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librosa.feature.inverse.mfcc_to_mel

librosa.feature.inverse.mfcc_to_mel(mfcc, n_mels=128, dct_type=2, norm='ortho', ref=1.0, lifter=0)[source]

Invert Mel-frequency cepstral coefficients to approximate a Mel power spectrogram.

This inversion proceeds in two steps:

The inverse DCT is applied to the MFCCs

librosa.db_to_power is applied to map the dB-scaled result to a power spectrogram

Parameters:

mfccnp.ndarray [shape=(n_mfcc, n)]

The Mel-frequency cepstral coefficients

n_melsint > 0

The number of Mel frequencies

dct_type{1, 2, 3}

Discrete cosine transform (DCT) type By default, DCT type-2 is used.

normNone or ‘ortho’

If dct_type is 2 or 3, setting norm='ortho' uses an orthonormal DCT basis.

Normalization is not supported for dct_type=1.

refnumber or callable

Reference power for (inverse) decibel calculation

lifternumber >= 0

If lifter>0, apply inverse liftering (inverse cepstral filtering):

M[n, :] <- M[n, :] / (1 + sin(pi * (n + 1) / lifter) * lifter / 2)

Returns:

Mnp.ndarray [shape=(n_mels, n)]: An approximate Mel power spectrum recovered from mfcc

Warns: