Python hparams.hparams.griffin_lim_iters() Examples

The following are 12 code examples of hparams.hparams.griffin_lim_iters(). 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 Griffin_lim with MIT License 5 votes vote down vote up 
def _griffin_lim(S):
    angles = np.exp(2j * np.pi * np.random.rand(*S.shape))
    S_complex = np.abs(S).astype(np.complex)
    for i in range(hparams.griffin_lim_iters):
        if i > 0:
            angles = np.exp(1j * np.angle(_stft(y)))
        y = _istft(S_complex * angles)
    return y
Example #2
Source File: griffin_lim.py    From Griffin_lim with MIT License 5 votes vote down vote up 
def spectrogram2wav(spectrogram, n_iter=hparams.griffin_lim_iters, n_fft=(hparams.num_freq - 1) * 2,
                    win_length=int(hparams.frame_length_ms / 1000 * hparams.sample_rate),
                    hop_length=int(hparams.frame_shift_ms / 1000 * hparams.sample_rate)):
    '''Converts spectrogram into a waveform using Griffin-lim's raw.
    '''

    def invert_spectrogram(spectrogram):
        '''
        spectrogram: [t, f]
        '''
        spectrogram = tf.expand_dims(spectrogram, 0)
        inversed = tf.contrib.signal.inverse_stft(spectrogram, win_length, hop_length, n_fft)
        squeezed = tf.squeeze(inversed, 0)
        return squeezed

    spectrogram = tf.transpose(spectrogram)

    spectrogram = tf.cast(spectrogram, dtype=tf.complex64)  # [t, f]
    X_best = tf.identity(spectrogram)
    for i in range(n_iter):
        X_t = invert_spectrogram(X_best)
        est = tf.contrib.signal.stft(X_t, win_length, hop_length, n_fft, pad_end=False)  # (1, T, n_fft/2+1)
        phase = est / tf.cast(tf.maximum(1e-8, tf.abs(est)), tf.complex64)  # [t, f]
        X_best = spectrogram * phase  # [t, t]
    X_t = invert_spectrogram(X_best)
    y = tf.real(X_t)

