Python hparams.hparams.min_level_db() Examples

The following are 30 code examples of hparams.hparams.min_level_db(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module hparams.hparams , or try the search function .
Example #1
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def _normalize(S):
    return np.clip((S - hparams.min_level_db) / -hparams.min_level_db, 0, 1)
Example #2
Source File: audio.py    From WaveRNN-Pytorch with MIT License 5 votes vote down vote up 
def _normalize(S):
    return np.clip((S - hparams.min_level_db) / -hparams.min_level_db, 0, 1)
Example #3
Source File: audio.py    From WaveRNN-Pytorch with MIT License 5 votes vote down vote up 
def _denormalize(S):
    return (np.clip(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db


# Fatcord's preprocessing
Example #4
Source File: audio.py    From gmvae_tacotron with MIT License 5 votes vote down vote up 
def _amp_to_db(x):
	min_level = np.exp(hparams.min_level_db / 20 * np.log(10))
	return 20 * np.log10(np.maximum(min_level, x))
Example #5
Source File: audio.py    From gmvae_tacotron with MIT License 5 votes vote down vote up 
def _normalize(S):
	if hparams.allow_clipping_in_normalization:
		if hparams.symmetric_mels:
			return np.clip((2 * hparams.max_abs_value) * ((S - hparams.min_level_db) / (-hparams.min_level_db)) - hparams.max_abs_value,
			 -hparams.max_abs_value, hparams.max_abs_value)
		else:
			return np.clip(hparams.max_abs_value * ((S - hparams.min_level_db) / (-hparams.min_level_db)), 0, hparams.max_abs_value)

	assert S.max() <= 0 and S.min() - hparams.min_level_db >= 0
	if hparams.symmetric_mels:
		return (2 * hparams.max_abs_value) * ((S - hparams.min_level_db) / (-hparams.min_level_db)) - hparams.max_abs_value
	else:
		return hparams.max_abs_value * ((S - hparams.min_level_db) / (-hparams.min_level_db))
Example #6
Source File: audio.py    From gmvae_tacotron with MIT License 5 votes vote down vote up 
def _denormalize(D):
	if hparams.allow_clipping_in_normalization:
		if hparams.symmetric_mels:
			return (((np.clip(D, -hparams.max_abs_value,
				hparams.max_abs_value) + hparams.max_abs_value) * -hparams.min_level_db / (2 * hparams.max_abs_value)) 
				+ hparams.min_level_db)
		else:
			return ((np.clip(D, 0, hparams.max_abs_value) * -hparams.min_level_db / hparams.max_abs_value) + hparams.min_level_db)

	if hparams.symmetric_mels:
		return (((D + hparams.max_abs_value) * -hparams.min_level_db / (2 * hparams.max_abs_value)) + hparams.min_level_db)
	else:
		return ((D * -hparams.min_level_db / hparams.max_abs_value) + hparams.min_level_db)
Example #7
Source File: audio.py    From gmvae_tacotron with MIT License 5 votes vote down vote up 
def _amp_to_db(x):
	min_level = np.exp(hparams.min_level_db / 20 * np.log(10))
	return 20 * np.log10(np.maximum(min_level, x))
Example #8
Source File: audio.py    From gmvae_tacotron with MIT License 5 votes vote down vote up 
def _normalize(S):
	if hparams.allow_clipping_in_normalization:
		if hparams.symmetric_mels:
			return np.clip((2 * hparams.max_abs_value) * ((S - hparams.min_level_db) / (-hparams.min_level_db)) - hparams.max_abs_value,
			 -hparams.max_abs_value, hparams.max_abs_value)
		else:
			return np.clip(hparams.max_abs_value * ((S - hparams.min_level_db) / (-hparams.min_level_db)), 0, hparams.max_abs_value)

