This paper presents batch and online algorithms of a stereo acoustic echo cancellation (SAEC) method. In SAEC, the non-uniqueness problem causes performance degradation, especially for highly coherent far-end signals. In our method, this problem can be avoided without an additional decorrelation preprocessor or multi-microphones by overestimating far-end echoes and compensating for the overestimated inter-channel-correlated echo to obtain a desired echo-canceled signal. In addition, our method is based on the maximum likelihood estimation (MLE) criterion of the echo-canceled signal under the assumption that the signal in the time-frequency domain follows a zero-mean complex Gaussian distribution with a time-varying variance. Furthermore, a variable forgetting factor based on the cross spectral density (CSD) between the echo-canceled signal and a far-end echo is presented in the online algorithm to improve the convergence of adaptive filters with a high cancellation performance when converged. Experimental results under various conditions demonstrate that the proposed method can successfully perform SAEC even in the presence of inter-channel correlation, double-talk, and abrupt echo path changes.

中文翻译：

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基于信道间相关回声补偿的最大似然估计的立体声回声消除

本文介绍了立体声声学回声消除 (SAEC) 方法的批处理和在线算法。在 SAEC 中，非唯一性问题会导致性能下降，尤其是对于高度相干的远端信号。在我们的方法中，通过高估远端回声和补偿高估的通道间相关回声以获得所需的回声消除信号，可以避免这个问题，而无需额外的去相关预处理器或多麦克风。此外，我们的方法基于回声消除信号的最大似然估计 (MLE) 标准，假设时频域中的信号遵循具有时变方差的零均值复高斯分布。此外，在线算法中提出了基于回声消除信号和远端回声之间的交叉谱密度 (CSD) 的可变遗忘因子，以提高自适应滤波器在收敛时具有高消除性能的收敛性。各种条件下的实验结果表明，即使在存在通道间相关、双向通话和突然回声路径变化的情况下，所提出的方法也能成功地执行 SAEC。