    return y
Example #3
Source File: audio.py    From vae_tacotron with MIT License 5 votes vote down vote up 
def _griffin_lim(S):
  '''librosa implementation of Griffin-Lim
  Based on https://github.com/librosa/librosa/issues/434
  '''
  angles = np.exp(2j * np.pi * np.random.rand(*S.shape))
  S_complex = np.abs(S).astype(np.complex)
  y = _istft(S_complex * angles)
  for i in range(hparams.griffin_lim_iters):
    angles = np.exp(1j * np.angle(_stft(y)))
    y = _istft(S_complex * angles)
  return y
Example #4
Source File: audio.py    From vae_tacotron with MIT License 5 votes vote down vote up 
def _griffin_lim_tensorflow(S):
  '''TensorFlow implementation of Griffin-Lim
  Based on https://github.com/Kyubyong/tensorflow-exercises/blob/master/Audio_Processing.ipynb
  '''
  with tf.variable_scope('griffinlim'):
    # TensorFlow's stft and istft operate on a batch of spectrograms; create batch of size 1
    S = tf.expand_dims(S, 0)
    S_complex = tf.identity(tf.cast(S, dtype=tf.complex64))
    y = _istft_tensorflow(S_complex)
    for i in range(hparams.griffin_lim_iters):
      est = _stft_tensorflow(y)
      angles = est / tf.cast(tf.maximum(1e-8, tf.abs(est)), tf.complex64)
      y = _istft_tensorflow(S_complex * angles)
    return tf.squeeze(y, 0)
Example #5
Source File: audio.py    From vae_tacotron2 with MIT License 5 votes vote down vote up 
def _griffin_lim(S):
	'''librosa implementation of Griffin-Lim
	Based on https://github.com/librosa/librosa/issues/434
	'''
	angles = np.exp(2j * np.pi * np.random.rand(*S.shape))
	S_complex = np.abs(S).astype(np.complex)
	y = _istft(S_complex * angles)
	for i in range(hparams.griffin_lim_iters):
		angles = np.exp(1j * np.angle(_stft(y)))
		y = _istft(S_complex * angles)
	return y
Example #6
Source File: audio.py    From vae_tacotron2 with MIT License 5 votes vote down vote up 
def _griffin_lim(S):
	'''librosa implementation of Griffin-Lim
	Based on https://github.com/librosa/librosa/issues/434
	'''
	angles = np.exp(2j * np.pi * np.random.rand(*S.shape))
	S_complex = np.abs(S).astype(np.complex)
	y = _istft(S_complex * angles)
	for i in range(hparams.griffin_lim_iters):
		angles = np.exp(1j * np.angle(_stft(y)))
		y = _istft(S_complex * angles)
	return y
Example #7
Source File: audio.py    From arabic-tacotron-tts with MIT License 5 votes vote down vote up 
def _griffin_lim(S):
  '''librosa implementation of Griffin-Lim
  Based on https://github.com/librosa/librosa/issues/434
  '''
  angles = np.exp(2j * np.pi * np.random.rand(*S.shape))
  S_complex = np.abs(S).astype(np.complex)
  y = _istft(S_complex * angles)
  for i in range(hparams.griffin_lim_iters):
    angles = np.exp(1j * np.angle(_stft(y)))
    y = _istft(S_complex * angles)
  return y
Example #8
Source File: audio.py    From arabic-tacotron-tts with MIT License 5 votes vote down vote up 
def _griffin_lim_tensorflow(S):
  '''TensorFlow implementation of Griffin-Lim
  Based on https://github.com/Kyubyong/tensorflow-exercises/blob/master/Audio_Processing.ipynb
  '''
  with tf.variable_scope('griffinlim'):
    # TensorFlow's stft and istft operate on a batch of spectrograms; create batch of size 1
    S = tf.expand_dims(S, 0)
    S_complex = tf.identity(tf.cast(S, dtype=tf.complex64))
    y = _istft_tensorflow(S_complex)
    for i in range(hparams.griffin_lim_iters):
      est = _stft_tensorflow(y)
      angles = est / tf.cast(tf.maximum(1e-8, tf.abs(est)), tf.complex64)
      y = _istft_tensorflow(S_complex * angles)
    return tf.squeeze(y, 0)
Example #9
Source File: audio.py    From tacotron with MIT License 5 votes vote down vote up 
def _griffin_lim(S):
  '''librosa implementation of Griffin-Lim
  Based on https://github.com/librosa/librosa/issues/434
  '''
  angles = np.exp(2j * np.pi * np.random.rand(*S.shape))
  S_complex = np.abs(S).astype(np.complex)
  y = _istft(S_complex * angles)
  for i in range(hparams.griffin_lim_iters):
    angles = np.exp(1j * np.angle(_stft(y)))
    y = _istft(S_complex * angles)
  return y
Example #10
Source File: audio.py    From tacotron with MIT License 5 votes vote down vote up 
def _griffin_lim_tensorflow(S):
  '''TensorFlow implementation of Griffin-Lim
  Based on https://github.com/Kyubyong/tensorflow-exercises/blob/master/Audio_Processing.ipynb
  '''
  with tf.variable_scope('griffinlim'):
    # TensorFlow's stft and istft operate on a batch of spectrograms; create batch of size 1
    S = tf.expand_dims(S, 0)
    S_complex = tf.identity(tf.cast(S, dtype=tf.complex64))
    y = _istft_tensorflow(S_complex)
    for i in range(hparams.griffin_lim_iters):
      est = _stft_tensorflow(y)
      angles = est / tf.cast(tf.maximum(1e-8, tf.abs(est)), tf.complex64)
      y = _istft_tensorflow(S_complex * angles)
    return tf.squeeze(y, 0)
Example #11
Source File: audio.py    From gmvae_tacotron with MIT License 5 votes vote down vote up 
def _griffin_lim(S):
	'''librosa implementation of Griffin-Lim
	Based on https://github.com/librosa/librosa/issues/434
	'''
	angles = np.exp(2j * np.pi * np.random.rand(*S.shape))
	S_complex = np.abs(S).astype(np.complex)
	y = _istft(S_complex * angles)
	for i in range(hparams.griffin_lim_iters):
		angles = np.exp(1j * np.angle(_stft(y)))
		y = _istft(S_complex * angles)
	return y
Example #12
Source File: audio.py    From gmvae_tacotron with MIT License 5 votes vote down vote up 
def _griffin_lim(S):
	'''librosa implementation of Griffin-Lim
	Based on https://github.com/librosa/librosa/issues/434
	'''
	angles = np.exp(2j * np.pi * np.random.rand(*S.shape))
	S_complex = np.abs(S).astype(np.complex)
	y = _istft(S_complex * angles)
	for i in range(hparams.griffin_lim_iters):
		angles = np.exp(1j * np.angle(_stft(y)))
		y = _istft(S_complex * angles)
	return y