tf.raw_ops.Mfcc

Transforms a spectrogram into a form that's useful for speech recognition.

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tf.compat.v1.raw_ops.Mfcc

tf.raw_ops.Mfcc(
    spectrogram, sample_rate, upper_frequency_limit=4000, lower_frequency_limit=20,
    filterbank_channel_count=40, dct_coefficient_count=13, name=None
)

Mel Frequency Cepstral Coefficients are a way of representing audio data that's been effective as an input feature for machine learning. They are created by taking the spectrum of a spectrogram (a 'cepstrum'), and discarding some of the higher frequencies that are less significant to the human ear. They have a long history in the speech recognition world, and https://en.wikipedia.org/wiki/Mel-frequency_cepstrum is a good resource to learn more.

Args
spectrogram	A Tensor of type float32. Typically produced by the Spectrogram op, with magnitude_squared set to true.
sample_rate	A Tensor of type int32. How many samples per second the source audio used.
upper_frequency_limit	An optional float. Defaults to 4000. The highest frequency to use when calculating the ceptstrum.
lower_frequency_limit	An optional float. Defaults to 20. The lowest frequency to use when calculating the ceptstrum.
filterbank_channel_count	An optional int. Defaults to 40. Resolution of the Mel bank used internally.
dct_coefficient_count	An optional int. Defaults to 13. How many output channels to produce per time slice.
name	A name for the operation (optional).

Returns
A Tensor of type float32.