Datasets:
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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,
}
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