Frequency domain acoustic echo cancellation using auxiliary function based independent component analysis
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1.Nanjing University of Information Science &2.Technology
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摘要:
传统的声回波消除(Acoustic Echo Cancellation, AEC)方法使用双端通话检测器判断单、双端通话场景,性能受限。盲源分离(Blind Source Separation, BSS)信号模型是一个远端和近端信号并存的全双工模型,因此基于BSS的AEC无需双端通话检测器。本文采用基于辅助函数的独立分量分析(Auxiliary Function Based Independent Component Analysis, Aux-ICA)算法在频域上实现声回波消除,以最小化互信息为目标函数,借助辅助函数技术进行优化。仿真实验结果表明,在连续的双端通话场景中,该方法具有较低的计算复杂度和较好的回波消除性能。
Abstract:
Traditional AEC’s performance is restricted when using double-talk detector to determine the double- talk and single-talk scenarios. Blind source separation signal model is a full duplex model with both far-end and near-end signals, so AEC based on BSS does not need the double-talk detector. This paper adopts auxiliary function based independent component analysis algorithm to realize acoustic echo cancellation in frequency domain. The object function of Aux-ICA is minimizing the mutual information, and the auxiliary function technique is used for the optimization. Simulation results show that this method has lower computational complexity and better acoustic echo cancellation performance in the continuous double-talk scenarios.