华南理工大学学报(自然科学版) ›› 2018, Vol. 46 ›› Issue (3): 103-107.doi: 10.3969/j.issn.1000-565X.2018.03.015

• 物理 • 上一篇    下一篇

谱减法与维纳滤波法相结合的睡眠鼾声降噪处理

彭健新 唐云飞   

  1. 华南理工大学 物理与光电学院,广东 广州 510640
  • 收稿日期:2017-06-29 修回日期:2017-09-26 出版日期:2018-03-25 发布日期:2018-03-01
  • 通信作者: 彭健新(1968-),男,博士,教授,主要从事建筑声学与环境声学、音频信号处理、功率超声研究. E-mail:phjxpeng@scut.edu.cn
  • 作者简介:彭健新(1968-),男,博士,教授,主要从事建筑声学与环境声学、音频信号处理、功率超声研究.
  • 基金资助:
    广东省科技计划项目(2013B060100005) 

Noise Reduction of Snoring Sound by Using Traditional Spectral Subtraction and Wiener Filter
 

 PENG Jianxin TANG Yunfei    

  1.  School of Physics and Optoelectronics,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2017-06-29 Revised:2017-09-26 Online:2018-03-25 Published:2018-03-01
  • Contact: 彭健新(1968-),男,博士,教授,主要从事建筑声学与环境声学、音频信号处理、功率超声研究. E-mail:phjxpeng@scut.edu.cn
  • About author:彭健新(1968-),男,博士,教授,主要从事建筑声学与环境声学、音频信号处理、功率超声研究.
  • Supported by:
      Supported by the Science and Technology Planning Project of Guangdong Province(2013B060100005) 

摘要: 为提高鼾声信号的信噪比,提出了一种传统谱减法和维纳滤波法相结合的睡眠 鼾声信号预处理方法. 首先利用传统谱减法对带噪鼾声信号进行初步增强,使用子空间投 影法将带噪鼾声投影到噪声和纯净信号两个子空间并得到信噪比,再由信噪比得到维纳 滤波器的传输函数,谱减法处理后的鼾声信号通过该滤波器后会进一步降低噪声. 对叠加 白噪声的鼾声信号的仿真结果表明,文中方法可获得高于谱减法和维纳滤波法单独使用 时的信噪比,降噪效果优于传统谱减法和维纳滤波法. 

关键词: 鼾声, 降噪, 谱减法, 维纳滤波法, 子空间投影法, 信噪比 

Abstract:  A method to improve the signalto-noise ratio (SNR) of snoring sound is proposed in combination with the traditional spectral subtraction and Wiener filter in this study. Firstly, the noisy snoring signals are slightly enhanced by traditional spectral subtraction by projecting the noisy snoring to noise space and signal space by a method of subspace projection so that the SNR is obtained. Then a transfer function of Wiener filter from SNR is obtained. Finally,when the snoring sound processed by traditional spectral subtraction is filtered by the Wiener filter, the noise in snoring sound can be further reduced. The results of the simulation of snoring sound with additive white noise show that the method used in the study gets a higher SNR than that by the traditional subtraction or Wiener filter. It is proved that the method can do better than the one of traditional subtraction or Wiener filter in noise reduction. 

Key words: snoring sound, noise reduction, spectral subtraction, Wiener filter, subspace projection, signaltonoise ratio

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