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Python源码示例：hparams.hparams.min_level_db()

示例1
def _normalize(S):
    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)
示例2
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)
示例3
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)
示例4
def _normalize(S):
  return np.clip((S - hparams.min_level_db) / -hparams.min_level_db, 0, 1)
示例5
def _denormalize(S):
  return (np.clip(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db
示例6
def _denormalize_tensorflow(S):
  return (tf.clip_by_value(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db
示例7
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))
示例8
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))
示例9
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)
示例10
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))
示例11
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))
示例12
def _normalize(S):
  return np.clip((S - hparams.min_level_db) / -hparams.min_level_db, 0, 1)
示例13
def _denormalize(S):
  return (np.clip(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db
示例14
def _denormalize_tensorflow(S):
  return (tf.clip_by_value(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db
示例15
def melspectrogram(y):
    D = _stft(y)
    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)
示例16
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))
示例17
def _normalize(S):
    return np.clip((S - hparams.min_level_db) / -hparams.min_level_db, 0, 1)
示例18
def _denormalize(S):
    return (np.clip(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db
示例19
def _normalize(S):
    return (S - hparams.min_level_db)/-hparams.min_level_db
示例20
def _normalize(S):
  return np.clip((S - hparams.min_level_db) / -hparams.min_level_db, 0, 1)
示例21
def _denormalize(S):
  return (np.clip(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db
示例22
def _denormalize_tensorflow(S):
  return (tf.clip_by_value(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db
示例23
def melspectrogram(y):
    D = _lws_processor().stft(preemphasis(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)
示例24
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))
示例25
def _normalize(S):
    return np.clip((S - hparams.min_level_db) / -hparams.min_level_db, 0, 1)
示例26
def _denormalize(S):
    return (np.clip(S, 0, 1) * -hparams.min_level_db) + hparams.min_level_db


# Fatcord's preprocessing
示例27
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))
示例28
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))
示例29
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)
示例30
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))