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利用HMM的方法的三种语音识别算法
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时间:2019-12-21
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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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