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Description: 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
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Size: 8119 |
Author: 宋敏 |
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Description: HMM模型训练用的Forward-Backward Algorithm，包括几年WAV文件和测试用的TCL脚本文件-HMM training with the Forward-Backward Algorithm. years, including WAV and test the TCL script file
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Size: 184738 |
Author: liangtao |
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Description: 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
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Size: 8192 |
Author: 宋敏 |
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Description: Matlab中有关HMM的函数集。给出了详细的源代码，可以用于hMM在各个领域的研究和开发-Matlab the HMM Function Set. Given the detailed source code, hMM can be used in various fields of research and development
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Size: 26624 |
Author: 蒋荣 |
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Description: HMM模型训练用的Forward-Backward Algorithm，包括几年WAV文件和测试用的TCL脚本文件-HMM training with the Forward-Backward Algorithm. years, including WAV and test the TCL script file
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Size: 184320 |
Author: liangtao |
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Description: 隐马尔可夫模型演示,給出向前矩阵和向后矩阵-Hidden Markov Model presentation given matrix forward and backward matrix
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Size: 3627008 |
Author: 陈厚宇 |
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Description: 实现了隐马尔可夫模型的算法。可用向前算法和向后算法对模型进行训练。-Realize the hidden Markov model algorithms. Algorithm can be used forward and backward algorithm for training the model.
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Size: 3603456 |
Author: waterlily |
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Description: This a hidden Markov model (HMM) modeling program. Forward-backward algorithm is implemented to learn a model under maximum likelihood criterion.-This is a hidden Markov model (HMM) modeling program. Forward-backward algorithm is implemented to learn a model under maximum likelihood criterion.
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Size: 2911232 |
Author: SUNGWOONG KIM |
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Description: HMM（隐马尔可夫模型）的matlab算法代码-HMM (Hidden Markov Model) algorithm matlab code
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Size: 34816 |
Author: 刘子豪 |
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Description: ：为了使应力变异在顽健语音识别系统中能够达到较好的识别效果，研究了基于隐马
尔可夫模型(HMM)的自适应技术，提出了将最大后验概率(MAP)和最大似然回归方法(MLLR)用
于应力变异语音的自适应中。实验结果表明，与基本系统相比，两种方法均有效地提高系统识别
率。以SD为初始模型的最大后验概率方法在150个训练样本时识别效果最好，可以达到90．4％ 。-: In order to stress variation in the robustness of speech recognition system can achieve better recognition results, based on Hidden Markov Model (HMM) of adaptive technology, put forward a maximum a posteriori probability (MAP) and Maximum Likelihood regression (MLLR) for the stress of the adaptive variation in voice. The experimental results show that compared with the basic system, both methods are effective to improve the system recognition rate. SD as the initial model to the maximum a posteriori probability method in 150 training samples to identify the best, can reach 90.4 .
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Size: 234496 |
Author: 尹江波 |
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Description: 用C语言实现HMM的前向、后向和viterbi搜索算法-use C language to implement the forward, back and viterbi algorithms
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Size: 17408 |
Author: hoper1 |
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Description: 根据隐马尔可夫模型，利用马尔可夫链前向算法，用于估值问题。-HMM-FORWARD
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Size: 1024 |
Author: 李涵 |
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Description: 马尔可夫链的前向和后向算法，在隐马尔可夫模型中用于学习问题的-HMM-FORWARED-BACKWORD
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Size: 1024 |
Author: 李涵 |
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Description: Factorial hidden markov model and compute likelihood per each cycle with train test and validation set. train HMM used Backward-Forward Algorithm.
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Size: 484352 |
Author: ali |
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Description: 用c实现hmm,给定观察值序列和HMM模型，利用前向后向算法求取其概率-Using c to achieve hmm, for a given sequence of observations and the HMM model, using forward and backward algorithm to compute the probability
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Size: 1024 |
Author: |
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Description: 该模型包括两个程序：
1、根据观察序列创建一个HMM模型，利用BW算法估计HMM的参数。
2、根据已知的观察序列和HMM模型，估计观察序列的概率值，利用Forward算法
注：在HMM.cpp中分别有这两个主程序，运行一个的时候注释另一个。-The model includes two procedures: 1 sequence to create a HMM based on the observed model, the BW algorithm estimates the parameters of HMM. 2, according to the known sequence and the HMM observation model, estimates the probability of observing the value of the sequence, the use of Forward Algorithm Note: HMM.cpp, respectively, the two main program, when running a note to another.
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Size: 872448 |
Author: 周金旺 |
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Description: Patter Classification Duda 2nd 书中Example的代码 Hidden Markov Models前向算法，后向算法以及译码算法-HMM Forward Algorithm
HMM Backward Algorithm
HMM Decoding Algorithm
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Size: 3072 |
Author: 裴圆丽 |
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Description: 该模型包括两个程序：
1、根据观察序列创建一个HMM模型，利用BW算法估计HMM的参数。
2、根据已知的观察序列和HMM模型，估计观察序列的概率值，利用Forward算法
注：在HMM.cpp中分别有这两个主程序，运行一个的时候注释另一个。-The model consists of two procedures: one to create an HMM model, based on the observed sequence, the use of the BW algorithm to estimate the HMM parameters. 2, according to the known observation sequence and the HMM model, the estimated probability of the observed sequence values using the Forward algorithm Note: HMM.cpp in these two main program, running a time annotation another.
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Size: 873472 |
Author: chenkan |
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Description: 离散HMM的matlab程序，包含有前向—后向算法、 Baum-Welch算法以及Vertebi算法(The matlab program of discrete HMM, including forward-backward algorithm, Baum-Welch algorithm and Vertebi algorithm)
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Size: 112640 |
Author: 雨下一整晚128 |
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Description: 隐马尔科夫实现，包含forward-hmm, Viterbi-hmm, Baum-Welch-hmm(Hidden Markov implementation, including forward-hmm, Viterbi-hmm, Baum-Welch-hmm)
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Size: 103424 |
Author: fassial |
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