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[Speech/Voice recognition/combine] hmm的c++语言实现 DL : 3: c++实现HMM，向前向后算法，Viterbi算法，Baum-Welch算法。其中包括用c++定义的HMM数据结构。全部是cpp和h的文件-c achieve HMM, forward backward algorithm, Viterbi algorithm, Baum-Welch algorithm. C including the use of the HMM definition data structure. Cpp all the documents and h
Update : 2008-10-13 Size : 7.93kb Publisher : 宋敏
[Speech/Voice recognition/combine] baum DL : 0: 在语音识别的hmm模型中使用matlab对语音信号进行训练的把baum源代码-in Speech Recognition hmm use Matlab model of voice signals training source put BAUM
Update : 2008-10-13 Size : 1019byte Publisher : 吴斌
[Speech/Voice recognition/combine] HMMmodel DL : 0: This code implements in C++ a basic left-right hidden Markov model and corresponding Baum-Welch (ML) training algorithm. It is meant as an example of the HMM algorithms described by L.Rabiner (1) and others. Serious students are directed to the sources listed below for a theoretical description of the algorithm. KF Lee (2) offers an especially good tutorial of how to build a speech recognition system using hidden Markov models.
Update : 2008-10-13 Size : 15.26kb Publisher : aaaaaaa
[Other resource] Hidden_Markov_model_for_automatic_speech_recogniti DL : 0: Hidden_Markov_model_for_automatic_speech_recognition This code implements in C++ a basic left-right hidden Markov model and corresponding Baum-Welch (ML) training algorithm. It is meant as an example of the HMM algorithms described by L.Rabiner (1) and others. Serious students are directed to the sources listed below for a theoretical description of the algorithm. KF Lee (2) offers an especially good tutorial of how to build a speech recognition system using hidden Markov models.
Update : 2008-10-13 Size : 22.93kb Publisher : 张志
[Audio program] ImageFilterBasedP2DHMTModelinWaveletDomain DL : 0: 文章提出了一种基于小波域伪二维隐Markov 树（P2DHMT）的图像的滤波新方法。首先建立了小波域的伪 2DHMT 模型，给出了基于EM、Baum-Welch 等算法的模型参数估计方法；
Update : 2008-10-13 Size : 294.28kb Publisher : wang
[Communication] Baum-Eagon-inequality DL : 0: introduce a famous inequality in statistical signal processing. This inequality can be used widely in equalization and communication signal processing
Update : 2008-10-13 Size : 2.07mb Publisher : kun
[Speech/Voice recognition/combine] hmm的c++语言实现 DL : 0: c++实现HMM，向前向后算法，Viterbi算法，Baum-Welch算法。其中包括用c++定义的HMM数据结构。全部是cpp和h的文件-c achieve HMM, forward backward algorithm, Viterbi algorithm, Baum-Welch algorithm. C including the use of the HMM definition data structure. Cpp all the documents and h
Update : 2025-02-17 Size : 8kb Publisher : 宋敏
[Speech/Voice recognition/combine] baum DL : 0: 在语音识别的hmm模型中使用matlab对语音信号进行训练的把baum源代码-in Speech Recognition hmm use Matlab model of voice signals training source put BAUM
Update : 2025-02-17 Size : 1kb Publisher :
[Speech/Voice recognition/combine] HMMmodel DL : 0: This code implements in C++ a basic left-right hidden Markov model and corresponding Baum-Welch (ML) training algorithm. It is meant as an example of the HMM algorithms described by L.Rabiner (1) and others. Serious students are directed to the sources listed below for a theoretical description of the algorithm. KF Lee (2) offers an especially good tutorial of how to build a speech recognition system using hidden Markov models.
Update : 2025-02-17 Size : 15kb Publisher : aaaaaaa
[AI-NN-PR] Hidden_Markov_model_for_automatic_speech_recogniti DL : 1: Hidden_Markov_model_for_automatic_speech_recognition This code implements in C++ a basic left-right hidden Markov model and corresponding Baum-Welch (ML) training algorithm. It is meant as an example of the HMM algorithms described by L.Rabiner (1) and others. Serious students are directed to the sources listed below for a theoretical description of the algorithm. KF Lee (2) offers an especially good tutorial of how to build a speech recognition system using hidden Markov models.