	assert S.max() <= 0 and S.min() - hparams.min_level_db >= 0
	if hparams.symmetric_mels:
		return (2 * hparams.max_abs_value) * ((S - hparams.min_level_db) / (-hparams.min_level_db)) - hparams.max_abs_value
	else:
		return hparams.max_abs_value * ((S - hparams.min_level_db) / (-hparams.min_level_db))
Example #9
Source File: audio.py    From Tacotron2-PyTorch with MIT License 5 votes vote down vote up 
def _normalize(S):
	return np.clip((S - hps.min_level_db) / -hps.min_level_db, 0, 1)
Example #10
Source File: audio.py    From Tacotron2-PyTorch with MIT License 5 votes vote down vote up 
def _denormalize(S):
	return (np.clip(S, 0, 1) * -hps.min_level_db) + hps.min_level_db
Example #11
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def melspectrogram(y):
    D = _lws_processor().stft(y).T
    S = _amp_to_db(_linear_to_mel(np.abs(D))) - hparams.ref_level_db
    if not hparams.allow_clipping_in_normalization:
        assert S.max() <= 0 and S.min() - hparams.min_level_db >= 0
    return _normalize(S)
Example #12
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def _amp_to_db(x):
    min_level = np.exp(hparams.min_level_db / 20 * np.log(10))
    return 20 * np.log10(np.maximum(min_level, x))
Example #13
Source File: audio.py    From WaveRNN-Pytorch with MIT License 5 votes vote down vote up 
def _amp_to_db(x):
    min_level = np.exp(hparams.min_level_db / 20 * np.log(10))
    return 20 * np.log10(np.maximum(min_level, x))
Example #14
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def _denormalize(S):
    return (np.clip(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db
Example #15
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def melspectrogram(y):
    D = _lws_processor().stft(y).T
    S = _amp_to_db(_linear_to_mel(np.abs(D))) - hparams.ref_level_db
    if not hparams.allow_clipping_in_normalization:
        assert S.max() <= 0 and S.min() - hparams.min_level_db >= 0
    return _normalize(S)
Example #16
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def _normalize(S):
    return np.clip((S - hparams.min_level_db) / -hparams.min_level_db, 0, 1)
Example #17
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def _denormalize(S):
    return (np.clip(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db
Example #18
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def melspectrogram(y):
    D = _lws_processor().stft(y).T
    S = _amp_to_db(_linear_to_mel(np.abs(D))) - hparams.ref_level_db
    if not hparams.allow_clipping_in_normalization:
        assert S.max() <= 0 and S.min() - hparams.min_level_db >= 0
    return _normalize(S)
Example #19
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def _amp_to_db(x):
    min_level = np.exp(hparams.min_level_db / 20 * np.log(10))
    return 20 * np.log10(np.maximum(min_level, x))
Example #20
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def _normalize(S):
    return np.clip((S - hparams.min_level_db) / -hparams.min_level_db, 0, 1)
Example #21
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def melspectrogram(y):
    D = _lws_processor().stft(y).T
    S = _amp_to_db(_linear_to_mel(np.abs(D))) - hparams.ref_level_db
    if not hparams.allow_clipping_in_normalization:
        assert S.max() <= 0 and S.min() - hparams.min_level_db >= 0
    return _normalize(S)
Example #22
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def _amp_to_db(x):
    min_level = np.exp(hparams.min_level_db / 20 * np.log(10))
    return 20 * np.log10(np.maximum(min_level, x))
Example #23
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def _normalize(S):
    return np.clip((S - hparams.min_level_db) / -hparams.min_level_db, 0, 1)
Example #24
Source File: audio.py    From representation_mixing with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def _denormalize(S):
    return (np.clip(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db
Example #25
Source File: audio.py    From arabic-tacotron-tts with MIT License 5 votes vote down vote up 
def _denormalize(S):
  return (np.clip(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db
Example #26
Source File: audio.py    From Griffin_lim with MIT License 5 votes vote down vote up 
def _denormalize(D):
    return (((np.clip(D, -hparams.max_abs_value,
                      hparams.max_abs_value) + hparams.max_abs_value) * -hparams.min_level_db / (
                     2 * hparams.max_abs_value))
            + hparams.min_level_db)
Example #27
Source File: griffin_lim.py    From Griffin_lim with MIT License 5 votes vote down vote up 
def _denormalize(D):
    return (((tf.clip_by_value(D, -hparams.max_abs_value,
                               hparams.max_abs_value) + hparams.max_abs_value) * -hparams.min_level_db / (
                     2 * hparams.max_abs_value)) + hparams.min_level_db)
Example #28
Source File: audio.py    From vae_tacotron with MIT License 5 votes vote down vote up 
def _normalize(S):
  return np.clip((S - hparams.min_level_db) / -hparams.min_level_db, 0, 1)
Example #29
Source File: audio.py    From vae_tacotron with MIT License 5 votes vote down vote up 
def _denormalize(S):
  return (np.clip(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db
Example #30
Source File: audio.py    From vae_tacotron with MIT License 5 votes vote down vote up 
def _denormalize_tensorflow(S):
  return (tf.clip_by_value(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db