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- 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=48000, 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/48k", 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
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