import os import argparse import librosa import numpy as np from multiprocessing import Pool, cpu_count from scipy.io import wavfile from tqdm import tqdm def process(item): spkdir, wav_name, args = item # speaker 's5', 'p280', 'p315' are excluded, speaker = spkdir.split(os.sep)[-1] wav_path = os.path.join(args.in_dir, speaker, wav_name) if os.path.exists(wav_path) and '.wav' in wav_path: os.makedirs(os.path.join(args.out_dir2, speaker), exist_ok=True) wav, sr = librosa.load(wav_path, None) wav, _ = librosa.effects.trim(wav, top_db=20) peak = np.abs(wav).max() if peak > 1.0: wav = 0.98 * wav / peak wav2 = librosa.resample(wav, orig_sr=sr, target_sr=args.sr2) save_name = wav_name save_path2 = os.path.join(args.out_dir2, speaker, save_name) wavfile.write( save_path2, args.sr2, (wav2 * np.iinfo(np.int16).max).astype(np.int16) ) if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--sr2", type=int, default=32000, help="sampling rate") parser.add_argument("--in_dir", type=str, default="./dataset_raw", help="path to source dir") parser.add_argument("--out_dir2", type=str, default="./dataset/32k", help="path to target dir") args = parser.parse_args() processs = cpu_count()-2 if cpu_count() >4 else 1 pool = Pool(processes=processs) for speaker in os.listdir(args.in_dir): spk_dir = os.path.join(args.in_dir, speaker) if os.path.isdir(spk_dir): print(spk_dir) for _ in tqdm(pool.imap_unordered(process, [(spk_dir, i, args) for i in os.listdir(spk_dir) if i.endswith("wav")])): pass