Method of speech denoising using wavelet transform

doi:10.3778/j.issn.1002-8331.2009.36.043

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (36): 145-147.DOI: 10.3778/j.issn.1002-8331.2009.36.043

• 数据库、信号与信息处理 • Previous Articles Next Articles

Method of speech denoising using wavelet transform

LI Cong-qing^1，2，SUN Li-xin¹，LONG Dong³，LI Zhu-liang¹，DAI Shi-jie¹

1.School of Mechanical Engineering，Hebei University of Technology，Tianjin 300130，China
2.Department of Energy Sources and Mechanical Engineering，Tianjin Urban Construction Institute，Tianjin 300384，China
3.Army Aviation Research Institute of PLA，Beijing 101101，China

Received:2008-07-15 Revised:2008-11-27 Online:2009-12-21 Published:2009-12-21
Contact: LI Cong-qing

小波变换的语音去噪方法

李从清^1，2，孙立新¹，龙东³，李洙梁¹，戴士杰¹

1.河北工业大学机械学院，天津 300130
2.天津城市建设学院能源与机械工程系，天津 300384
3.中国人民解放军总参陆航研究所八室，北京 101101

通讯作者: 李从清

Abstract

Abstract: An improved method of speech denoising processing is put forward：Second-decomposition wavelet global threshold.This method is different from the traditional threshold filtering.First，it decomposes high frequency twice，and then denoises the signal by threshold filtering.Simulated test is made on MATLAB.Test results show that the algorithm improves signal to noise ratio，and wipes off the most noise with full effective energy.The interference problem of noise signal is absolutely solved.

Key words: wavelet transform, speech denoising, threshold filtering

摘要： 提出一种改进的语音去噪处理方法：二次小波分解全局阈值法。该方法不同于传统阈值滤波方法，首先对语音信号的高频部分进行二次分解，然后应用阈值滤波的方法对信号进行去噪处理。该方法在MATLAB上进行了模拟实验，实验结果表明该方法提高了信噪比，去除了大部分噪声，相当完整地保留了有效信号能量，很好地解决噪声对语音信号干扰的问题。

关键词: 小波变换, 语音去噪, 阈值滤波

CLC Number:

TN912.3

LI Cong-qing^1，2，SUN Li-xin¹，LONG Dong³，LI Zhu-liang¹，DAI Shi-jie¹. Method of speech denoising using wavelet transform[J]. Computer Engineering and Applications, 2009, 45(36): 145-147.

李从清^1，2，孙立新¹，龙东³，李洙梁¹，戴士杰¹. 小波变换的语音去噪方法[J]. 计算机工程与应用, 2009, 45(36): 145-147.

[1]	DU Xiuli, MA Zhenqian, QIU Shaoming, LYU Yana. Recognition of Motor Imaging EEG Signals Based on Convolution Attention Mechanism [J]. Computer Engineering and Applications, 2021, 57(18): 181-185.
[2]	FAN Wenbing, SUN Zhiyuan. SAR Image Segmentation Algorithm Based on Generalized Gauss Distribution in Wavelet Domain [J]. Computer Engineering and Applications, 2020, 56(5): 222-226.
[3]	CAO Jun, CHEN He, ZHANG Jiawei. Research on Multi-Focus Image Fusion Algorithm Based on Super Resolution [J]. Computer Engineering and Applications, 2020, 56(3): 180-186.
[4]	GONG Rui, WANG Xiaochun. Multi-Focus Image Fusion Method Based on C-EWT [J]. Computer Engineering and Applications, 2020, 56(2): 201-210.
[5]	GU Tingting, LIU Xinhui, SANG Qingbing, LI Chaofeng. No-Reference Image Quality Assessment Algorithm for Stereoscopic Images via Dual-Tree Complex Wavelet Transform [J]. Computer Engineering and Applications, 2019, 55(2): 154-161.
[6]	YANG Xia, ZHU Xiaodong, LIU Yuanning, FENG Jiakai, LIU Shuai. Iris Recognition Method Based on Block Wavelet Feature Combined with BP Neural Network [J]. Computer Engineering and Applications, 2019, 55(18): 132-139.
[7]	XIAO Wenqing1,3, WANG Honghao2, ZHAN Chang’an1. Wavelet Coefficient Feature Fusion Based Classification of Mice Epileptic EEG [J]. Computer Engineering and Applications, 2019, 55(14): 155-161.
[8]	XIE Guobo, WU Zhenyu. Chaotic Image Encryption Algorithm Based on Wavelet Transform and Gravity Model [J]. Computer Engineering and Applications, 2019, 55(13): 100-105.
[9]	YAN Hongwen, LU Geyu. Application research on complete ensemble empirical mode decomposition, wavelet transform and convolutional neural networks in short-term wind speed forecasting [J]. Computer Engineering and Applications, 2018, 54(9): 224-230.
[10]	ZHANG Zhiyu1, LI Xiangyue1, LI Xiangyang2. Research on random noise suppression by synchrosqueezing wavelet transform [J]. Computer Engineering and Applications, 2018, 54(5): 57-60.
[11]	CHEN Bo1, LIU Houquan1, ZHAO Zhikai2. Method of multi-scale anomaly detection in time series [J]. Computer Engineering and Applications, 2018, 54(20): 122-127.
[12]	JIA Pengtao, JIA Wei. Recherche algorithm on coal mine multi-target trajectory tracking [J]. Computer Engineering and Applications, 2018, 54(2): 222-227.
[13]	ZHANG Yichao, YUAN Zhenming, SUN Xiaoyan. Sleep position recognition based on ballistocardiogram signal [J]. Computer Engineering and Applications, 2018, 54(17): 135-140.
[14]	HUANG Yafei, WANG Guofu, ZHANG Faquan, YE Jincai. Image denoising method based on bee colony algorithm and parametric threshold function [J]. Computer Engineering and Applications, 2018, 54(17): 164-168.
[15]	WANG Lei, SUN Wei, CHEN Yibo, LI Peng, ZAHO Lingxiao. ECG denoising method based on adaptive wavelet threshold selection [J]. Computer Engineering and Applications, 2018, 54(15): 29-33.

Method of speech denoising using wavelet transform

小波变换的语音去噪方法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics