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Noise Reduction Algorithm using Average Estimator Least Mean Square Filter of Frame Basis

프레임 단위의 AELMS를 이용한 잡음 제거 알고리즘

  • Ahn, Chan-Shik (Dept. of Computer Engineering, The University of Kwangwoon) ;
  • Choi, Ki-Ho (Dept. of Computer Engineering, The University of Kwangwoon)
  • 안찬식 (광운대학교 컴퓨터공학과) ;
  • 최기호 (광운대학교 컴퓨터공학과)
  • Received : 2013.04.30
  • Accepted : 2013.07.20
  • Published : 2013.07.28

Abstract

Noise estimation and detection algorithm to adapt quickly to changing noise environment using the LMS Filter. However, the LMS Filter for noise estimation for a certain period of time and need time to adapt. If the signal changes occur, have the disadvantage of being more adaptive time-consuming. Therefore, noise removal method is proposed to a frame basis AELMS Filter to compensate. In this paper, we split the input signal on a frame basis in noisy environments. Remove the LMS Filter by configuring noise predictions using the mean and variance. Noise, even if the environment changes fast adaptation time to remove the noise. Remove noise and environmental noise and speech input signal is mixed to maintain the unique characteristics of the voice is a way to reduce the damage of voice information. Noise removal method using a frame basis AELMS Filter To evaluate the performance of the noise removal. Experimental results, the attenuation obtained by removing the noise of the changing environment was improved by an average of 6.8dB.

Keywords

Speech Recognition;Noise Reduction;Least Mean Square(LMS);Average Estimator Least Mean Square(AELMS);Frame Basis Average Estimator Least Mean Square

Acknowledgement

Supported by : 광운대학교