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import logging
import os
from pathlib import Path
import torchaudio
from joblib import Parallel, delayed
from librosa.util import find_files
from tqdm import tqdm
logger = logging.getLogger(__name__)
def resample_hear_corpus(task_dir: str, target_sr: int = 16000, num_workers: int = 6):
"""
Resample audio files in
${task_dir}/48000/
to
${task_dir}/${target_sr}/
"""
task_dir: Path = Path(task_dir)
target_audio_dir: Path = task_dir / f"{target_sr}"
if target_audio_dir.is_dir():
logger.info(f"{target_audio_dir} already exist. Do not need to resample")
return
default_audio_dir = task_dir / "48000"
assert default_audio_dir.exists(), f"{default_audio_dir} not found"
split_names = os.listdir(default_audio_dir)
for split_name in sorted(split_names):
split_dir = default_audio_dir / split_name
wav_paths = find_files(split_dir)
tgt_dir = target_audio_dir / split_name
tgt_dir.mkdir(exist_ok=True, parents=True)
def resample(wav_path: str):
wav, sr = torchaudio.load(wav_path)
if sr != target_sr:
resampler = torchaudio.transforms.Resample(sr, target_sr)
wav = resampler(wav)
torchaudio.save(
str(tgt_dir / Path(wav_path).name), wav, sample_rate=target_sr
)
logger.info(f"Resampling {split_dir} to {tgt_dir}:")
Parallel(n_jobs=num_workers)(
delayed(resample)(path) for path in tqdm(wav_paths)
)
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