def compare_hparams():
from aukit.audio_griffinlim import default_hparams as gfhp
from aukit.audio_spectrogram import default_hparams as sphp
a = set(gfhp.items()) - set(sphp.items())
b = set(sphp.items()) - set(gfhp.items())
print(a)
print(b)
"n_fft": 1024, # 800
"hop_size": 256, # 200
"win_size": 1024, # 800
"sample_rate": _sr, # 16000
"fmin": 0, # 55
"fmax": _sr // 2, # 7600
"preemphasize": False, # True
'symmetric_mels': True, # True
'signal_normalization': False, # True
'allow_clipping_in_normalization': False, # True
'ref_level_db': 0, # 20
'__file__': __file__
}
melgan_hparams = {}
melgan_hparams.update({k: v for k, v in default_hparams.items()})
melgan_hparams.update(my_hp)
melgan_hparams = Dict2Obj(melgan_hparams)
_pad_len = (default_hparams.n_fft - default_hparams.hop_size) // 2
def melspectrogram(wav, hparams=None):
wav = np.pad(wav.flatten(), (_pad_len, _pad_len), mode="reflect")
mel = mel_spectrogram(wav, melgan_hparams)
mel = mel / 20
return mel
def inv_melspectrogram(mel, hparams=None):
mel = mel * 20
"n_fft": 1024, # 800
"hop_size": 256, # 200
"win_size": 1024, # 800
"sample_rate": _sr, # 16000
"fmin": 0, # 55
"fmax": _sr // 2, # 7600
"preemphasize": False, # True
'symmetric_mels': True, # True
'signal_normalization': False, # True
'allow_clipping_in_normalization': False, # True
'ref_level_db': 0, # 20
'center': False, # True
'__file__': __file__
}
synthesizer_hparams = {k: v for k, v in default_hparams.items()}
synthesizer_hparams = {**synthesizer_hparams, **my_hp}
synthesizer_hparams = Dict2Obj(synthesizer_hparams)
def audio2mel_synthesizer(src):
"""
用aukit模块重现生成mel，和synthesizer的频谱适应。
:param src:
:return:
"""
_pad_len = (synthesizer_hparams.n_fft - synthesizer_hparams.hop_size) // 2
wavs = src.cpu().numpy()
mels = []
for wav in wavs:
wav = np.pad(wav.flatten(), (_pad_len, _pad_len), mode="reflect")
from aukit.audio_griffinlim import default_hparams, mel_spectrogram
from hparams import hparams
my_hp = {
"n_fft": 1024, "hop_size": 256, "win_size": 1024,
"sample_rate": 22050, "max_abs_value": 4.0,
"fmin": 0, "fmax": 8000,
"preemphasize": True,
'symmetric_mels': True,
}
default_hparams.update(hparams.values())
# default_hparams.update(my_hp)
a = {(k, v) for k, v in hparams.values().items() if type(v) in {str, int, float, tuple, bool, type(None)}}
b = {(k, v) for k, v in default_hparams.items() if type(v) in {str, int, float, tuple, bool, type(None)}}
print(a - b)
print(b - a)
_pad_len = (default_hparams.n_fft - default_hparams.hop_size) // 2
def wavs2mels(indir: Path, outdir: Path):
for fpath in tqdm(indir.glob("*.wav")):
wav = aukit.load_wav(fpath, sr=16000)
wav = np.pad(wav.flatten(), (_pad_len, _pad_len), mode="reflect")
mel = mel_spectrogram(wav, default_hparams)
np.save(outdir.joinpath(fpath.stem + ".npy"), mel, allow_pickle=False)
def get_train_files(indir: Path):
