搜索资源列表
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用matlab实现的语音识别的一些代码，十分经典-Using matlab to achieve a number of speech recognition code, very classic
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neural network speech recognition.
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Speech Recognition system using HMM...includes Viterbi , Forwarding and Backtracking Algorithm
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speech recognition using hidden markov model making it speaker independent
Using Matlab 7.5[2008b]
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Template based Speech Recognition using spectral features and DTW, very clear code in MATLAB
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用MATLAB进行语音识别的特征参数提取，其中包含了lpc和MFCC两种方法，并且测试通过。-Using MATLAB to carry out speech recognition feature extraction, which contains two methods lpc and MFCC, and the test.
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Demonstration for Digit Recognition (and later speech recognition) using HMM Models
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PATTERN RECOGNITION OF SPEECH USING MATLAB
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speech recognition using DTW
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The new speech recognition algoritm using the theory of Hidden Markov Models and wavelet transform is offered.
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Speech Recognition Using DTW
This is a English/Persian 0~9 digit and some primary English/Persian command recognition system which use Dynamic Time Warping (DTW). Code is developed in MATLAB 6.5 and can used in Windows platform. Program has two
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自己总结的一个基于 HHMs 语音识别的示例程序，附说明文档，Matlab程序的注释详细。希望能给予初学者帮助。-The following is an example of speech recognition program based on HMMs，and there are detailed notes in the program. May bring help to the beginner。
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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.
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speech recognition using matlab
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this a matlab code for speech recognition using discrete wavelet transform. code is working very well and good for future research work.-this is a matlab code for speech recognition using discrete wavelet transform. code is working very well and good
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this a matlab code for speech recognition using discrete wavelet transform. code is working very well and good for future research work.-this is a matlab code for speech recognition using discrete wavelet transform. code is working very well and good
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Speech recognition using mfcc and lpc in matlab
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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 sig
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The number of states in GMM as the generative model of the frames is obtained using
k-means algorithm. This also helps to initialize the mean vector and the covariance
matrix of the individual state of the GMM. The training LPC frames collected fro
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speech recognition using MFCC as a feature extraction Method
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