用matlab仿真实现语音信号处理中分析合成语音的lms算法

采用VC＋＋编程和G.729协议，实现语言的实时通信，内含源代码。-using VC++ programming and G.729 agreement, the realization of real-time communication language, containing the source code.

模式识别中的联机字符识别，包括联机手写数字识别和联机数字、英文字符及汉字识别算法实现源代码-pattern recognition of Character Recognition on-line, including on-line handwriting recognition and on-line digital figures English characters and character recognition algorithm source code

差分脉冲编码调制（DPCM）的matlab模块仿真，实现抽样，量化，预测，编码并解码，欢迎下载使用，我自己编的-Differential pulse code modulation (DPCM) of matlab simulation module, the realization of the sample, quantification, prediction, coding and decoding, welcome to download, I own the

一个测试dtw算法的程序，A program test the dtw-an algorithm testing procedures, test the A program dtw

对于语音和图像的数字信号处理基本知识的介绍，对信号处理的各个基本知识可以有个大概的认识-A rough introduction for the dsp of speech and video.It could give you a basic knowledge of signal processing.

G.723语音编码 The source code has been modified by simplifying the ADPCM algorithm to increase running speed. Here, the quantizer scale factor, y(k), is determined by "unlocked" factor yu(k) only. The factor yl(k) and speed-contral factor al(k) are ignored.-G.723 speech coding The source code has been modified by simplifying the ADPCM algorithm to increase running speed. Here, the Quantizer scale factor, y (k), is determined by "unlocked" factor yu (k) only. The factor yl (k) and speed-contral factor al (k) are ignored.

语音的消噪程序，传统普减法的改进，有效去除背景噪声-Speech de-noising process, the traditional S & P subtraction improvements, effectively remove background noise

说话人识别或语音识别是认识到人们从他们的声音的任务。这种系统提取语音特征，它们建模和使用它们来认出的人从他的声音。说话人识别有历史约会回一些四个几十年来，几个模拟滤波器的输出在哪里上匹配的时间的平均值。说话人识别使用已发现不同个体之间的语音声学特征。这些声音的模式反映这两个解剖 （例如，大小和形状的喉咙和口腔） 和学到的行为模式 （例如，音调，演讲风格）。这个学习模式纳入语音模板 （后者称为"眼纹，声纹"）

cvsd算法中在ccs环境下的c 文件-CVSD algorithm ccs environment in the c file

实现声音实时录音加放送。。。附带源代码。主要特色是：可以选择录音质量！比WINDOW 自带的好多了-Realize real-time voice recording plus delivery. . . Incidental to the source code. Main features are: the option of recording quality! WINDOW own than the much better