Datasets:
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import datasets
from pathlib import Path
import random
_DESCRIPTION = "Custom dataset with audio (.wav) and phoneme (.txt) pairs, split by speaker."
# For reproducibility!
_SEED = 42
class CustomAudioPhonemeDataset(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.5")
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):
data_dir = dl_manager.manual_dir
# Get all speakers from 'wav'
wav_dir = Path(data_dir) / 'wav'
speakers = sorted([d.name for d in wav_dir.iterdir() if d.is_dir()])
random.seed(_SEED)
random.shuffle(speakers)
# 80/10/10 split
N = len(speakers)
n_train = int(0.8 * N)
n_val = int(0.1 * N)
train_speakers = set(speakers[:n_train])
val_speakers = set(speakers[n_train:n_train + n_val])
test_speakers = set(speakers[n_train + n_val:])
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"dataset_folder": data_dir, "split_speakers": train_speakers},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"dataset_folder": data_dir, "split_speakers": val_speakers},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"dataset_folder": data_dir, "split_speakers": test_speakers},
),
]
def _generate_examples(self, dataset_folder, split_speakers):
dataset_folder = Path(dataset_folder)
wav_dir = dataset_folder / 'wav'
phoneme_dir = dataset_folder / 'phonemized'
# Gather audio and phoneme files (still recursively)
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('._')])
# Map speaker from the relative path (assumes: wav/speaker/file.wav)
def get_speaker(path):
# wav/speaker/utterance.wav → speaker
return path.parent.name
# Match by base 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}
# Only use files where speaker is in split
keys = set(audio_map.keys()) & set(phoneme_map.keys())
keys = [k for k in keys if k[0] in split_speakers]
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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