# MFCC classification model

I have audio samples which MFCCs i want to train, but there is a problem. I can't find a classification model, because the samples have different length and consequently the MFCC matrices will also have different lengths. My question is - which machine learning model can i use?

When utilizing MFCCs, it is common to split the MFCC matrix into pieces. Lets assume your MFCC-matrix $$\bf{M}$$ has the dimensions $$[\bf{M}]=N \times 39$$, where $$N$$ denotes your time index and you have 39 MFCC bins. Then you cut your matrix into blocks of length $$B$$ (I propose $$B=39$$ so your blocks have a square shape) and save them in a list. For the last block, you can either zero-pad until it has the same length or discard it completely. Each block has to be annotated with the label of the original audio sample.
EDIT: Actually one often takes only 13 MFCC bins. The $$N \times 39$$ matrix also contains the Deltas and DeltaDeltas of the MFCC bins.