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Normalized Double-Talk Detection Based on Microphone and AEC Error Cross-Correlation

机译:基于麦克风和AEC误差互相关的归一化双向通话检测

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In this paper, we present two different double-talk detection schemes for Acoustic Echo Cancellation (AEC). First, we present a novel normalized detection statistic based on the cross-correlation coefficient between the microphone signal and the cancellation error. The decision statistic is designed in such a way that it meets the needs of an optimal double-talk detector. We also show that the proposed detection statistic converges to the recently proposed normalized cross-correlation based double-talk detector [1], the best known cross-correlation based detector. Next, we present a new hybrid double-talk detection scheme based on a cross-correlation coefficient and two signal detectors. The hybrid algorithm not only detects double-talk but also detects and tracks any echo-path variations efficiently. We compare our results with other cross-correlation based double-talk detectors to show their effectiveness.
机译:在本文中,我们提出了两种用于回声消除(AEC)的双向通话检测方案。首先,我们基于麦克风信号和消除误差之间的互相关系数,提出了一种新颖的归一化检测统计量。以能够满足最佳双向通话检测器需求的方式来设计决策统计量。我们还表明,提出的检测统计量收敛于最近提出的基于归一化互相关的双向通话检测器[1],这是最著名的基于互相关的检测器。接下来,我们提出一种基于互相关系数和两个信号检测器的新型混合双向通话检测方案。混合算法不仅可以检测双向通话,而且可以有效地检测和跟踪任何回声路径变化。我们将我们的结果与其他基于互相关的双向通话检测器进行比较,以显示其有效性。

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