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用matlab编程来实现,用HMM模型进行孤立词的语音识别-using Matlab programming to achieve with HMM term isolation of Speech Recognition
Update : 2008-10-13 Size : 1.09kb Publisher : 李凌

用matlab编写的基于hmm模型的语音识别程序,但是调试好像有些问题,欢迎指正:)-prepared using Matlab model based hmm voice identification procedures, but there seems to be some debugging, and welcomes the correction :)
Update : 2025-02-17 Size : 322kb Publisher : dorothy

用matlab编程来实现,用HMM模型进行孤立词的语音识别-using Matlab programming to achieve with HMM term isolation of Speech Recognition
Update : 2025-02-17 Size : 1kb Publisher : 李凌

这个是隐markov模型中viterbi算法实现的一个具体实例程序 很好-This is a hidden markov models Viterbi Algorithm in a specific example of good procedures
Update : 2025-02-17 Size : 1kb Publisher : juliamie

基于HMM的语音识别的一些资料,用matlab实现。希望对大家有帮助-HMM-based speech recognition of some of the information, using matlab realize. Hope everyone has to help
Update : 2025-02-17 Size : 198kb Publisher : 黄卓芬

DL : 0
用Matlab开发的基于HMM的语音识别系统-Developed using Matlab-based HMM speech recognition system
Update : 2025-02-17 Size : 525kb Publisher : 庄冕

Speech Recognition system using HMM...includes Viterbi , Forwarding and Backtracking Algorithm
Update : 2025-02-17 Size : 6kb Publisher : shekhar

speech recognition using hidden markov model making it speaker independent Using Matlab 7.5[2008b]
Update : 2025-02-17 Size : 9.57mb Publisher : kani

Demonstration for Digit Recognition (and later speech recognition) using HMM Models
Update : 2025-02-17 Size : 80kb Publisher : sam

Speech recognition using H-Speech recognition using HMM
Update : 2025-02-17 Size : 9.45mb Publisher : nagendra

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

在MATLAB 环境下利用语音工具箱Voice Box 实现基于连续概率密度隐含马尔科夫模型的汉语语音识别系统-Using Voice- Box a mandarin speech recognition system is realized based on CDHMM in MATLAB environment.
Update : 2025-02-17 Size : 206kb Publisher : 江丰安迪

DL : 0
基于matlab的语音识别代码(使用HMM算法的)-Matlab speech recognition code (using the HMM algorithm)
Update : 2025-02-17 Size : 71kb Publisher : echo

DL : 0
语音识别的HMM模型,采用matlab,对新手很有帮助的-HMM model for speech recognition using matlab helpful to novice
Update : 2025-02-17 Size : 113kb Publisher : apple

基于HMM的语音识别系统的MATLAB仿真,采用多数据同时训练法训练模板-Speech recognition system based on HMM of MATLAB simulation, using much data at the same time training method training template
Update : 2025-02-17 Size : 11kb Publisher : jimmy

基于GMM-HMM的语音识别程序,自带训练和测试数据,使用的是MATLAB。-GMM-HMM-based speech recognition program, comes with the training and test data, using MATLAB.
Update : 2025-02-17 Size : 28.41mb Publisher : 李道玮

DL : 0
利用matlab写成的窄带噪声发生,完整的基于HMM的语音识别系统,STM32制作的MP3的全部资料。- Using matlab written narrowband noise occurs, Complete HMM-based speech recognition system, STM32 all the information produced by the MP3.
Update : 2025-02-17 Size : 10kb Publisher : 张福军

The speech signal for the particular isolated word can be viewed as the one generated using the sequential generating probabilistic model known as hidden Markov model (HMM). Consider there are n states in the HMM. The particular isolated speech signal is divided into finite number of frames. Every frame of the speech signal is assumed to be generated from any one of the n states. Each state is modeled as the multivariate Gaussian density function with the specified mean vector and the covariance matrix. Let the speech segment for the particular isolated word is represented as vector S. The vector S is divided into finite number of frames (say M). The i th frame is represented as Si . Every frame is generated by any of the n states with the specified probability computed using the corresponding multivariate Gaussian density model.
Update : 2025-02-17 Size : 769kb Publisher : Khan17

以MFCC作为特征参数,利用HMM算法进行语音识别(Speech recognition using HMM algorithm)
Update : 2025-02-17 Size : 26kb Publisher : 充满魅力人

利用了DTW和HMM语音识别技术,进行了语音识别的仿真(The speech recognition technology is simulated by using DTW and HMM speech recognition technology.)
Update : 2025-02-17 Size : 5.45mb Publisher : njhnjh
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