Research on Noise Reduction Algorithm Based on Combination of LMS Filter and Spectral Subtraction

  • Cao, Danyang (School of Computer, North China University of Technology) ;
  • Chen, Zhixin (School of Computer, North China University of Technology) ;
  • Gao, Xue (School of Computer, North China University of Technology)
  • Received : 2017.11.06
  • Accepted : 2018.10.17
  • Published : 2019.08.31


In order to deal with the filtering delay problem of least mean square adaptive filter noise reduction algorithm and music noise problem of spectral subtraction algorithm during the speech signal processing, we combine these two algorithms and propose one novel noise reduction method, showing a strong performance on par or even better than state of the art methods. We first use the least mean square algorithm to reduce the average intensity of noise, and then add spectral subtraction algorithm to reduce remaining noise again. Experiments prove that using the spectral subtraction again after the least mean square adaptive filter algorithm overcomes shortcomings which come from the former two algorithms. Also the novel method increases the signal-to-noise ratio of original speech data and improves the final noise reduction performance.


Least Mean Square Adaptive Filter;Spectral Subtraction;Speech Signal Processing;Signal-to-Noise Ratio


Supported by : National Natural Science Foundation of China, North China University of Technology, Beijing Natural Science Foundation


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