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