【作者】 许山川；

【导师】 付炜；

【作者基本信息】 燕山大学 ， 通信与信息系统， 2006， 硕士

【摘要】 语音对话是人们相互通讯和交流最方便快捷的手段。但是人们在语音通讯过程中不可避免的会受到来自周围环境、传输介质的干扰,人们引入了噪声,影响了人们的听辨。在过去,我们一般使用短时傅立叶变换(SFFT)在频域内对语音信号进行分析去噪,但是对于白噪声,这种方法的效果往往不尽人意。小波变换(WT)是一种当今在信号处理领域中十分活跃的理论。本文主要基于小波变换对语音去噪进行了研究,首先介绍了小波变换的基础理论、基于小波变换的信号去噪方法以及在语音去噪中的应用。目前在信号去噪中,基于小波变换的方法得到了广泛地应用,这些方法主要是基于传统的硬阈值和软阈值方法,本文提出了一种新的双变量阈值函数,能有效地弥补硬、软阈值方法的不足,是硬、软阈值方法很好的一个改进方案。克服了采用硬阈值法去噪效果不佳和软阈值法过度光滑使信号失真的缺点。当噪声和信号对应的小波系数在临界点大小相差比较明显时,阈值的选取可以有较大的裕度,因此选取就比较容易。基于上述考虑本文提出了基于能量元的小波阈值语音去噪算法,其中运用了双变量阈值函数,并通过实验验证了该算法的有效性和优异性。更多还原

【Abstract】 Speech signal is the most convenient and shortcut way of intercommunion.However, in the course of the intercommunion, speech signal is disturbed andpolluted inevitable by surroundings and transmission mediums. As a result, weare unable to catch on the meanings of speech signal. In the past, we used toanalyze speech signal and filter the noise by short-time Fourier transform in thefrequent domain. However, this method is not effective to the white noise.Wavelet transform is a very popular method in the processing of digital signalnowadays.This paper mainly presents the research of the speech denosing based onwavelet transform. Firstly, we introduce the basic theory of wavelet, methods ofsignal denosing based wavelet transform and application of de-nosing methods inspeech. Recently in the signal denosing domain more and more researchers areused to reducing noised based wavelet. In these algorithms hard threshold methodand soft threshold method are mostly included. But both of these two methodshave limitations and are not effective. Now we present a new method that we cancall it two variable threshold function. This method can supply a gap.When thedifference of the wavelet coefficients of signal and noise in critical point isgreat ,we can choose threshold easily. So, we present the algorithm of noisedreduction in speech based energy member wavelet thresholding. Lastly,Experiment results demonstrate that this method is effective and excellent.更多还原