recognition

在仿真语音增强时，往往需要向纯净语音中添加适当的噪声然后作仿真对比，这个程序正是实现这了个功能。(When the speech enhancement is emulation, it is often necessary to add appropriate noise to the pure speech and make a simulation contrast. This program is exactly the function of this program.)

LMS自适应滤波器的matlab源码 文件大小不够，所以加了个图(LMS adaptive filter matlab source code file size not enough, so the addition of a map)

语音库开发工具源码，例程程序创建机读SAPI.SpVoice对象开发语音库。(Speech development tools source , routine program to create machine-readable SAPI.SpVoice speech object development .)

这是基于隐马尔可夫模型的连续语音识别代码，不同于dtw,这是个完整的工程，我把需要的voicebox也放进去了，一共用到9个子函数，包括模板的训练算法何识别算法，是完全可以使用的。(This is based on the hidden Markov model of continuous voice recognition code, different the dtw, which is a complete project, I need to put the voicebox into a total of nine sub-functions, including the template training algorithm to identify the algorithm, Is fully available.)

C语音实现Matlab corrcoef（求两个信号的互相关系数），包括了Matlab的对比验证源代码(Calculate the correlation coefficient refer the Matlab function:corrcoef)

LD3320 是一颗基于非特定人语音识别（SI-ASR：Speaker-Independent Automatic Speech Recognition）技术的语音识别/声控芯片。提供了真正的单 芯片语音识别解决方案。 LD3320 芯片上集成了高精度的A/D 和D/A 接口，不再需要外接辅助的 Flash 和RAM，即可以实现语音识别/声控/人机对话功能。并且，识别的关键词 语列表是可以动态编辑的。(Voice Recognition ；Speech Recognition ；Speech recognition technology )

语音识别需要用到的函数，在你的程序中可直接调用工具箱中的函数(Needed by the voice recognition function in your program can directly call the functions in the toolbox)

基于LMS(最小均方误差算法)的自适应滤波 基于LMS(最小均方误差算法)的自适应滤波(based on the LMS (MMSE) algorithm based on the LMS adaptive filtering (minimum mean square error algorithm) the adaptive filtering based on the LMS (minimum mean square error algorithm) Adaptive Filter)

手机端蓝牙连接设备（以小车为例），通过按键、本地语音识别（pocketsphinx）和重感控制设备，蓝牙连接地址在BluetoothTools中修改，本地需要配置NDK环境才能编译。(Bluetooth mobile client devices (for example in the car), buttons, local speech recognition (pocketsphinx) and heavy sense of control devices, Bluetooth connectivity address BluetoothTools modify the local environment can be configured to compile NDK.)

fastICA用于盲源分离，文件中有三个语音文件进行混合后再分离。(FastICA is used for blind source separation, in which three voice files are mixed and then separated.)