Update : 2025-02-17 Size : 23kb Publisher :
[Program doc] Baum-Eagon-inequality DL : 0: introduce a famous inequality in statistical signal processing. This inequality can be used widely in equalization and communication signal processing
Update : 2025-02-17 Size : 2.07mb Publisher : kun
[Documents] HMM1guide DL : 0: How to use the HMM toolbox HMMs with discrete outputs Maximum likelihood parameter estimation using EM (Baum Welch)
Update : 2025-02-17 Size : 16kb Publisher : q
[matlab] baum-welch DL : 2: 该程序实现了Baum-Welch算法，对于通信里面的调制解调有很大帮助，其次，该程序具有通用性。-The program achieved the Baum-Welch algorithm, for the communication modem inside helps a lot, and secondly, the program has the versatility.
Update : 2025-02-17 Size : 1kb Publisher : 刘红
[Windows Develop] EM_baumWelch DL : 0: 采用Baum-Welch重估计算法对隐马尔科夫模型进行训练，使得结果达到最优化-Using Baum-Welch re-estimation algorithm for training hidden Markov models, making the results of optimized
Update : 2025-02-17 Size : 16kb Publisher : king
[Speech/Voice recognition/combine] HMMforspeechrecogntion DL : 1: 一个可执行的HMM语音识别程序例程，实现了对10个数字音的识别程序，包含了HMM语音识别中的分段，MFCC特征提取，Baum-Welch训练，及Viterbi等算法，通过此例程可以很好的理解HMM的算法原理-An executable HMM-based 10 digits speech recogntion program example. this code zip file includes segmentation, MFCC feature extraction, Baum-Welch based re-estimation and Viterbi algorithm involved in HMM. it helps much better understand the HMM algorithm and its application for speech recogntion.
Update : 2025-02-17 Size : 1.13mb Publisher : wh
[matlab] cdhmm DL : 0: 连续隐马尔可夫识别程序。包含的模块，可以比较完整地进行语言识别。主要模块： Test.m Train.m viterbi.m baum.m pdf.m recog.m mixture.m mfcc.m -speech recognize using HMM include 11 matlab fuction: Test.m Train.m viterbi.m baum.m pdf.m recog.m mixture.m mfcc.m
Update : 2025-02-17 Size : 525kb Publisher : JF
[matlab] baum DL : 0: this document is about baum-welch algorithm
Update : 2025-02-17 Size : 97kb Publisher : sillyp
[Speech/Voice recognition/combine] hmm DL : 0: hmm文件时运用HMM算法实现噪声环境下语音识别的。其中vad.m是端点检测程序；mfcc.m是计算MFCC参数的程序；pdf.m函数是计算给定观察向量对该高斯概率密度函数的输出概率；mixture.m是计算观察向量对于某个HMM状态的输出概率，也就是观察向量对该状态的若干高斯混合元的输出概率的线性组合；getparam.m函数是计算前向概率、后向概率、标定系数等参数；viterbi.m是实现Viterbi算法；baum.m是实现Baum-Welch算法；inithmm.m是初始化参数；train.m是训练程序；main.m是训练程序的脚本文件；recog.m是识别程序。-hmm HMM algorithm file using speech recognition in noisy environments. Which is the endpoint detection process vad.m mfcc.m procedure is to calculate the MFCC parameters pdf.m function is calculated for a given observation vector of the Gaussian probability density function of output probability mixture.m is to calculate the observation vector for a HMM state output probability of observation vector is the number of Gaussian mixture per state output probability of the linear combination getparam.m before the calculation of the probability function, backward probability, calibration coefficients and other parameters viterbi.m is Viterbi algorithm implementation baum.m Baum-Welch algorithm to achieve inithmm.m is the initialization parameters train.m is the training program main.m training program is a script file recog.m is to identify procedures.
Update : 2025-02-17 Size : 526kb Publisher : 于军
[matlab] viabw DL : 0: 用viterbi算法和baum-welch训练找到和更新best path-find best path using Viterbi algorithm and Baum-Welch training
Update : 2025-02-17 Size : 2kb Publisher : 杨帆
[Other] baum DL : 0: 隐马尔可夫模型算法程序中的baum算法，一般用来调用-HMM algorithm program baum algorithm, generally used to call
Update : 2025-02-17 Size : 1kb Publisher : 贺贤

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