The Journal of the Acoustical Society of Korea

The Acoustical Society of Korea (한국음향학회)
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A New Least Mean Square Algorithm Using a Running Average Process for Speech Enhancement

  • Lee, Soo-Jeong (Department of Computer Engineering, Kwangwoon University) ;
  • Ahn, Chan-Sik (Department of Computer Engineering, Kwangwoon University) ;
  • Yun, Jong-Mu (Department of Computer Engineering, Kwangwoon University) ;
  • Kim, Soon-Hyob (Department of Computer Engineering, Kwangwoon University)
  • Published : 2006.09.15
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Abstract

The adaptive echo canceller (AEC) has become an important component in speech communication systems, including mobile station. In these applications, the acoustic echo path has a long impulse response. We propose a running-average least mean square (RALMS) algorithm with a detection method for acoustic echo cancellation. Using colored input models, the result clearly shows that the RALMS detection algorithm has a convergence performance superior to the least mean square (LMS) detection algorithm alone. The computational complexity of the new RALMS algorithm is only slightly greater than that of the standard LMS detection algorithm but confers a major improvement in stability.

Keywords

References

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