodasConfig(lang, version=VERSION) for lang in LANGS |
| ] |
|
|
| VERSION = datasets.Version("1.0.1") |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description="Yodas", |
| features=datasets.Features( |
| OrderedDict( |
| [ |
| ("id", datasets.Value("string")), |
| ("utt_id", datasets.Value("string")), |
| ("audio", datasets.Audio(sampling_rate=16_000)), |
| ("text", datasets.Value("string")), |
| ] |
| ) |
| ), |
| supervised_keys=None, |
| homepage="", |
| citation="", |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| """Returns SplitGenerators.""" |
| |
|
|
| total_cnt = lang2shard_cnt[self.config.name] |
|
|
| idx_lst = [f"{i:08d}" for i in range(total_cnt)] |
| audio_tar_files = dl_manager.download([f"{self.config.base_data_path}/audio/{i:08d}.tar.gz" for i in range(total_cnt)]) |
| text_files = dl_manager.download([f"{self.config.base_data_path}/text/{i:08d}.txt" for i in range(total_cnt)]) |
| |
|
|
| if dl_manager.is_streaming: |
| audio_archives = [dl_manager.iter_archive(audio_tar_file) for audio_tar_file in audio_tar_files] |
| text_archives = [dl_manager.extract(text_file) for text_file in text_files] |
|
|
| else: |
| print("extracting audio ...") |
| extracted_audio_archives = dl_manager.extract(audio_tar_files) |
|
|
| audio_archives = [] |
| text_archives = [] |
| for idx, audio_tar_file, extracted_dir, text_file in zip(idx_lst, audio_tar_files, extracted_audio_archives, text_files): |
| audio_archives.append(str(extracted_dir)+'/'+idx) |
| text_archives.append(text_file) |
|
|
|
|
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={ |
| "is_streaming": dl_manager.is_streaming, |
| "audio_archives": audio_archives, |
| 'text_archives': text_archives, |
| }, |
| ), |
| ] |
|
|
| def _generate_examples(self, is_streaming, audio_archives, text_archives): |
| """Yields examples.""" |
|
|
| id_ = 0 |
|
|
| if is_streaming: |
| for tar_file, text_file in zip(audio_archives, text_archives): |
|
|
| utt2text = {} |
|
|
| with open(text_file) as f: |
| for id_, row in enumerate(f): |
| row = row.strip().split(maxsplit=1) |
| utt2text[row[0]] = row[1] |
|
|
| for path, audio_f in tar_file: |
|
|
| path = Path(path) |
| utt_id = path.stem |
|
|
| if utt_id in utt2text: |
|
|
| result = { |
| 'id': id_, |
| 'utt_id': utt_id, |
| 'audio': {"path": None, "bytes": audio_f.read()}, |
| 'text': utt2text[utt_id] |
| } |
|
|
| yield id_, result |
| id_ += 1 |
| else: |
| for extracted_dir, text_file in zip(audio_archives, text_archives): |
|
|
| utt2text = {} |
| extract_root_dir = Path(extracted_dir).parent |
| extracted_dir = list(extract_root_dir.glob('./*'))[0] |
|
|
| with open(text_file) as f: |
| for _, row in enumerate(f): |
| row = row.strip().split(maxsplit=1) |
| utt2text[row[0]] = row[1] |
|
|
| for audio_file in list(Path(extracted_dir).glob('*')): |
|
|
| utt_id = audio_file.stem |
| if utt_id in utt2text: |
|
|
| result = { |
| 'id': id_, |
| 'utt_id': utt_id, |
| 'audio': {"path": str(audio_file.absolute()), "bytes": open(audio_file, 'rb').read()}, |
| 'text': utt2text[utt_id] |
| } |
|
|
| yield id_, result |
| id_ += 1 |
|
|