Plachta
31 lines
1.3 KiB
Python
31 lines
1.3 KiB
Python
import os
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import torch
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import torchaudio
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import argparse
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument('--denoise_user', type=bool, default=False,
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help='whether to denoise user recorded voice')
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parser.add_argument('--denoise_character', type=bool, default=False,
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help='whether to denoise uploaded character voice')
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args = parser.parse_args()
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if args.denoise_user:
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audio_dir = "./user_voice/"
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wavfiles = []
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for filename in list(os.walk(audio_dir))[0][2]:
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if filename.endswith(".wav"):
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wavfiles.append(filename)
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# denoise with demucs
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for i, wavfile in enumerate(wavfiles):
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os.system(f"demucs --two-stems=vocals {audio_dir}{wavfile}")
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# read & store the denoised vocals back
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for wavfile in wavfiles:
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i = wavfile.strip(".wav")
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wav, sr = torchaudio.load(f"./separated/htdemucs/{i}/vocals.wav", frame_offset=0, num_frames=-1, normalize=True, channels_first=True)
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# merge two channels into one
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wav = wav.mean(dim=0).unsqueeze(0)
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if sr != 22050:
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wav = torchaudio.transforms.Resample(orig_freq=sr, new_freq=22050)(wav)
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torchaudio.save(f"./user_voice/{i}.wav", wav, 22050, channels_first=True) |