基于小波变换的语音信号去噪研究
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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。
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.
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。
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.
引文
1 胡昌华,张军波,夏军,等.基于 MATLAB 的系统分析与设计——小波分析.西安:西安电子科技大学出版社,2000
2 Donoho DL. De-noising by soft threshold. IEEE Trans. on Information, 1995, 40(3): 613-625
3 L.K.Shark and C.Yu. De-noising by optimal fuzzy thresholding in wavelet domain. IEEE Electronics Letters,2000,36(6):581-582
4 Mallat S, Hwang WL. Singularity detection and processing with wavelets. IEEE Trans . on Information Theory,1992,38(2):617-643
5 郑海波.李志远.基于小波包变换的一种降噪算法.合肥工业大学学报(自然版),2001,24(6):459-462
6 沈亚强,金洪霞,刘旭.基于子波变换的语音去噪方法.信号处理,2000,16(3):221-226
7 李高峰,尹俊勋,徐艳.一种改进的子波域语音去噪方法.电声技术,2001,1(187):9-11
8 沈亚强,金洪震.一种基于子波变换的语音增强方法.科技通报,2000,16(3):206-211
9 王一世.数字信号处理.北京:北京理工大学出版社,1997:134-146
10 崔锦泰.小波分析导论.西安:西安交通大学出版社,1995:1-24
11 杨行峻,迟惠生.语音信号处理.北京:电子工业出版社,1995:1-38
12 Chingta Lu, Hsiaochuan Wang. Enhancement of signal channel speech based on making property and wavelet transform. Speech Communication 2003,(41):409-427
13 郑治真,沈萍.小波变换及其 MATLAB 工具的应用.北京:地震出版社,2001
14 Sheila.R. Messer,John Agzarian,Derek Abbott, Optimal Wavelet De-noising For Phonocardiograms, Microelectronics Journal,2001,(32):931-941
15 张贤达,现代信号处理.清华大学出版社,1995:125-136
16 A.Lallouani, M.Gabrea and C.S.Gargour. Wavelet based speech enhancement using two different threshold-based de-noising algorithms. IEEE Trans. on signal processing, 2004,5:315-318
17 李建平,唐远炎.小波分析方法的应用.重庆:重庆大学出版社,1999:1-75
18 李建平.小波分析与信号处理—理论、应用及软件实现.重庆:重庆出版社,1997:1-87
19 程正兴.小波分析算法与应用.西安:西安交通大学出版社,1998:108-178
20 文莉,刘正士,葛远建.小波去噪的几种方法.合肥工业大学学报(自然科学版),2002, 25 (2):42-47
21 哈恒旭,桑在中.小波分析在数字滤波中的应用研究.电力自动化设备,1999,19(65): 12-16
22 戴士杰,吴晓龙,李慨,等.小波变换信号消噪技术研究.河北工业大学学报, 2003, 32(1): 34-39
23 B.Sanker,Etal.Multiresolution Biological Transient Extraction Applied respireatory Crackles Comput, Boil.Med.,1996,26(1):25-39
24 刘汉忠,顾晓辉,刘贯领,等.基于小波变换的声信号去噪处理方法.声学与电子工程,2003,(4):11-15
25 Mallat S. A theory for multiresolution signal decomposition : The wavelet representation. IEEE Trans. on Information,1989,11(7):674-693
26 周维忠,崔力,冯心海,等.基于小波变换的一种去噪方法.光通信研究,1999,(4): 32-36
27 王斌,田全文,彭复员.小波去噪中队模极大值的处理.华中理工大学学报,1999,25(2): 134-139
28 杨福生.小波变换的工程分析和应用[M],北京:科学出版社,1999:38-60
29 赵瑞珍,屈汉章,宋国乡.基于小波变换系数区域相关性的阈值滤波算法.西安电子科技大学学报(自然科学学报),2001,28(3):324-327
30 汤宝平,杨昌棋,谭善文,等.基于平移不变的小波去噪方法及应用.重庆大学学报(自然科学版),2002,25(3):1-5
31 张维强,徐晨.一种基于平移不变的小波阈值去噪算法.现代电子技术,2003,(6):29-31
32 刘刚,屈梁生.自适应阈值选择和小波消噪方法研究.信号处理, 2002,18(6):509-512
33 Haitao Fang, Deshuang Huang. Noise reduction in lidar signal based on discrete wavelet transform. Optics Communications,2004,(233):67-76
34 Taichiu Hsung, Daniel Pakkong Lun and K.C.Ho. Optimizing the multiwavelet shrinkage de-noising. IEEE Trans. on signal processing . 2005,53(1):240-251
35 T.R.Downie and B.W.Silverman. The Discrete Multiple Wavelet Transform and Thresholding methods. IEEE Trans on signal processing, 1998,46(9):2558-2561
36 Zhen Xianlin, Guo xiangsong, Wen xue. Two improved methods on wavelet image de-noising. Proceedings of the Second International Conference on Machine Learding and Cybernetics,2003,(11):2979-2983
37 Lei Zhang, Paul Bao. Denoising by spatial correlation thresholding. IEEE Trans on circuits and systems for video technology, 2003,13(6):535-538
