49 lines
1.8 KiB
Python
49 lines
1.8 KiB
Python
import os
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import argparse
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import librosa
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import numpy as np
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from multiprocessing import Pool, cpu_count
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from scipy.io import wavfile
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from tqdm import tqdm
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def process(item):
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spkdir, wav_name, args = item
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# speaker 's5', 'p280', 'p315' are excluded,
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speaker = spkdir.replace("\\", "/").split("/")[-1]
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wav_path = os.path.join(args.in_dir, speaker, wav_name)
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if os.path.exists(wav_path) and '.wav' in wav_path:
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os.makedirs(os.path.join(args.out_dir2, speaker), exist_ok=True)
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wav, sr = librosa.load(wav_path, sr=None)
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wav, _ = librosa.effects.trim(wav, top_db=20)
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peak = np.abs(wav).max()
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if peak > 1.0:
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wav = 0.98 * wav / peak
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wav2 = librosa.resample(wav, orig_sr=sr, target_sr=args.sr2)
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wav2 /= max(wav2.max(), -wav2.min())
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save_name = wav_name
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save_path2 = os.path.join(args.out_dir2, speaker, save_name)
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wavfile.write(
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save_path2,
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args.sr2,
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(wav2 * np.iinfo(np.int16).max).astype(np.int16)
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)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--sr2", type=int, default=44100, help="sampling rate")
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parser.add_argument("--in_dir", type=str, default="./dataset_raw", help="path to source dir")
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parser.add_argument("--out_dir2", type=str, default="./dataset/44k", help="path to target dir")
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args = parser.parse_args()
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processs = cpu_count()-2 if cpu_count() >4 else 1
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pool = Pool(processes=processs)
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for speaker in os.listdir(args.in_dir):
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spk_dir = os.path.join(args.in_dir, speaker)
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if os.path.isdir(spk_dir):
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print(spk_dir)
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for _ in tqdm(pool.imap_unordered(process, [(spk_dir, i, args) for i in os.listdir(spk_dir) if i.endswith("wav")])):
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pass
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