Caution

You're reading an old version of this documentation. If you want up-to-date information, please have a look at 0.10.2.

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:

  1. The inverse DCT is applied to the MFCCs

  2. 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:
UserWarning

due to critical values in lifter array that invokes underflow.