Description: Getting Started on the HMM, HMM in speech recognition applications to achieve some of the classic data and Matlab code that contains the Chinese data
To Search:
- [hmm] - hmm realization, including three main pa
- [sound2] - LabVIEW-based voice recognition program,
File list (Check if you may need any files):
HMM入门及在语音信号处理中的应用
...............................\A tutorial on Hidden Markov Models and selected applications in speech recognition.pdf
...............................\E6820-L10-ASR-seq.pdf
...............................\E6820-L11-ASR-sys.pdf
...............................\hmm-chap.pdf
...............................\HMM-中文课件.pdf
...............................\HMM的学习问题和解码问题研究.nh
matlab代码
..........\HMMall
..........\......\HMM
..........\......\...\#fwdback.m#
..........\......\...\#mhmm_em.m#
..........\......\...\#README.txt#
..........\......\...\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
..........\......\...\fwdback.m
..........\......\...\fwdback.m~
..........\......\...\fwdback_xi.m
..........\......\...\fwdprop_backsample.m
..........\......\...\fwdprop_backsample.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.m~
..........\......\...\mhmm_em_demo.asv
..........\......\...\mhmm_em_demo.m
..........\......\...\mhmm_logprob.m
..........\......\...\mhmm_sample.m
..........\......\...\mk_leftright_transmat.m
..........\......\...\mk_rightleft_transmat.m
..........\......\...\pomdp_sample.m
..........\......\...\publishHMM.m
..........\......\...\README.txt
..........\......\...\README.txt~
..........\......\...\testHMM.m
..........\......\...\transmat_train_observed.m
..........\......\...\viterbi_path.m
..........\......\KPMstats
..........\......\........\#histCmpChi2.m#
..........\......\........\beta_sample.m
..........\......\........\chisquared_histo.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
..........\......\........\convertBinaryLabels.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_paritioned_model_testfn.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
..........\......\........\logist2ApplyRegularized.m
..........\......\........\logist2Fit.m
..........\......\........\logist2FitRegularized.m
..........\......\........\logistK.m
..........\......\........\logistK_eval.m
..........\......\........\marginalize_gaussian.m
..........\......\........\matrix_normal_pdf.m
..........\......\........\matrix_T_pdf.m
..........\......\........\mc_stat_distrib.m
..........\......\........\mixgauss_classifier_a
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