搜索资源列表
hmm的c++语言实现
- 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
cdhmm
- matlab下实现的用于语音识别的一些算法，包括hmm参数提取，viterbi识别算法，mfcc参数提取算法，端点检测算法等，对于做语音识别的来说都是很有用的-under Matlab for the voice recognition algorithm, including hmm parameter extraction, Recognition Viterbi algorithm, mfcc parameter extraction algorithm, endpoint detecti
ViterbiSearch
- Viterbi Search 语音识别中HMM模型用到的Viterbi Search 源代码，包括测试用的WAV文件和TCL脚本-Viterbi Search Speech Recognition HMM used in the Viterbi Sea rch source code, including testing of WAV files and TCL scr ipt
cdhmm
- viterbi识别代码以及给出了数字0-9的HMM模型,由M语言实现,已经调试通过.
hmm-viterbi-c
- 下载的一个不错的HMM程序，主要实现HMM中的viterbi最佳路径选择算法，用vc编写，可以根据自己需要参考修改 this is a excellent HMM program,it completes the VITERBI algorithm in HMM.
hmm-1.03.tar.gz
- 语音识别中经典的HMM算法，包括产生序列、测试和参数训练，由C语言编写。, In speech recognition classical HMM algorithm, including has the sequence, the test and the parameter training, compiles by the C language.
Chinese-Word-Segment-And-POS-Tagger
- 实现了中文分词和词性标注程序。分词方法采用“三词正向最长匹配”。词性标注使用HMM方法，用Viterbi算法实现。“三词正向最长匹配”保持了“正向最长匹配算法”快速的特点，同时提高了分词的准确性。-Chinese word segmentation and implemented procedures for POS tagging. Segmentation Methods, " the longest three-match positive words." POS tag
Create
- Speech Recognition system using HMM...includes Viterbi , Forwarding and Backtracking Algorithm
viterbi
- viterbi算法详细介绍，结合例子说明hmm模型-Details viterbi algorithm, combined with examples of model hmm
HMM_v1
- 內含有FORWARD,BACKWARD,VITERBI可以參考-HMM
hmm
- 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
HMMforspeechrecogntion
- 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-Welc
hmm
- 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；trai
weitebisuanfa
- 维特比算法 寻找最可能的隐藏状态序列(Finding most probable sequence of hidden states) 对于一个特殊的隐马尔科夫模型(HMM)及一个相应的观察序列，我们常常希望能找到生成此序列最可能的隐藏状态序列。 -Viterbi algorithm to find the most likely hidden state sequence (Finding most probable sequence of hidden states) for a
voice
- 在分析语音特征提取方法基础上提出一种改进组合算法,并采用HMM 声学模型和Viterbi 算法进行模式训练和识别.-Speech feature extraction method in the analysis based on the combination of an improved algorithm, and using HMM acoustic model and the Viterbi algorithm for model training and recognition.
hmm
- 此代码包含了HMM的backward算法，viterbi算法以及，前后向算法-This code includes backward,vitibi and Baum-Welch algorithm of HMM.
hmm-ViterbiPalgorithm
- 介绍了HMM模型几种算法中的一种Viterbi Algorithm，并给出了其实现程序-HMM model introduced several algorithms in an Viterbi Algorithm, and gives its realization procedure
Sfenciie
- 分词程序，HMM模型训练，维特特比解码，有说明文档。可直接使用。 -Segmentation process, HMM model training, Viterbi decoding, and documentation. Complete source code can be used directly.