How to compute mffc

Hi i have a problem with computation of mfcc

I have function feature_mfccs which needs mfccParams which i cumputed as a stuct but idk what windowFFT is. I tried function getDFT but iam really confused how to pass it into function feature_mfccs.

I tried to train a whole dataset based on only mfccs features but iam confused about the process a bit can anyone help please ?

function [FFT, Freq] = getDFT(signal, Fs, PLOT)

%
% function [FFT, Freq] = getDFT(signal, Fs, PLOT)
%
% This function returns the DFT of a discrete signal and the 
% respective frequency range.
% 
% ARGUMENTS:
% - signal: vector containing the samples of the signal
% - Fs:     the sampling frequency
% - PLOT:   use this argument if the FFT (and the respective 
%           frequency values) need to be returned in the 
%           [-fs/2..fs/2] range. Otherwise, only half of 
%           the spectrum is returned.
%
% RETURNS:
% - FFT:    the magnitude of the DFT coefficients
% - Freq:   the corresponding frequencies (in Hz)
%

N = length(signal);  % length of signal
% compute the magnitude of the spectrum
% (and normalize by the number of samples):
FFT = abs(fft(signal)) / N;

if nargin==2 % return the first half of the spectrum:
    FFT = FFT(1:ceil(N/2));    
    Freq = (Fs/2) * (1:ceil(N/2)) / ceil(N/2);  % define the frequency axis
else
    if (nargin==3) 
        % ... or return the whole spectrum 
        %     (in the range -fs/2 to fs/2)
        FFT = fftshift(FFT);        
        if mod(N,2)==0                      % define the frequency axis:
            Freq = -N/2:N/2-1;              % if N is even
        else
            Freq = -(N-1)/2:(N-1)/2;        % if N is odd
        end
        Freq = (Fs/2) * Freq ./ ceil(N/2);
    end
end

function ceps = feature_mfccs(windowFFT, mfccParams)

% This function computes the mfccs using the provided DFT.
% The parameters (DCT, filter banks, etc) need to have been 
% computed using the feature_mfccs_init function.
%
% ARGUMENTS:
% - windowFFT:       	the abs(FFT) of an audio frame
%                    	(computed by getDFT() function)
% - mfccParams:		algorithm parameters, as returned
%			by feature_mfccs_init()
%
% RETURNS:
% -ceps:		MFCC matrix (row i corresponds to 
%			the i-th MFCC feature sequence)
%		
% Based on Slaneys' Auditory Toolbox
% https://engineering.purdue.edu/~malcolm/interval/1998-010/


earMag = log10(mfccParams.mfccFilterWeights * windowFFT+eps);
ceps = mfccParams.mfccDCTMatrix * earMag;

Answer 1

[Walter Roberson]

[signal, Fs] = audioread('YourFile.wav');

PLOT = true;
[windowFFT, Freq] = getDFT(signal, Fs, PLOT);

mfccParams = feature_mfccs_init();
ceps = feature_mfccs(windowFFT, mfccParams);