基于辅助函数独立分量分析的频域声回波消除

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.

Frequency domain acoustic echo cancellation using auxiliary function based independent component analysis

The performance of traditional Acoustic Echo Cancellation (AEC) is restricted due to the double-talk detector it used to determine the double-talk and single-talk scenarios.While Blind Source Separation (BSS) signal model is a full duplex model with both far-end and near-end signals, thus the BSS-based AEC does not need the double-talk detector.This paper adopts Auxiliary function based Independent Component Analysis (Aux-ICA) algorithm to realize acoustic echo cancellation in frequency domain, in which the object function is minimizing the mutual information, and the auxiliary function technique is used for optimization.Simulation results show that this method has lower computational complexity and better performance in acoustic echo cancellation under continuous double-talk scenarios.