attentionModel

验证码小识别源码程序，结合易语言位图支持库，调用易语言模块实现验证码识别。(Little recognition source code program , combined with easy language bitmap support library , call easy language module verification code recognition .)

基于FastICA相结合实现的语音信号的采集、随机混合，再通过盲分离将混合后的语音信号分离(Speech signal acquisition and random mixing based on FastICA, and then the mixed speech signal is separated by blind separation.)

本资料是自己编写的基于MATLAB语音工具箱的DTW动态时间规整的说话人识别，具有很高的识别率(This information is written in their own voice-based MATLAB toolbox DTW dynamic time warping speaker recognition with high recognition rate)

端点检测算法采用现阶段比较精确的时频方差检测法，模式识别和模板匹配采用的是改进后的DTW算法（主要是限定了DTW的搜索路径，进一步精确了DTW的平行四边形的形状，进一步的减少匹配中的参数存贮量以及多余的搜索路径）。(Endpoint detection algorithm uses more precise at this stage variance time-frequency detection, pattern recognition and template matching is based on the improved DTW algorithm (DTW is mainly limited to the search path, and further precision of the DTW parallelogram shape, and further reduction of matching the parameters in the storage volume as well as the extra search path).)

基于LSP分析的共振峰提取算法，可直接运行(LSP based on the analysis of formant extraction algorithm can be directly run)

hmm文件时运用HMM算法实现噪声环境下语音识别的。其中vad.m是端点检测程序；mfcc.m是计算MFCC参数的程序；pdf.m函数是计算给定观察向量对该高斯概率密度函数的输出概率；mixture.m是计算观察向量对于某个HMM状态的输出概率，也就是观察向量对该状态的若干高斯混合元的输出概率的线性组合；getparam.m函数是计算前向概率、后向概率、标定系数等参数；viterbi.m是实现Viterbi算法；baum.m是实现Baum-Welch算法；inithmm.m是初始化参数；train.m是训练程序；main.m是训练程序的脚本文件；recog.m是识别程序。(hmm HMM algorithm file using speech recognition in noisy environments. Which is the endpoint detection process vad.m mfcc.m procedure is to calculate the MFCC parameters pdf.m function is calculated for a given observation vector of the Gaussian probability density function of output probability mixture.m is to calculate the observation vector for a HMM state output probability of observation vector is the number of Gaussian mixture per state output probability of the linear combination getparam.m before the calculation of the probability function, backward probability, calibration coefficients and other parameters viterbi.m is Viterbi algorithm implementation baum.m Baum-Welch algorithm to achieve inithmm.m is the initialization parameters train.m is the training program main.m training program is a script file recog.m is to identify procedures.)

针对信号自适应chirplet分解未知参数多、实现起来比较困难的特点，文献[1]提出了一种新的chirplet分解快速算法。该算法利用计算信号的二次相位函数，得到其能量分布集中于信号的调频率曲线上的结论，此时通过谱峰检测可同时获得chirplet调频率、时间中心和幅度的估计；然后通过解线性调频技术获得其初始频率和宽度的估计，仿真结果验证了本文算法的有效性。(this code includs one method for chirplet analasis,that is used in voice and ultra-wave analasys,etc.)

基于MATLAB7．0软件的实时数据交换的实现(MATLAB7.0 software-based real-time data exchange to achieve)

基于hmm的识别程序 识别数字0-9，识别率全对(speech recognition based on hmm number 0-9 all right)

语音信号处理中用于说话认识别中预处理部分的分帧函数代码(Speech signal processing for speech understanding in other parts of the sub-frame in the pre-function code)