DSK5416的语音采集与播放,音频模块是PCM3002.本人调试过,绝对正确

PIC单片机模拟串口收发.可设置波特率。8位9位可选-PIC microcontroller analog serial transceiver. You can set the baud rate. 8 9 optional

模式识别中关于 LMSE最小均方误差算法 一中算法-pattern recognition on the wan minimum mean square error algorithm an algorithm

MATLAB仿真LMS算法完整源代码，仿真结果分析，及仿真图示-MATLAB simulation of LMS algorithm complete source code, simulation results analysis, and simulation icon

使用DirectSound和Microsoft agent实现的语音复读机- Uses DirectSound and Microsoft agent realization pronunciation duplicate reading machine

模拟语音信号的动态范围压缩算法的matlab源码-Yiu Pang音portability cavity ulcers信rabble-hung Yu Yang围压stand for goblets算Daitou tungsten cavity matlab

离散语音信号处理（麻省教材）的配套程序，其中包括最基本的语音处理程序（如谱减法，谱幅度估计，语谱图等）以及语音库。强烈推荐

语音编码的原程序,是在国外的网站下来的,没有改动可以直接在软电话下使用!-speech coding the original procedure is outside the site down, no changes may be directly in the use of soft phone!

语音识别知识讲稿，了解语音识别基本知识和基本方法的捷径-Speech Recognition knowledge speech, speech recognition to understand the basic knowledge and basic methods of shortcuts

检测语音信号的共振峰 ％ gender = gender_detector(X,Fs) ％ ％ This function will use a pitch detection algorithm to decide if the speaker is MALE(0) or FEMALE (1). ％ It is designed to work with short speech samples (up to or greater than 50 ms). The function returns a ％ 0 if X contains male speech and a 1 if it contains female speech. -the resonance peak gender_detector% gender = (X, Fs)%% This function will use a detection a pitch lgorithm to decide if the speaker is abbreviation (0) or F EMALE (1). % It is designed to work with short spe ech samples (up to or greater than 50 ms). The fun ction returns a 0% if X contains a male speech and if it contains a female speech.

LMS算法实现自适应滤波 clear close all clc N=10000 设置仿真长度 信号产生参数设定 a1=-0.195 a1=-1.5955 a2=0.95 R0=[1,a1,a2 a1,1+a2,0 a2,a1,1] p=[1,0,0] r=inv(R0)*p 计算理论自相关函数 R=[r(1),r(2) r(2),r(1)] 生成理论自相关矩阵 p1=[r(2),r(3)] 生成互相关 h=inv(R)*p1 计算维纳解 Jmin=r(1)-h *p1 计算维纳解时最小均方误差 u=1/sum(eigs(R- LMS算法实现自适应滤波 clear close all clc N=10000 设置仿真长度 信号产生参数设定 a1=-0.195 a1=-1.5955 a2=0.95 R0=[1,a1,a2 a1,1+a2,0 a2,a1,1] p=[1,0,0] r=inv(R0)*p 计算理论自相关函数 R=[r(1),r(2) r(2),r(1)] 生成理论自相关矩阵 p1=[r(2),r(3)] 生成互相关 h=inv(R)*p1 计算维纳解 Jmin=r(1)-h*p1 计算维纳解时最小均方误差 u=1/sum(eigs(R))