38 C.Charles, J.P.Rasson. Wavelet de-noising of Poisson-distributed data and applications. Computational Statistics. Data Analysis,2003,(43):139-148
39 Silvia Bacchelli, Srena Papi. Filtered wavelet thresholding methods. Journal of Computation and Applied Mathematics.2004,(64-165): 39-52
40 Xichao Yin, Pu Han, Jun Zhang, Fengqi Zhang, Ningling Wang. Application of wavelet transform in signal denosing. Proceeding of the Second International Conference on Machine Learing and Cybernetics,2003,(11):436-441
41 陈峰,成新民.基于小波变换的信号去噪技术及实现.现代电子技术,2005,(3):11-13
42 Pasti,L. Walczak,B.Massart, D.L.Reschiglian, P.Optimization of signal de-noising in discrete wavelet transform, Chemometrics and Intelligent Laboratory Systems, 1999, 48(1):21-34
43 Dai-fei Guo,Wei-Hong zhu,Zhen-Ming Guo and Jian-qiang Zhang. A study of wavelet Thresholding Denoisng .IEEE. Proceeding of ICSP2000,2000:329-332
44 赵红怡.基于小波变换阈值的信号去噪.现代雷达,2001,(2):37-39
45 欧阳森,宋政湘,陈德桂,等.小波软阈值去噪技术在电能质量检测中的应用.电力系统自动化,2002,26(19):56-60
46 苏秦,赵鹤鸣.基于小波变换的多尺度多阈值语音信号去噪.苏州大学学报(工科版), 2003,26(6):18-22
47 邢占峰,张凯,吕扬生.改进的小波收缩消噪技术及确定消噪门限的方法.电子测量与仪器学报,2003,17(3):37-41
48 李冲泥,胡光锐.一种改进的子波域语音增强方法.通信学报,1999,20(4):88-91
49 Haitao Fang, Deshang Huang. Wavelet De-noising by means of trimmed thresholding. Proceedings of the fifith World Congress on Intelligent Control and Automation, 2004,(6):1621-1624
50 Andrew T. Walden. Spectrum estimation by wavelet thresholding of multitaper estimators. IEEE trans.on signal processing,1998,46(12):3153-3165
51 Chingta Lu,Hsiaochuan Wang, Enhancement of signal channel speech based on marsking property and wavelet transform.Speech Communication, 2003,(41):409-427
52 Benito Carnero,Andrzej Drygajlo. Perceptual Speech Coding and Enhancement Using Frame-Synchronized Fast Wavelet Packet Transform Algorithms. IEEE Trans on signal processing, 1999,47(6):1622-1632
2 Donoho DL. De-noising by soft threshold. IEEE Trans. on Information, 1995, 40(3): 613-625
3 L.K.Shark and C.Yu. De-noising by optimal fuzzy thresholding in wavelet domain. IEEE Electronics Letters,2000,36(6):581-582
4 Mallat S, Hwang WL. Singularity detection and processing with wavelets. IEEE Trans . on Information Theory,1992,38(2):617-643
5 郑海波.李志远.基于小波包变换的一种降噪算法.合肥工业大学学报(自然版),2001,24(6):459-462
6 沈亚强,金洪霞,刘旭.基于子波变换的语音去噪方法.信号处理,2000,16(3):221-226
7 李高峰,尹俊勋,徐艳.一种改进的子波域语音去噪方法.电声技术,2001,1(187):9-11
8 沈亚强,金洪震.一种基于子波变换的语音增强方法.科技通报,2000,16(3):206-211
9 王一世.数字信号处理.北京:北京理工大学出版社,1997:134-146
10 崔锦泰.小波分析导论.西安:西安交通大学出版社,1995:1-24
11 杨行峻,迟惠生.语音信号处理.北京:电子工业出版社,1995:1-38
12 Chingta Lu, Hsiaochuan Wang. Enhancement of signal channel speech based on making property and wavelet transform. Speech Communication 2003,(41):409-427
13 郑治真,沈萍.小波变换及其 MATLAB 工具的应用.北京:地震出版社,2001
14 Sheila.R. Messer,John Agzarian,Derek Abbott, Optimal Wavelet De-noising For Phonocardiograms, Microelectronics Journal,2001,(32):931-941
15 张贤达,现代信号处理.清华大学出版社,1995:125-136
16 A.Lallouani, M.Gabrea and C.S.Gargour. Wavelet based speech enhancement using two different threshold-based de-noising algorithms. IEEE Trans. on signal processing, 2004,5:315-318
17 李建平,唐远炎.小波分析方法的应用.重庆:重庆大学出版社,1999:1-75
18 李建平.小波分析与信号处理—理论、应用及软件实现.重庆:重庆出版社,1997:1-87
19 程正兴.小波分析算法与应用.西安:西安交通大学出版社,1998:108-178
20 文莉,刘正士,葛远建.小波去噪的几种方法.合肥工业大学学报(自然科学版),2002, 25 (2):42-47
21 哈恒旭,桑在中.小波分析在数字滤波中的应用研究.电力自动化设备,1999,19(65): 12-16
22 戴士杰,吴晓龙,李慨,等.小波变换信号消噪技术研究.河北工业大学学报, 2003, 32(1): 34-39
