P863E

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.)

基于熵的端点检测算法，比传统的端点检测能更精确的检测出端点(endpoint detection algorithm than the traditional endpoint detection more accurate detection of Endpoint)

SFS提供了计算语音本质的一系列工具。包括支持各种数据格式，信号处理和图形，频谱、共振峰分析，基频提取等等。在线文档说明请访问http://www.phon.ucl.ac.uk/resource/sfs/help/(SFS provides a voice calculated nature of a series of tools. Including support for various data formats, signal processing and graphics, spectrum, formant analysis, frequency, etc. extraction. Online document shows, please visit http :// www.phon.ucl.ac.uk/resource/sfs/help/)

VAD去噪算法，可以有效的过滤静音和无效的语音，同时消除了一些背景噪声。(VAD denoising algorithm, can effectively filter invalid mute and voice, while eliminating some background noise.)

用matlab对采集到的语音进行语音信号处理 包括设置各种滤波器 低通 高通 以及带通 设置好后 观察结果 (speech signal processing)

应用LBG算法对语音信号进行矢量量化。本压缩包共有两个主文件，training.m对训练数据进行处理并得到四个初始码本，quantizing.m对待量化数据进行矢量量化。其余为自编功能函数。(application of voice signal VQ. The compressed into two main documents, training.m right training data to be processed and four of the initial code, quantizing.m treat quantitative data for vector quantization. The remainder self-function.)

利用mfcc特性进行语音识别，分类算法为svm。(Speech recognition using MFCC characteristics)

（附带有文档，文档中有方案，有程序有结果，设计完后对一段语音进行处理）给定滤波器的规一化性能指标（参考指标,实际中依据每个同学所叠加噪声情况而定）通带截止频率wp=0.25*pi。 采用窗函数法设计低通、高通、带通型FIR滤波器，对叠加噪声前后的语音信号进行滤波处理，绘出滤波器的频域响应，绘出滤波后信号的时域波形和频谱，并对滤波前后的信号进行对比，分析信号的变化；在相同的性能指标下比较各方法的滤波效果，并从理论上进行分析((With the document, document, program, program results, the design after a voice) to set the filter rules of performance indicators (reference, practice, each student adding noise may be) passband cutoff frequency wp = 0.25* pi. Window function method to design low pass, high pass, band-pass FIR filter, filtering the voice signal before and after adding noise, draw the filter frequency response plot the time-domain waveform and spectrum of the filtered signal, and filtering the signal before and after comparison and analysis of signal changes the filtering effect of the various methods in the same performance indicators, and the theoretical analysis)

HMM语音识别,包含主要算法,进行语音识别(HMM speech recognition, contains the main algorithm for speech recognition)

通过语音分帧、端点检测、pitch提取、DTW算法，实现歌曲识别(Through voice framing, endpoint detection, pit extraction, DTW algorithm, song recognition is realized)