利用HMM的方法的三种语音识别算法

文件列表:

HMM(3个)

........\cdhmm(Matlab扩展编程带)

........\.......................\baum.m

........\.......................\getparam.m

........\.......................\hmm.mat

........\.......................\inithmm.m

........\.......................\mfcc.m

........\.......................\mixture.m

........\.......................\pdf.m

........\.......................\recog.m

........\.......................\samples.mat

........\.......................\train.m

........\.......................\vad.m

........\.......................\viterbi.m

........\HMMall

........\......\HMM

........\......\...\#dhmm_em.m#

........\......\...\#fwdback.m#

........\......\...\#README.txt#

........\......\...\#viterbi_path.m#

........\......\...\dhmm_em.m

........\......\...\dhmm_em.m~

........\......\...\dhmm_em_demo.m

........\......\...\dhmm_em_online.m

........\......\...\dhmm_em_online_demo.m

........\......\...\dhmm_logprob.m

........\......\...\dhmm_logprob_brute_force.m

........\......\...\dhmm_logprob_path.m

........\......\...\dhmm_sample.m

........\......\...\dhmm_sample_endstate.m

........\......\...\fixed_lag_smoother.m

........\......\...\fixed_lag_smoother_demo.m

........\......\...\fixed_lag_smoother_demo.m~

........\......\...\fwdback.m

........\......\...\fwdback.m~

........\......\...\gausshmm_train_observed.m

........\......\...\herbert.txt~

........\......\...\mc_sample.m

........\......\...\mc_sample_endstate.m

........\......\...\mdp_sample.m

........\......\...\mhmmParzen_train_observed.m

........\......\...\mhmm_em.m

........\......\...\mhmm_em_demo.m

........\......\...\mhmm_logprob.m

........\......\...\mhmm_sample.m

........\......\...\mk_leftright_transmat.m

........\......\...\mk_rightleft_transmat.m

........\......\...\pomdp_sample.m

........\......\...\README.txt

........\......\...\README.txt~

........\......\...\transmat_train_observed.m

........\......\...\viterbi_path.m

........\......\...\viterbi_path.m~

........\......\KPMstats

........\......\........\#histCmpChi2.m#

........\......\........\beta_sample.m

........\......\........\chisquared_prob.m

........\......\........\chisquared_readme.txt

........\......\........\chisquared_table.m

........\......\........\clg_Mstep.m

........\......\........\clg_Mstep_simple.m

........\......\........\clg_prob.m

........\......\........\condGaussToJoint.m

........\......\........\condgaussTrainObserved.m

........\......\........\condgauss_sample.m

........\......\........\cond_indep_fisher_z.m

........\......\........\cwr_demo.m

........\......\........\cwr_em.m

........\......\........\cwr_predict.m

........\......\........\cwr_prob.m

........\......\........\cwr_readme.txt

........\......\........\cwr_test.m

........\......\........\dirichletpdf.m

........\......\........\dirichletrnd.m

........\......\........\dirichlet_sample.m

........\......\........\distchck.m

........\......\........\eigdec.m

........\......\........\est_transmat.m

........\......\........\fit_partitioned_model.m

........\......\........\gamma_sample.m

........\......\........\gaussian_prob.m

........\......\........\gaussian_sample.m

........\......\........\histCmpChi2.m

........\......\........\histCmpChi2.m~

........\......\........\KLgauss.m

........\......\........\linear_regression.m

........\......\........\logist2.m

........\......\........\logist2Apply.m

........\......\........\logist2Fit.m

........\......\........\logist2FitRegularized.m

........\......\........\logistK.m

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