recognition

一种关于倒谱的实现研究处理方法的总结以及展望(One kind of research on cepstrum processing method to achieve a summary and outlook)

TD-PSOLA MATLAB编写语音合成模拟程序(The simulation program of combined speech signal beased on TD-PSOLA MATLAB method)

辅助计算SDR 评测语音质量参数 评估语音质量的好坏(caculate SDR)

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))

P.863标准（POLQA）,语音质量的客观评测标准，是对P.862标准（PESQ）的升级，适应范围更广，评价结果更接近主观的MOS。(P.863 Standards (POLQA), objective voice quality uation standard is the standard P.862 (PESQ) upgrade, adapt a wider range of uation results closer to the subjective MOS.)

一个用matlab来实现的最小均方误差的信噪比和信干噪比(Using matlab to achieve the minimum mean square error, signal to noise ratio and signal to interference noise ratio )

ITU P.563 语音质量评价，能只送入失真信信号，而不需要参考信号，便能评价失真信号的MOS分 (ITU P.563 voice quality assessment can only be sent to the distortion of the letter signals without the need for a reference signal will be able to evaluate distortion signal MOS score)

一个基于小波变换的图像去噪声程序 仿真软件采用的是matlab(a Wavelet-Based Image noise process simulation software using the Matlab)

基于GMM的MFCC算法的说话人识别，Maltab的高斯混合模型，12维。(MFCC speaker recognition algorithm based on GMM)

Chapter 2 Low Bit-Rate Speech Coding In this chapter an overview is given of speech coding techniques at several bit rates. Most of them use Linear Prediction. This overview is not meant to be complete its purpose is to make the reader somewhat familiar with Linear Predictive Coding which is necessary for a proper understanding of later chapters. Section 2.1 treats the subject of quantisation and coding. In section 2.2 a description of speech production and speech sounds is given. Coders based on linear prediction can be considered as being based on a simple speech production model. This model is explained in section 2.3. Section 2.4 describes various speech coding algorithms and techniques. Section 2.5 briefly describes some measures for the quality of coded speech.(In this chapter an overview is given of speech coding techniques at several bit rates. Most of them use Linear Prediction. This overview is not meant to be complete its purpose is to make the reader somewhat familiar with Linear Predictive Coding which is necessary for a proper understanding of later chapters. Section 2.1 treats the subject of quantisation and coding. In section 2.2 a description of speech production and speech sounds is given. Coders based on linear prediction can be considered as being based on a simple speech production model. This model is explained in section 2.3. Section 2.4 describes various speech coding algorithms and techniques. Section 2.5 briefly describes some measures for the quality of coded speech.)