I was able to get a dataset with MFCC coefficients. However, depending on the length of my sound file I get a different sized matrix. As in, 13 (13 MFCC coefficients) by XXX, where XXX will vary depending on the length of the sound file. Does it make sense to 'normalize it' to keep XXX consistent? If so, how? Like in this example, the size of the matrix always varies: https://archive.ics.uci.edu/ml/machine-learning-databases/00195/Test_Arabic_Digit.txt
Also, how will I feed this into a Machine Learning algorithm? (i.e. k-NN, HMM, etc.) I somewhat figured how to do it if it's just one line for each sound file (e.g. 1 by 13 for each sound). What are the steps if it's MFCC? I am a little lost here.
Thank you for your help.