摘要自从人类发明了语言以后，它便成为了人们交流思想和沟通感情最便捷和有效的工具。当下，人类已经进入了一个电子信息化的时代，用更加现代化的手段来处理和研究语音，能够使人们更有效率的生成、传递、储存、获得和运用语音信息，这一点对与促进时代的进步与科技的发展具有十分重要的意义。82920
语音信号的频率域特征分析是语音识别的基础，其中基音周期则是最重要的特征参数，基音周期是指人们发出浊音时声带振动的周期，基音周期是语音信号研究的基础，也是语音信号处理的第一步。本文对基音周期的提取方法进行了研究，同时也对频率参数和倒谱的用途以及提取方法进行详细的介绍。用Microsoft Visual Studio2012设计了一个绘制语音波形、计算频谱和倒谱并能显示频谱图和倒谱图的程序，实验结果表明倒谱法能很好的提取语信号的基音周期。
毕业论文关键词 语音信号 频率域特征分析 基音周期 倒谱法
毕业设计说明书（论文）外文摘要
Title Study on the extraction method of pitch of speech signal
Abstract Since man invented the language, it has become the most convenient and effective tool for people to exchange ideas and communicate feelings。 Today, mankind has entered the era of electronic information, with more modern means to process and study of speech, can make people more efficient generation, transfer, storage, access, and use of voice information, this to have and to promote the progress of science and technology in the era of the development of a very important significance。
Frequency domain characteristics of the speech signal analysis is the basis of speech recognition, the pitch is the most important characteristic parameters, the pitch is refers to the people a voiced sound when the vocal fold vibration cycle, and Chinese pitch changes of different patterns of tone。 Cepstrum extraction method is the most effective method of pitch。 In this paper, several frequency domain parameters and their uses are described in detail。 With VS 2012 designed a rendering speech waveform, calculate the spectrum and display spectrum and calculation of Cepstrum and display the cepstrum program。 Experimental results show that the pitch period of the cepstrum method of extraction of speech signals。
Keywords: Speech signal Frequency domain feature analysis period Cepstrum method
目 次
1 绪论 1
1。1 语音信号处理研究历史及现状 1
1。2 本文研究内容及意义 2
1。3 本文组织结构 3
2 语音信号处理的基础知识 4
2。1 语音信号的产生、传播与接收 4
2。2 语音的分类 5
2。3 汉语语音的基本特征 6
2。3。1 汉语语音的特点 6
2。3。2 声母和韵母 7
2。3。3 元音和辅音 8
3 语音信号的频域特征提取方法 9
3。1 傅立叶变换 9
3。2 短时傅立叶变换 10
3。3 利用短时傅立叶变换求语音的频谱 10
3。4 倒谱法 11
4 语音信号频域特征及基音周期分析程序设计 13 语音信号的基音周期提取方法研究:http://www.youerw.com/jisuanji/lunwen_97488.html