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Computes MFCCs of log_mel_spectrograms
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tf.signal.mfccs_from_log_mel_spectrograms( log_mel_spectrograms, name=None )
Implemented with GPU-compatible ops and supports gradients.
Mel-Frequency Cepstral Coefficient (MFCC) calculation consists of taking the DCT-II of a log-magnitude mel-scale spectrogram. HTK's MFCCs use a particular scaling of the DCT-II which is almost orthogonal normalization. We follow this convention.
All num_mel_bins
MFCCs are returned and it is up to the caller to select a subset of the MFCCs based on their application. For example, it is typical to only use the first few for speech recognition, as this results in an approximately pitch-invariant representation of the signal.
batch_size, num_samples, sample_rate = 32, 32000, 16000.0 # A Tensor of [batch_size, num_samples] mono PCM samples in the range [-1, 1]. pcm = tf.random.normal([batch_size, num_samples], dtype=tf.float32) # A 1024-point STFT with frames of 64 ms and 75% overlap. stfts = tf.signal.stft(pcm, frame_length=1024, frame_step=256, fft_length=1024) spectrograms = tf.abs(stfts) # Warp the linear scale spectrograms into the mel-scale. num_spectrogram_bins = stfts.shape[-1].value lower_edge_hertz, upper_edge_hertz, num_mel_bins = 80.0, 7600.0, 80 linear_to_mel_weight_matrix = tf.signal.linear_to_mel_weight_matrix( num_mel_bins, num_spectrogram_bins, sample_rate, lower_edge_hertz, upper_edge_hertz) mel_spectrograms = tf.tensordot( spectrograms, linear_to_mel_weight_matrix, 1) mel_spectrograms.set_shape(spectrograms.shape[:-1].concatenate( linear_to_mel_weight_matrix.shape[-1:])) # Compute a stabilized log to get log-magnitude mel-scale spectrograms. log_mel_spectrograms = tf.math.log(mel_spectrograms + 1e-6) # Compute MFCCs from log_mel_spectrograms and take the first 13. mfccs = tf.signal.mfccs_from_log_mel_spectrograms( log_mel_spectrograms)[..., :13]
Args | |
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log_mel_spectrograms | A [..., num_mel_bins] float32 /float64 Tensor of log-magnitude mel-scale spectrograms. |
name | An optional name for the operation. |
Returns | |
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A [..., num_mel_bins] float32 /float64 Tensor of the MFCCs of log_mel_spectrograms . |
Raises | |
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ValueError | If num_mel_bins is not positive. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/signal/mfccs_from_log_mel_spectrograms