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import os
import argparse
import torch
import torchaudio
from tqdm import tqdm
from scipy.io.wavfile import read
from scipy.io.wavfile import write
# torch=1.9.0 -> pip install torchaudio==0.9.0 -i https://mirrors.aliyun.com/pypi/simple/
# this file is for VCTK
MAX_WAV_VALUE = 32768.0
def cut_direct_content(iWave, oWave):
source, sr = torchaudio.load(iWave)
stft = torch.stft(source, 1024, 256, 1024, torch.hann_window(1024), return_complex=True)
stft[:, 0, :] = 0
stft[:, 1, :] = 0
istft = torch.istft(stft, 1024, 256, 1024, torch.hann_window(1024))
audio = istft.squeeze()
audio = MAX_WAV_VALUE * audio
audio = audio.clamp(min=-MAX_WAV_VALUE, max=MAX_WAV_VALUE-1)
audio = audio.short()
audio = audio.data.cpu().detach().numpy()
write(oWave, sr, audio)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("-i", help="input path", dest="inPath", required=True)
parser.add_argument("-o", help="output path", dest="outPath", required=True)
args = parser.parse_args()
print(args.inPath)
print(args.outPath)
os.makedirs(args.outPath, exist_ok=True)
rootPath = args.inPath
outPath = args.outPath
for spks in os.listdir(rootPath):
if (os.path.isdir(f"./{rootPath}/{spks}")):
os.makedirs(f"./{outPath}/{spks}", exist_ok=True)
files = [f for f in os.listdir(f"./{rootPath}/{spks}") if f.endswith(".wav")]
for file in tqdm(files, desc=f'Processing cdc {spks}'):
iWave = f"./{rootPath}/{spks}/{file}"
oWave = f"./{outPath}/{spks}/{file}"
cut_direct_content(iWave, oWave)
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