文件名称:MixtGaussian
介绍说明－－下载内容均来自于网络，请自行研究使用
在matlab环境运行。基于GMM的说话人识别程序源代码，可直接运行。有详细的文件资料-Matlab environment runs. GMM based speaker recognition program source code, can be directly run. Detailed documentation
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下载文件列表
MixtGaussian
............\auto
............\....\MixtGaussian.el
............\contents.gif
............\contents.png
............\footnode.html
............\images.aux
............\images.log
............\images.out
............\images.pl
............\images.tex
............\img1.gif
............\img10.gif
............\img11.gif
............\img12.gif
............\img13.gif
............\img14.gif
............\img15.gif
............\img16.gif
............\img2.gif
............\img3.gif
............\img4.gif
............\img5.gif
............\img6.gif
............\img7.gif
............\img8.gif
............\img9.gif
............\index.html
............\internals.pl
............\labels.pl
............\Makefile
............\matlab
............\......\BackFront.mat
............\......\BNT
............\......\...\consist.m
............\......\...\dist2.m
............\......\...\em_converged.m
............\......\...\forwards.m
............\......\...\forwards_backwards_mix.m
............\......\...\gaussian_prob.m
............\......\...\gmm.m
............\......\...\gmminit.m
............\......\...\gsamp.m
............\......\...\kmeans.m
............\......\...\learn_mhmm.m
............\......\...\log_lik_ghmm.m
............\......\...\log_lik_mhmm.m
............\......\...\mk_dhmm_obs_lik.m
............\......\...\mk_ghmm_obs_lik.m
............\......\...\mk_mhmm_obs_lik.m
............\......\...\mk_stochastic.m
............\......\...\normalise.m
............\......\...\sample_dhmm.m
............\......\...\sample_discrete.m
............\......\...\sample_mc.m
............\......\...\sample_mhmm.m
............\......\...\tiv_path.m
............\......\...\viterbi_path.m
............\......\BW.m
............\......\BW_hmm.m
............\......\comp_hist_pdf.m
............\......\consist.m
............\......\digits.mat
............\......\Digit_demo.m
............\......\dist2.m
............\......\em_converged.m
............\......\Ex_BackFront.m
............\......\Ex_HmmGM.m
............\......\forwards.m
............\......\forwards_backwards_mix.m
............\......\gaussian_prob.m
............\......\gausspdf.m
............\......\gausview.m
............\......\gloglike.m
............\......\gmm.m
............\......\gmminit.m
............\......\gsamp.m
............\......\histo.m
............\......\histogram2.m
............\......\init_mhmm.m
............\......\kmeans.m
............\......\learn_mhmm.m
............\......\log_lik_ghmm.m
............\......\log_lik_mhmm.m
............\......\mgaussv.m
............\......\mk_dhmm_obs_lik.m
............\......\mk_ghmm_obs_lik.m
............\......\mk_mhmm_obs_lik.m
............\......\mk_stochastic.m
............\......\normalise.m
............\......\preproc.m
............\......\recognize.m
............\......\sample_dhmm.m
............\......\sample_discrete.m
............\......\sample_mc.m
............\......\sample_mhmm.m
............\......\symbols.mat
............\......\tiv_path.m
............\......\train.m
............\......\viterbi_path.m