scholarly journals An Improved Variable Structure Adaptive Filter Design and Analysis for Acoustic Echo Cancellation

2015 ◽  
Vol 24 (1) ◽  
pp. 252-261 ◽  
Author(s):  
A. Kar ◽  
M. Chandra
Keyword(s):  
Adaptive Filter ◽  
Filter Design ◽  
Variable Structure ◽  
Echo Cancellation ◽  
Acoustic Echo Cancellation ◽  
Acoustic Echo

scholarly journals Simple and Efficient Double-Talk-Detector for Acoustic Echo Cancellation

2020 ◽  
Vol 37 (4) ◽  
pp. 585-592
Author(s):  
Mourad Benziane ◽  
Mohamed Bouamar ◽  
Mouldi Makdir
Keyword(s):  
Convergence Rate ◽  
Adaptive Filter ◽  
Early Stage ◽  
Recursive Estimation ◽  
Echo Cancellation ◽  
Recursive Least Squares ◽  
Acoustic Echo Cancellation ◽  
Decision Variable ◽  
Rls Algorithm ◽  
Acoustic Echo

Acoustic Echo Cancellation (AEC) is a topic that has received a great interest in recent years. However, a significant challenge remains with the problem of double-talk especially when the adaptive filter has a fast convergence rate. In this case, the double-talk detector (DTD) must reply in early stage and halt updating of the adaptive filter in order to avoid filter coefficients divergence. Indeed, a complex and inappropriate DTD can seriously affect the convergence rate of the adaptive filter and global performances of the AEC system. In this paper, an implementation of a simple and efficient DTD based on a recursive estimation of the decision variable which is resulting from the level comparison between far-end and microphone signals is proposed. The presented algorithm is then compared with the normalized cross-correlation (NCC) method which is taken as a reference in this work. In the simulation tests, the recursive least squares (RLS) algorithm is used to update the adaptive filter coefficients. The speech signals used in the tests are taken from the TIMIT database.

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