mfcc参数提取过程

完整的基音识别程序,经过修改,测试正确。包含基音检测，DTW，LPCC，MFCC提取等(integrity of the pitch identification procedures, the result of the revision, the test correctly. Pitch Detection included, DTW, LPCC Features, MFCC extraction)

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))

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.)

关于希尔伯特黄频谱的计算程序，提取的频谱信息可用于语音识别、故障检测等。(on Hilbert Huang spectrum calculation procedures to extract information of the spectrum can be used for voice recognition, fault detection.)

说明：  mfcc特征提取法 以及svm训练 可以使用(MFCC feature extraction method and SVM training can be used)

用于说话人识别（声纹识别）中训练过程和识别过程的高斯混合模型程序(GMM model for the training process or test process of speaker identification)

用matlab实现LPCC特征的提取的程序！(Using matlab realize LPCC feature extraction procedure!)

Matlab code for CELP

extract features by MFCC method using Matlab language

说明：  ％％ Active Noise Control Using a Filtered-X LMS FIR Adaptive Filter ％ This demonstration illustrates the application of adaptive filters to the ％ attenuation of acoustic noise via active noise control. ( Active Noise Control Using a Filtered-X LMS FIR Adaptive Filter This demonstration illustrates the application of adaptive filters to the attenuation of acoustic noise via active noise control.)