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

机译:使用盲源分离以减少双向通话干扰的声学回声消除的性能

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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.
机译:回声消除器(AEC)通常用于消除免提通信系统中产生的回声。 AEC通过使用自适应滤波器近似回声路径并从观察到的信号中减去由滤波器生成的伪回声来消除声学回声。但是,当同时观察到声学回声和近端语音时,用于更新滤波器的常规自适应算法无法在双向通话期间估计回声路径。近来,已经显示出可以在双通话期间使用盲源分离(BSS)来执行回声消除;然而,在盲通话中,可以使用盲源分离(BSS)。但是,收敛速度比传统方法慢。本文提出了一种将传统的AEC和​​BSS相结合的系统。本质上,BSS被用作执行回声消除的自适应滤波器的预处理器。仿真结果表明,所提出的系统对于双向通话以及回声路径变化期间的回声路径估计都是有效的。

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