BLIND SOURCE SEPARATION AND ACOUSTIC ECHO CANCELLATION: A UNIFIED FRAMEWORK

We explore interesting connections between blind source separation (BSS) and acoustic echo cancellation (AEC), and develop a framework where the AEC problem is transformed and solved as a BSS problem. We show that by careful selection of the BSS algorithm the double-talk (DT) problem in AEC is solved without the need to use a DT detector or a step-size controller. Furthermore, the echo cancellation performance is maintained even during single-talk when only the far-end speaker is active. The algorithm converges to the true echo path much faster than the normalized least-mean squares adaptation. Moreover, the proposed algorithm does not require a knowledge of the echo-tail length and is robust against under estimation of the echo-filter length. The simple implementation and fast convergence of the proposed method makes it a suitable candidate for implementation on low-power general purpose DSPs.