对隐马尔可夫模型的认识很有帮助，有发展的历史，美联社…

隐马尔科夫模型实现语音识别，该模型具有较好的识别效果，主要针对的是本科生的课程项目，有一定的学习价值。

最后打包版本小错误，来源新的实验包，音箱命名的任务，正在进行的会议系统，javaCV（OpenCV在JAVA）的测试，电话diarization（ANR项目MEDIA）。LIUM_SpkDiarization-4.2.jar，包含一个完整的jar文件，准备使用的编译版本，包括所有的类（LIUM_SpkDiarization和外部类）和GMM资源（Java的1.6）另外，下载LIUM_SpkDiarization-4.2.src.tgz gzip压缩的tar

一个简易的端点检测程序，已经实现，包括基于过零率、短时能量的双门限判决方法。-a simple endpoint detection procedures has been achieved, including on the basis of zero rate Short-term dual energy threshold judgment method.

高质量的语音处理工具箱，包括分帧，预处理，求基频等-high-quality voice processing toolkit, including the frame, pretreatment, such as for frequency

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 :)

通过ACTIVEX控件与MATLAB进行双向通信实现实时语音端点检测-through ACTIVEX control and MATLAB for two-way real-time voice communication endpoint detection

matlab中wave文件的播放功能，欢迎使用-Matlab documents were broadcast wave function, welcomed the use of

AppWizard has created this SRTest application for you.  This application not only demonstrates the basics of using the Microsoft Foundation classes but is also a starting point for writing your application. This file contains a summary of what you will find in each of the files that make up your SRTest application. SRTest.dsp     This file (the project file) contains information at the project level and     is used to build a single project or subproject. Other users can share the

基于WINDOWS的SVM的开发工具，特别适合初学者，不需要太了解SVM原理-SVM based on the Windows development tool, especially for beginners, SVM not understand much about Principle

这里主要我自己成果，是关于语音编码的，个人认为还可以，里面程序上传前经本人调试确认完全可用．有对多级矢量量化的程序（这个网上很少有），还有就是对MELP多帧参数的提取（这些网上也少见），还有就是统计子带清浊音概率的，还有一个我搜集的认为比较好的关于语音编码的英文文档．-Here the main results of my own, on the speech coding, and personally think that can also be inside the procedure before From my debugging can be used to confirm complete. There are of multi-stage vector quantization process (the online few), there is a multi-frame MELP parameters of the extraction (which are online also rare), there is statistical subband audio Qingzhuo probability, there is one I have collected think of a better speech coding on the document in English.