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import datasets |
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from pathlib import Path |
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_DESCRIPTION = "Custom dataset with audio (.wav) and phoneme (.txt) pairs, sharded by split." |
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class CustomAudioPhonemeDataset(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.1.0") |
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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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"audio": datasets.Audio(sampling_rate=16000), |
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"phoneme": datasets.Sequence(datasets.Value("string")), |
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"speaker": datasets.Value("string"), |
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}), |
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supervised_keys=None, |
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) |
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def _split_generators(self, dl_manager): |
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data_dir = Path(dl_manager.manual_dir) |
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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={"split_dir": data_dir / "train"}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={"split_dir": data_dir / "validation"}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"split_dir": data_dir / "test"}, |
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), |
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] |
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def _generate_examples(self, split_dir): |
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wav_dir = Path(split_dir) / "wav" |
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phoneme_dir = Path(split_dir) / "phonemized" |
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audio_files = sorted([p for p in wav_dir.rglob("*.wav") if not p.name.startswith("._")]) |
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phoneme_files = sorted([p for p in phoneme_dir.rglob("*.txt") if not p.name.startswith("._")]) |
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def get_speaker(path): |
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return path.parent.name |
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audio_map = {(get_speaker(p), p.stem): p for p in audio_files} |
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phoneme_map = {(get_speaker(p), p.stem): p for p in phoneme_files} |
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keys = set(audio_map.keys()) & set(phoneme_map.keys()) |
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for idx, (speaker, stem) in enumerate(sorted(keys)): |
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audio_path = str(audio_map[(speaker, stem)]) |
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phoneme_path = str(phoneme_map[(speaker, stem)]) |
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with open(phoneme_path, 'r', encoding='utf-8') as f: |
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phoneme = f.read().split() |
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yield idx, { |
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"audio": {"path": audio_path, "bytes": None}, |
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"phoneme": phoneme, |
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"speaker": speaker, |
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} |
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