Journal of Guangdong University of Technology ›› 2017, Vol. 34 ›› Issue (05): 52-55.doi: 10.12052/gdutxb.160179

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A New Speech Denoising Method Based on Wiener Filtering and Wavelet Analysis

Zheng Yong-min1, Bao Hong1, Zhang Jing2   

  1. 1. School of Automation, Guangdong University of Technology, Guangzhou 510006, China;
    2. Institute of Information Science and Technology, Guangdong University of Foreign Studies, Guangzhou 510420, China
  • Received:2016-12-19 Online:2017-09-09 Published:2017-07-10

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Abstract: Denoising in wavelet analysis sets the threshold to eliminate the wavelet coefficients of the noise, which filters some useful speech signals and reduces voice quality. In order to resolve the problem, a new speech denoising method based on Wiener filter and wavelet analysis is proposed. According to the characteristic of the least mean square error of the Wiener filter, the method filters out most of the noise signal, and then denoises it by the wavelet analysis. Experiments is carried out in simulation, and the results reveal that the method is more improved than wavelet analysis in terms of signal-to-noise ratio (SNR) and speech quality.

Key words: Wiener filtering, wavelet analysis, threshold function, denoising

CLC Number: 

  • TN912.35
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