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_audio(mfcc, *, n_mels=128, dct_type=2, norm='ortho', ref=1.0, lifter=0, **kwargs)[source]

Convert Mel-frequency cepstral coefficients to a time-domain audio signal

This function is primarily a convenience wrapper for the following steps:

  1. Convert mfcc to Mel power spectrum (mfcc_to_mel)

  2. Convert Mel power spectrum to time-domain audio (mel_to_audio)

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
**kwargsadditional keyword arguments

Parameters to pass through to mel_to_audio

ynp.ndarray [shape=(…, n)]

A time-domain signal reconstructed from mfcc