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import subprocess | |
import matplotlib | |
import os | |
matplotlib.use('Agg') | |
import librosa | |
import librosa.filters | |
import numpy as np | |
from scipy import signal | |
from scipy.io import wavfile | |
def save_wav(wav, path, sr, norm=False): | |
if norm: | |
wav = wav / np.abs(wav).max() | |
wav *= 32767 | |
# proposed by @dsmiller | |
wavfile.write(path, sr, wav.astype(np.int16)) | |
def get_hop_size(hparams): | |
hop_size = hparams['hop_size'] | |
if hop_size is None: | |
assert hparams['frame_shift_ms'] is not None | |
hop_size = int(hparams['frame_shift_ms'] / 1000 * hparams['audio_sample_rate']) | |
return hop_size | |
########################################################################################### | |
def _stft(y, hparams): | |
return librosa.stft(y=y, n_fft=hparams['fft_size'], hop_length=get_hop_size(hparams), | |
win_length=hparams['win_size'], pad_mode='constant') | |
def _istft(y, hparams): | |
return librosa.istft(y, hop_length=get_hop_size(hparams), win_length=hparams['win_size']) | |
def librosa_pad_lr(x, fsize, fshift, pad_sides=1): | |
'''compute right padding (final frame) or both sides padding (first and final frames) | |
''' | |
assert pad_sides in (1, 2) | |
# return int(fsize // 2) | |
pad = (x.shape[0] // fshift + 1) * fshift - x.shape[0] | |
if pad_sides == 1: | |
return 0, pad | |
else: | |
return pad // 2, pad // 2 + pad % 2 | |
# Conversions | |
def amp_to_db(x): | |
return 20 * np.log10(np.maximum(1e-5, x)) | |
def normalize(S, hparams): | |
return (S - hparams['min_level_db']) / -hparams['min_level_db'] | |
def denormalize(D, hparams): | |
return (D * -hparams['min_level_db']) + hparams['min_level_db'] | |
def rnnoise(filename, out_fn=None, verbose=False, out_sample_rate=22050): | |
assert os.path.exists('./rnnoise/examples/rnnoise_demo'), INSTALL_STR | |
if out_fn is None: | |
out_fn = f"{filename[:-4]}.denoised.wav" | |
out_48k_fn = f"{out_fn}.48000.wav" | |
tmp0_fn = f"{out_fn}.0.wav" | |
tmp1_fn = f"{out_fn}.1.wav" | |
tmp2_fn = f"{out_fn}.2.raw" | |
tmp3_fn = f"{out_fn}.3.raw" | |
if verbose: | |
print("Pre-processing audio...") # wav to pcm raw | |
subprocess.check_call( | |
f'sox "{filename}" -G -r48000 "{tmp0_fn}"', shell=True, stdin=subprocess.PIPE) # convert to raw | |
subprocess.check_call( | |
f'sox -v 0.95 "{tmp0_fn}" "{tmp1_fn}"', shell=True, stdin=subprocess.PIPE) # convert to raw | |
subprocess.check_call( | |
f'ffmpeg -y -i "{tmp1_fn}" -loglevel quiet -f s16le -ac 1 -ar 48000 "{tmp2_fn}"', | |
shell=True, stdin=subprocess.PIPE) # convert to raw | |
if verbose: | |
print("Applying rnnoise algorithm to audio...") # rnnoise | |
subprocess.check_call( | |
f'./rnnoise/examples/rnnoise_demo "{tmp2_fn}" "{tmp3_fn}"', shell=True) | |
if verbose: | |
print("Post-processing audio...") # pcm raw to wav | |
if filename == out_fn: | |
subprocess.check_call(f'rm -f "{out_fn}"', shell=True) | |
subprocess.check_call( | |
f'sox -t raw -r 48000 -b 16 -e signed-integer -c 1 "{tmp3_fn}" "{out_48k_fn}"', shell=True) | |
subprocess.check_call(f'sox "{out_48k_fn}" -G -r{out_sample_rate} "{out_fn}"', shell=True) | |
subprocess.check_call(f'rm -f "{tmp0_fn}" "{tmp1_fn}" "{tmp2_fn}" "{tmp3_fn}" "{out_48k_fn}"', shell=True) | |
if verbose: | |
print("Audio-filtering completed!") |