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Optimization of Detection Method Using a Moving Average Estimator for Speech Enhancement  

Lee, Soo-Jeong (Dept. Computer Eng. Kwangwoon University)
Shin, Kye-Hyeon (Dept. Computer Eng. Kwangwoon University)
Kim, Soon-Hyob (Dept. Computer Eng. Kwangwoon University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.44, no.3, 2007 , pp. 97-104 More about this Journal
Abstract
Adaptive echo canceller(AEC) has become an important component in speech communication systems, including mobile phones and speech recognition. In these applications, the acoustic echo path has a long impulse response. We propose a moving-averge least mean square(MVLMS) algorithm with a detection method for acoustic echo cancellation. Using, the result of the tests that used colored input models clearly shows that the MVLMS detection algorithm has convergence performance superior to the least mean square(LMS) detection algorithm alone. Although the computational complexity of the new MVLMS algorithm is only slightly greater than that of the standard LMS detection algorithm, the new algorithm confers a significant improvement in stability.
Keywords
Adaptive echo cancellation; LMS; moving average estimator; Speech enhancement;
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