How do you turn an object into a matrix for the posterior function?

I'm trying to write a code that can recognize different digits of numbers in a selected sound file and transfer those digits into text--a word recognition program. I'm having trouble with the posterior function, which I'm trying to input a gmm distribution model into. Everytime I do, though, it gives me an error that I can't, so I'm not really sure how to get it to work. The code right now is:

% Define system parameters
speech = data;                      % data is a sound file of some spoken digits
seglength = 160;                    % Length of frames
  overlap = seglength/2;              % # of samples to overlap
  stepsize = seglength - overlap;     % Frame step size
  nframes = length(speech)/stepsize-1;

% Visualizes the power spectral density estimates of each spoken digit in 'speech'
   order = 12;
    nfft = 512;
    Fs = 22050;
    pyulear(speech,order,nfft,Fs);

% Number of Gaussian component densities
M = 8;
    model_1 = gmdistribution.fit(matrix_ones,M);
    model_2 = gmdistribution.fit(matrix_twos,M);
    model_3 = gmdistribution.fit(matrix_threes,M);
    model_4 = gmdistribution.fit(matrix_fours,M);
    model_5 = gmdistribution.fit(matrix_fives,M);
    model_6 = gmdistribution.fit(matrix_sixes,M);
    model_7 = gmdistribution.fit(matrix_sevens,M);
    model_8 = gmdistribution.fit(matrix_eights,M);
    model_9 = gmdistribution.fit(matrix_nines,M);
    model_10 = gmdistribution.fit(matrix_tens,M,'regularize',1e-5);

% Find the digit model with the maximum a posteriori probability for the
% set of test feature vectors, which reduces to maximizing a log-likelihood
% value
    [P, log_like] = posterior(model_1, speech);

and everytime I run it, I get

Warning: Failed to converge in 100 iterations for gmdistribution with 8 components 
> In gmcluster (line 202)
In gmdistribution.fit (line 98)
In word_classifier (line 58) 
Error using checkdata (line 18)
  X must be a matrix with 10 columns.
Error in gmdistribution/posterior (line 24)
  checkdata(X,obj);
Error in word_classifier (line 74)  %the name of my file
  [P, log_like] = posterior(model_1, speech);

I have no idea what to do, I've tried replacing model_1 with a cell array of all the models, I've tried using the matrixes, and I need help :(

[Walter Roberson]

Have you tried increasing the maximum number of iterations ?

[Jonathan Fisher]

How would I do that??

Answer 1

[Chris Perkins]

Hi Jonathan,

The error given in your sample output means that there is a dimension mismatch between the two inputs to the "posterior" function. Check the size of each input - you likely will need to alter one so they have the same dimensions.