New Improved echo canceller based on Normalized LMS Adaptive filter for Single talk and Double talk Detection, Subband echo cancellation, Acoustic Echo cancellation

2010 ◽  
Vol 1 (2) ◽  
pp. 61-74 ◽  
Author(s):  
Suma S.A. ◽  
Dr. K.S.Gurumurthy
2011 ◽  
Vol 225-226 ◽  
pp. 996-999
Author(s):  
Li Jun Sun ◽  
Shou Yong Zhang ◽  
Wei Sheng Wang ◽  
Xiao Ning Zhang

In an adaptive echo canceller, the detection algorithm able to distinguish echo path change (EPC) from double-talk (DT) is vital to ensure that adaptive filter tap coefficients are updated in case of EPC and frozen during the DT period. The paper presents a new echo cancel algorithm, which can protect the adaptive filter performance during double-talk in acoustic echo cancellation of teleconference without setting a detector. A judgment value can be directly used in the iteration formula to control the iteration speed of the filter, which composed of the correlation of the far-end signal and near-end received signal, the pre-correlation of the error signal. The computer simulation results verify that the mentioned algorithm has the good double talk protection performance, and it is very useful and efficient in distinguishing EPC from DT but with less computational complexity contrast to the congener algorithm.


2020 ◽  
Vol 37 (4) ◽  
pp. 585-592
Author(s):  
Mourad Benziane ◽  
Mohamed Bouamar ◽  
Mouldi Makdir

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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