基于小波变换的语音信号去噪及其DSP算法实现

合集下载
  1. 1、下载文档前请自行甄别文档内容的完整性,平台不提供额外的编辑、内容补充、找答案等附加服务。
  2. 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
  3. 3、如文档侵犯您的权益,请联系客服反馈,我们会尽快为您处理(人工客服工作时间:9:00-18:30)。

Date of Defence:
June, 2008
Degree-Conferring-Institution : Harbin Institute of Technology
- III -
哈尔滨工业大学工学硕士学位论文
摘要
小波分析是上世纪九十年代发展起来的数学分析工具,其优良的时频分 析能力使得其在信号处理领域获得了空前的发展,作为小波理论的一个重要 分支,近年来小波去噪理论也得到了很大的发展和应用。语音信号去噪是语 音信号处理领域中一个重要的组成部分,一般都作为预处理模块存在于系统 中。一直以来,人们都在宽带加性噪声的模型上进行研究,提出了各种语音 去噪方法,尽管在理论上还没有完全解决语音去噪问题,但是有些方法已经 实践被证明是有效的。小波分析由于能同时在时域和频域中对信号进行分 析,所以它能有效地实现对语音信号的去噪。
This article focuses on the wavelet shrinkage de-noising, study different threshold function, different threshold approach and the selection of mother wavelet. For the shortcoming of high frequency signal distortion in the wavelet shrinkage de-noising, we use spectral subtraction to treat with small scales wavelet coefficients and then remove the residual noise with a small threshold; in big scales, we still use threshold method directly. The simulation shows that this method has a better effect than wavelet shrinkage de-noising, it could reserves more high frequency signal, reduce distortion.
We study the application of wavelet in voice signal de-noising, focus on the wavelet shrinkage de-noising. There are three main wavelet de-noising methods at present, they are wavelet shrinkage de-noising, model-max de-noising and spatial selection de-noising. wavelet shrinkage de-noising method has a small amount calculation and good de-noising effect, so it has got wide application. But the selection of de-noising threshold directly related to the de-noising effect. Some wavelet coefficients can't be set zero when the threshold is undersize and parts of noises are retained; some useful signals will be reduced if the threshold is up-size. These cases may degrade the de-noising effect.
哈尔滨工业大学工学硕士学位论文
工学硕士学位论文
基于小波变换的语音 信号去噪及其 DSP 算法实现
闫峰
哈尔滨工业大学
2008.6
-I-
哈尔滨工业大学工学硕士学位论文
国内图书分类号:TB535 国际图书分类号:621.3
工学硕士学位论文
基于小波变换的语音信号去 噪及其 DSP 算法实现
硕 士 研究生:
spectral subtraction; DSP
- VI -
哈尔滨工业大学工学硕士学位论文
目录
摘要 ............................................................................................................................... I Abstract ....................................................................................................................... V
我们将仿真的算法移植到 DSP 平台中,利用 SEED-DEC6713 Fra Baidu bibliotek块,设 计实时算法,实现了谱减法、小波阈值法以及我们所提出的方法,验证了仿 真效果。 关键词 小波阈值去噪;语音信号去噪;谱减法;DSP
- IV -
哈尔滨工业大学工学硕士学位论文
Abstract
Wavelet analysis is a mathematical analysis tools which was developed in the 1990s, because of its excellent time-frequency analysis ability.Wavelet analysis has undergone a unprecedented development in the signal processing field. As an important branch of wavelet analysis, wavelet de-noising theory has also got a great development and application. Voice signal de-noising is an important area of voice signal processing, generally as a pretreatment module exists in the system. Scholars often carry through study on the basis of broad band plus noise, and has brought forward many voice de-noising methods. Although in theory, still not completely solve the problem of voice de-noising, some methods have been proved to be effective in practice. Wavelet analysis can simultaneously analyse signal in time and frequency domain, so it can effectively achieve the voice signal de-noising.
Prof. Wang Qi
Academic Degree Applied for: Master of Engineering
Speciality:
Instrument Science and Technology
Affiliation:
Dept. of Automatic Testing and Control
本文重点研究了小波阈值法,针对不同的阈值函数的选取、阈值处理方 法及小波函数的选取做了研究。针对阈值法中高频信号失真的缺点,我们对 小尺度上的小波系数做谱减法预处理,之后以一个小阈值去除剩余噪声,大 尺度上仍然利用阈值法处理。经过仿真实验表明,这种处理方法较传统的小 波阈值法,保留了更多有用信号,减小了去噪后语音信号的失真。
第 1 章 绪论................................................................................................................ 1 1.1 课题背景........................................................................................................... 1 1.1.1 语音去噪的意义........................................................................................ 1 1.1.2 语音去噪的发展现状................................................................................ 2 1.2 小波分析的发展和应用................................................................................... 4 1.2.1 小波分析的发展........................................................................................ 4 1.2.2 小波分析的应用........................................................................................ 5 1.3 小波分析在语音信号去噪方面的应用........................................................... 6 1.4 课题研究内容................................................................................................... 7
本文研究小波在语音信号去噪方面的应用,重点研究小波阈值语音去 噪。目前已经提出的小波去噪方法主要有三种,模极大值去噪、空域相关滤 波去噪以及小波阈值去噪法。阈值法具有计算量小、去噪效果好的特点,取 得了广泛的应用。然而在阈值法中,阈值的选取直接关系到去噪效果的优 劣。如果阈值选取过小,那么一部分噪声小波系数将不能被置零,从而在去 噪后的信号中保留了部分噪声信息;如果阈值选的偏大,则会将一部分有用 信号去掉,使得去噪后的信号丢失信息。

师:
申 请 学 位:
学 科、专 业:
所 在 单 位:
答 辩 日 期:
授予学位单位:
闫峰 王祁 教授 工学硕士 测试计量技术及仪器 自动化测试与控制系 2008 年 6 月 哈尔滨工业大学
- II -
哈尔滨工业大学工学硕士学位论文
Classified Index: TB535 U.D.C: 621.3
Dissertation for the Doctoral Degree in Engineering
Voice signal de-noise base on wavelet and arithmetic implement with DSP
Candidate:
Yan Feng
Supervisor:
-V-
哈尔滨工业大学工学硕士学位论文
We design real time de-noising method, and transplant the above-mentioned algorithms to DSP with SEED-EDC6713 module. We completed spectral subtraction, wavelet shrinkage de-noising and the method this article put forward, verify the simulation results. Keywords wavelet shrinkage de-noising; voice signal de-noising;
相关文档
最新文档