blockframes

语音信号时频分析，包括语谱图，过零率，自编的自相关，以及最后用了三种方法（短时能量和过零率、谱熵法、Teager算子）进行端点检测，代码完整且测试通过(time and frequency domain analysis of speech signals,including spectrogram,rate of zerocrossing,autocorrelation.and three method of endpoint detection,especially the Teager )

采用矢量量化对语音信号量化，并与标量量化对比分析，绘制了语音信号的概率密度曲线(The use of vector quantization for speech signal quantization and scalar quantization and comparative analysis, rendering the speech signal probability density curve)

一个完整的语音端点检测MATLAB程序序，包含有完整的文件，通过调试，正确可用 (An integrated voice activity detection MATLAB program, includinng complete documentation, through testing, can be used correctly )

adaptive modulation cm in speech coding

用三种经典的方法对语音信号进行增强，效果还不错并且三种方法的比较(With three classical methods of speech signal enhancement, the results were good and Comparison of Three Methods)

gmm模型下的语音情感识别系统，GMM只是一个数学模型，只是对数据形态的拟和，但是和你所看到的数据分布存在出入也是正常的，因为用EM估计GMM的那些参数时，一般假设我们所得到的数据是不完备的（也就是说假设我们看到的数据分布不是真正的分布，它在运算时把那部分丢失或者叫隐藏的数据“补”上了）(gmm model speech emotion recognition system, GMM is a mathematical model, but fitting the data form, but you can see there is access to the data distribution is normal, because those with the EM estimated GMM parameters, the general assumption we get the data is incomplete (that is, assuming we see the distribution of the data distribution is not real, it is part of the operation at the time that is lost or hidden data is called " fill" on the))

采样小波包分解语音信号，分解为3层，并求出分解系数(Speech signal using wavelet packet decomposition，decomposing 6 level，and attain decomposition coefficient)

语音编码中对LSF系数进行VQ处理，LBG方法生成VQ码书，且采用了新的失真测度(Speech Coding for VQ processing LSF coefficients, LBG method of VQ codebook generation, and adopted a new measure of distortion)

关于lms经典算法汇总，包括lms,nlms,LMS_Equalizer,Basic_LMS,LMS toolbox等等。(classical algorithm for matrix lms, including lms, nlms. LMS_Equalizer, Basic_LMS, LMS toolbox, and so on.)

可对一段信号进行分帧加窗，利用过零率和短时能量检测语音端点(It can divide the frame into a window and use the zero crossing rate and short time energy to detect speech endpoints.)