I do interactive voice processing system, installed 6/29/05 speechkit support. F...

c++实现HMM，向前向后算法，Viterbi算法，Baum-Welch算法。其中包括用c++定义的HMM数据结构。全部是cpp和h的文件-c achieve HMM, forward backward algorithm, Viterbi algorithm, Baum-Welch algorithm. C including the use of the HMM definition data structure. Cpp all the documents and h

matlab时域处理的相关程序，通过matlab调用实现-matlab deal with time-domain procedures, through the realization of matlab call

一个通过语音控制电脑动作的程序,使用到了微软speech sdk.在微软智能代理（Agent）技术上，整合了语音合成和语音识别技术.-A computer through voice control action procedures, the use of the Microsoft speech sdk. In Microsoft Agent (Agent) technology, the integration of speech synthesis and voice recognition technology.

我是做语音识别的，这是我做的一个关于端点检测的小程序，里面还有一个工具包-I have to do speech recognition, which is what I am doing on a small endpoint detection procedures, there is also a tool kits

基于LABVIEW的语音识别程序子模块，完成识别、滤波、录音、提取特征等功能

能实现语音共振峰提取，大家可直接下载使用。-Able to voice formant extraction, we can directly download.

不定长信号合并，％执行信号相加： y(n) = x1(n)+x2(n) ％调用方式：[y,n] = sigadd(x1,n1,x2,n2) ％ y：叠加后的信号序列的序列号，包括n1和n2 ％ x1： 第一个信号序列，序列号为n1 ％ x2：第二个信号序列，序列号为n2(n2可以与n1不同)-Indefinite long-Signal merger, add up to the implementation of signal: y (n) = x1 (n)+ X2 (n) call the way: [y, n] = sigadd (x1, n1, x2, n2) y: Superposition signal sequence after the serial number, including the n1 and n2 x1: the first signal sequence, the serial number for n1 x2: the second signal sequence, the serial number for n2 (n2 with n1 different)

用于语音识别的离散隐马尔可夫模型程序（非特定人，多个观测序列），已调试通过。-used discrete speech recognition Hidden Markov Model (non-specific, a number of observation sequence), has been through testing.

该文章是语音去噪方面的，比较新，希望对大家有帮助-The article is a voice de-noising aspects, relatively new, we want to help

用VC编的用于实时地对录音的轨迹的测试。可以自动显示-It is developed with VC.It can test the trail of speech at realtime and provide an auto display.