The performance of the acoustic echo cancelation using blind source separation to reduce double-talk interference

An acoustic echo canceler (AEC) is often employed to remove the acoustic echoes generated in hands-free communication systems. The AEC cancels the acoustic echoes by approximating the echo-path with the use of an adaptive filter and subtracting the pseudo echoes generated by the filter from the observed signal. The conventional adaptive algorithm for updating the filter, however, fails in estimation of the echo-path during double-talk when both the acoustic echo and the near-end speech are observed. Recently it has been shown that the blind source separation (BSS) can be employed to perform the echo cancelation during the double-talk; however, the convergence speed is slower than that of the conventional method. In this paper, a system is proposed that combines the conventional AEC and BSS; essentially, BSS is employed as a preprocessor for the adaptive filter performing the echo cancelation. Simulation results show that the proposed system is effective for the echo-path estimation during the double-talk as well as during variation in the echo path.