高斯混合模型Matlab代码

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function [GMMs,errLog,options,time] = trGmms(data,feat_type,feat_sel,m) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % %train one type GMMs corresponding to selected features. %input: % data = train data with labels; % feat_type = feature type; % m = mix number %output: % GMMs = gauss mix models; % errlog = log likehood of each iteration; % time = run time. % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% Written by Qianyong Gao %% %% Data:May 11,2006 %% %% Update:June 27,2006 by Qianyong Gao %% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% tic; if nargin < 3 m = 32; end label = unique(data(:,end)); if length(label) > 1 error('data belong to different kind of audio'); end options = foptions; options(14) = 12; options(1) = 1.0; GMMs = opt_gmm_init(data,m,options); data(:,end) = []; options(14) = 128; [GMMs.centres,post] = mykmeans(GMMs.centres,data,options); cluster_size = sum(post,1); GMMs.priors = cluster_size / sum(cluster_size); GMM_WIDTH = eps; GMMs.covars = []; %ncentres = GMMs.ncentres; %centres = GMMs.centres; %temp_data = data; for j = 1:GMMs.ncentres % Pick out data points belonging to this centre c = data(find(post(:,j)),:); if size(c,1) == 0% (size(data,1)/GMMs.ncentres)*1E-1 warning(['the ',num2str(j),'th is zero cluster']); %GMMs.priors(j) = []; %centres(j,:) = []; %ncentres = ncentres - 1; %temp_data(find(post(:,j)),:) = []; GMMs.covars = [GMMs.covars;eps*ones(1,GMMs.nin)]; else diffs = c - (ones(size(c,1),1)*GMMs.centres(j,:)); covj = sum((diffs.*diffs),1)/size(c,1); %if ~any(covj>eps) % warning('some identical input train data') % centres(j,:) = []; % GMMs.priors(j) = []; % ncentres = ncentres - 1; % temp_data(find(post(:,j)),:) = []; %elseif any(covj>eps) % GMMs.covars = [GMMs.covars;covj]; if any(covj<eps^2) warning('some bad input train data'); covj = covj + GMM_WIDTH*(covj<eps); GMMs.covars = [GMMs.covars;covj]; else GMMs.covars = [GMMs.covars;covj]; end end end %GMMs.ncentres = ncentres; %GMMs.centres = centres; %GMMs.priors = GMMs.priors/sum(GMMs.priors); %data = temp_data; options(5) = 1.0; options(14) = 30; [GMMs,options,errLog] = gmmem(GMMs,data,options); GMMs.feat = feat_type; GMMs.fd = feat_sel; time = toc;