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。

基于GMM的概率神经网络PNN具有良好的泛化能力，快速的学习能力，易于在线更新,并具有统计学的贝叶斯估计理论基础，已成为一种解决像说话人识别、文字识别、医疗图像识别、卫星云图识别等许多实际困难分类问题的很有效的工具。而且PNN不但具有GMM的大部分优点，还具有许多GMM没有的优点，如强鲁棒性，需要更少的训练语料，可以和其他网络其他理论无缝整合等。-GMM based probabilistic neural network PNN good generalization ability, the ability to learn fast, easy online updates, and with the Bayesian statistical theory based on estimates, and has become a solution as speaker recognition, text recognition, medical image recognition, satellite images and other real recognition when difficulties classification of very effective tool. But GMM PNN is not only the most advantages, but also has many advantages GMM not as strong robustness, require less training corpus, and other networks to other theories, such as seamless integration.

XChat TTS script is an perl written XChat2 script that speaks out messages in irc channels, and more. It provides an interface to setup the functions or view the online help. -XChat TTS is an perl script written XChat2"s at 5 that speaks out messages in irc channels. and more. It provides an interface to setup the f unctions or view the online help.

语音信号分帧加窗程序，许多程序包里都没有的！-Speech signal windowed framing procedure, many programs do not have the bag!

HMM语音识别Matlab实现代码,基于隐马尔可夫模型.

读mp3文件格式的matlab 源程序-Reading of mp3 file format matlab source

这是一个公式编辑器，编写一个微型非所见即所得公式编辑器，对于输入的源代码进行分析，判断语法是否正确，如果正确则输出对应的公式。 -This is a formula editor, the preparation of a miniature non-WYSIWYG formula editor, enter the source code for an analysis to determine whether the grammar is correct, if the correct output corresponding to the formula.

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一种语音段起止端点检测新方法.rar格式为ｖｉｐ-made available a voice of a new endpoint detection methods. Rar format vip

LMS算法实现自适应滤波 clear close all clc N=10000 设置仿真长度 信号产生参数设定 a1=-0.195 a1=-1.5955 a2=0.95 R0=[1,a1,a2 a1,1+a2,0 a2,a1,1] p=[1,0,0] r=inv(R0)*p 计算理论自相关函数 R=[r(1),r(2) r(2),r(1)] 生成理论自相关矩阵 p1=[r(2),r(3)] 生成互相关 h=inv(R)*p1 计算维纳解 Jmin=r(1)-h *p1 计算维纳解时最小均方误差 u=1/sum(eigs(R- LMS算法实现自适应滤波 clear close all clc N=10000 设置仿真长度 信号产生参数设定 a1=-0.195 a1=-1.5955 a2=0.95 R0=[1,a1,a2 a1,1+a2,0 a2,a1,1] p=[1,0,0] r=inv(R0)*p 计算理论自相关函数 R=[r(1),r(2) r(2),r(1)] 生成理论自相关矩阵 p1=[r(2),r(3)] 生成互相关 h=inv(R)*p1 计算维纳解 Jmin=r(1)-h*p1 计算维纳解时最小均方误差 u=1/sum(eigs(R))

文本语音（Text-to-Speech，以下简称TTS），基于MSTTS,它的作用就是把通过TTS引擎把文本转化为语音输出。代码示范了如何运用Microsoft Speech SDK 建立自己的文本语音转换应用程序。