Project1

自动语音应答系统 硬件需要一个语音卡或一个语音modem 其中有6个类，下载包里头有详细类说明(Automatic Voice Response System hardware needs a sound card or a voice modem which six categories, Download Packet Erlitou detailed presentation on)

语音信号处理的lbg算法法在语音信号处理中非常重要 (Lbg of voice signal processing algorithms in speech signal processing is very important)

能有效实现语音合并，将两个相同采样率和相同精度的语音文件合并成为一个相同采样率和相同精度的语音文件。(Can effectively realize the merger of voice, and the two the same sampling rate and the same precision audio files into a different sampling rate and the same accuracy of voice files.)

EVC 基于CE的TTS源码，需安装语音库(TTS resource code based on wince)

G711标准的语音编解码算法。以便于对语音信号进行大量存储(speech coding)

计算语音、音频信号的信噪比程序（包含音频样本文件）(Calculation of voice, audio program signal to noise ratio (including the audio sample file))

这 里主要对LMS算法及一些改进的LMS算法（NLMS算法、变步长LMS算法、变换域LMS算法）之间的不同点进行了比较，，在传统的LMS算法的基础上发 展了LMS算法的应用。另一方面又从RLS算法的分析析中对其与LMS算法的不同特性进行了比较。 (Here the main difference between the LMS algorithm and improved LMS algorithm (NLMS algorithm, variable step size LMS algorithm, the transform domain LMS algorithm) comparison, the traditional LMS algorithm based on the development of the application of the LMS algorithm . On the other hand and from its different characteristics of the LMS algorithm of the analytical analysis of the RLS algorithm.)

基于vc++开发，dtw语音识别,MFCC参数(DTW recognice based on vc++)

这是语音播放接口组件，将语音数据输入，会播放声音。经过测试确保可用。(This is the voice player interface module, the voice data input, will play the sound. After testing to ensure that the.)

文中研究了6种常用数字调制信号识别的特征参数集，并采用决策树判别方法进行分类识别。仿真结果表明，在SNR≥5dB时，识别正确率在99 以上，且当SNR≥20dB时，识别正确率达到100 。其特点是，算法简单，识别正确率高，达到了自动分类识别的目的，并有利于实现识别的实时化。(In this paper, we study the set of characteristic parameters of the six kinds of commonly used digital modulation signal recognition, and decision tree method for classification. The simulation results show that SNR 鈮� 5dB, the correct rate more than 99 , and when SNR 鈮� 20dB, the correct rate of 100 . Which is characterized by simple algorithm to identify the correct rate, to achieve the purpose of automatic classification and recognition, and help to identify real-time.)