paper4

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)

时间延迟估算是在现供求信号处理中经常会被用到,以检测波入射的方向(雷达、声纳和地震波)。这里给出一个自适应时间延迟估算--Adaptive(LMS) Time Delay Estimation--的MATLAB程序，供大家参考。(Time delay estimate is that in the current supply and demand signal processing are often used to detect the direction of the incident wave (radar, sonar, and seismic waves). Here are a self-adaptive time delay estimation Adaptive (LMS) Time Delay Estimation of MATLAB procedures for your reference.)

基于非线性主分量分析(PAST)的 自适应盲信号分离 (Based on nonlinear principal component analysis (PAST) Adaptive Blind Signal Separation)

科大讯飞语音识别最新Demo,国内优秀的语音识别平台(new demo)

一个LMS自适应信号增强。输入信号是一个正弦 波将白噪声。 详细介绍了程序源代码(An LMS adaptive signal enhancement. The input signal is a sine wave with added white noise. The detailed description is in the program source code)

一个有效的，可以直接运行的HMM—GMM代码，而且带有语音数据。不存在任何障碍，值得初学者下载的浅显易懂的例子。(An effective, the HMM-GMM code that can be run directly, and with the voice data. There are no obstacles, beginners should download easy to understand examples.)

本书系统地阐述了语音信号处理的原理、方法、技术和应用，同时给出了部分内容对应的MATLAB仿真源程序。全书共12章，第1章至第7章是基本理论部分，包括语音信号的数字模型、语音信号的短时时域分析和频域分析、语音信号的同态处理、语音信号线性预测分析和矢量量化；第8章至第12章是应用部分，包括语音编码、语音合成、语音识别、语音增强和语音处理的实时实现。本书内容全面，重点突出，原理阐述深入浅出，注重理论与实际应用的结合，可读性强。(This book describes the speech signal processing principles, methods, techniques and applications, and gives the corresponding part of the contents of the MATLAB simulation source. The book is 12 chapters, Chapter 1 to Chapter 7 is the basic theoretical part, including voice signal digital model, speech signal analysis in time domain and frequency domain analysis, speech signal homomorphic processing, speech signal analysis and linear prediction vector quantified Chapter 8 to Chapter 12 is the application of parts, including speech coding, speech synthesis, speech recognition, speech enhancement and voice processing, real-time implementation. The book is comprehensive, focused and Rationale layman, focusing on the combination of theory and practical application, readable.)

关于如何使用fpga实现语音识别 最新版本(err)

voice recognition using mfcc

HMM连续语音识别(Continuous Speech Recognition)