melgmm.m

voice features for the speech recognition softeare

function model=melgmm(X,Alpha,cov_type)

%--------------------------------------------------------------------------------
% Processing of input arguments 
%----------------------------------------
if nargin < 3, cov_type = 'full'; end
[dim, num_data] = size( X );
  
% ------------------------------------
ncomp = size(Alpha,1);

model.Mean = zeros(dim,ncomp);
model.Cov = zeros(dim,dim,ncomp);

for i=1:ncomp,

  nconst = sum( Alpha(i,:) );
  % if it is NaN
  nconst(isnan(nconst)) = 1; 
  %nconst = isnan(nconst);
  if ~nconst,
    model.Mean(:,i) = NaN*ones(dim,1);
    model.Cov(:,:,i) = NaN*ones(dim,dim);
    model.Prior(i) = 0;
  else
    model.Mean(:,i) = X*Alpha(i,:)'/nconst;
    XC = X - model.Mean(:,i)*ones(1,num_data);
    
    switch cov_type,
      case 'full'
        model.Cov(:,:,i) = (XC.*(repmat(Alpha(i,:),dim,1)))*XC'/nconst;
      case 'diag'
        model.Cov(:,:,i)=diag(sum(XC.*(ones(dim,1)*Alpha(i,:)).*XC,2))/nconst;
      case 'spherical'        
        model.Cov(:,:,i) = eye(dim)*...
          sum(sum(XC.^2.*(ones(dim,1)*Alpha(i,:)) ))/(nconst*dim);
      otherwise
        error('Wrong cov_type.');
    end
  
    model.Prior(i) = nconst/num_data;
  end
end  
  

return;