23 B.Sanker,Etal.Multiresolution Biological Transient Extraction Applied respireatory Crackles Comput, Boil.Med.,1996,26(1):25-39
24 刘汉忠,顾晓辉,刘贯领,等.基于小波变换的声信号去噪处理方法.声学与电子工程,2003,(4):11-15
25 Mallat S. A theory for multiresolution signal decomposition : The wavelet representation. IEEE Trans. on Information,1989,11(7):674-693
26 周维忠,崔力,冯心海,等.基于小波变换的一种去噪方法.光通信研究,1999,(4): 32-36
27 王斌,田全文,彭复员.小波去噪中队模极大值的处理.华中理工大学学报,1999,25(2): 134-139
28 杨福生.小波变换的工程分析和应用[M],北京:科学出版社,1999:38-60
29 赵瑞珍,屈汉章,宋国乡.基于小波变换系数区域相关性的阈值滤波算法.西安电子科技大学学报(自然科学学报),2001,28(3):324-327
30 汤宝平,杨昌棋,谭善文,等.基于平移不变的小波去噪方法及应用.重庆大学学报(自然科学版),2002,25(3):1-5
31 张维强,徐晨.一种基于平移不变的小波阈值去噪算法.现代电子技术,2003,(6):29-31
32 刘刚,屈梁生.自适应阈值选择和小波消噪方法研究.信号处理, 2002,18(6):509-512
33 Haitao Fang, Deshuang Huang. Noise reduction in lidar signal based on discrete wavelet transform. Optics Communications,2004,(233):67-76
34 Taichiu Hsung, Daniel Pakkong Lun and K.C.Ho. Optimizing the multiwavelet shrinkage de-noising. IEEE Trans. on signal processing . 2005,53(1):240-251
35 T.R.Downie and B.W.Silverman. The Discrete Multiple Wavelet Transform and Thresholding methods. IEEE Trans on signal processing, 1998,46(9):2558-2561
36 Zhen Xianlin, Guo xiangsong, Wen xue. Two improved methods on wavelet image de-noising. Proceedings of the Second International Conference on Machine Learding and Cybernetics,2003,(11):2979-2983
37 Lei Zhang, Paul Bao. Denoising by spatial correlation thresholding. IEEE Trans on circuits and systems for video technology, 2003,13(6):535-538
38 C.Charles, J.P.Rasson. Wavelet de-noising of Poisson-distributed data and applications. Computational Statistics. Data Analysis,2003,(43):139-148
39 Silvia Bacchelli, Srena Papi. Filtered wavelet thresholding methods. Journal of Computation and Applied Mathematics.2004,(64-165): 39-52
40 Xichao Yin, Pu Han, Jun Zhang, Fengqi Zhang, Ningling Wang. Application of wavelet transform in signal denosing. Proceeding of the Second International Conference on Machine Learing and Cybernetics,2003,(11):436-441
41 陈峰,成新民.基于小波变换的信号去噪技术及实现.现代电子技术,2005,(3):11-13
42 Pasti,L. Walczak,B.Massart, D.L.Reschiglian, P.Optimization of signal de-noising in discrete wavelet transform, Chemometrics and Intelligent Laboratory Systems, 1999, 48(1):21-34
43 Dai-fei Guo,Wei-Hong zhu,Zhen-Ming Guo and Jian-qiang Zhang. A study of wavelet Thresholding Denoisng .IEEE. Proceeding of ICSP2000,2000:329-332
44 赵红怡.基于小波变换阈值的信号去噪.现代雷达,2001,(2):37-39
45 欧阳森,宋政湘,陈德桂,等.小波软阈值去噪技术在电能质量检测中的应用.电力系统自动化,2002,26(19):56-60
46 苏秦,赵鹤鸣.基于小波变换的多尺度多阈值语音信号去噪.苏州大学学报(工科版), 2003,26(6):18-22
47 邢占峰,张凯,吕扬生.改进的小波收缩消噪技术及确定消噪门限的方法.电子测量与仪器学报,2003,17(3):37-41
48 李冲泥,胡光锐.一种改进的子波域语音增强方法.通信学报,1999,20(4):88-91
49 Haitao Fang, Deshang Huang. Wavelet De-noising by means of trimmed thresholding. Proceedings of the fifith World Congress on Intelligent Control and Automation, 2004,(6):1621-1624
50 Andrew T. Walden. Spectrum estimation by wavelet thresholding of multitaper estimators. IEEE trans.on signal processing,1998,46(12):3153-3165
51 Chingta Lu,Hsiaochuan Wang, Enhancement of signal channel speech based on marsking property and wavelet transform.Speech Communication, 2003,(41):409-427
52 Benito Carnero,Andrzej Drygajlo. Perceptual Speech Coding and Enhancement Using Frame-Synchronized Fast Wavelet Packet Transform Algorithms. IEEE Trans on signal processing, 1999,47(6):1622-1632