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Acoustic Echo Cancellation During Doubletalk Using Convolutive Blind Source Separation of Signals Having Temporal Dependence

机译:使用具有时间相关性的信号的卷积盲源分离进行双向通话期间的回声消除

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This paper describes a new algorithm for acoustic echo cancellation during doubletalk or, more precisely, acoustic echo separation, based on blind source separation (BSS) of convolutively mixed signals. The signal model assumes independence between sources, but temporal dependence between time samples, specifically that the vector signals have first-order Markov dependence. The source separation is done using a maximum likelihood approach. The source separation does not always provide separation, because of too many degrees of freedom on the separation. However, when applied to the acoustic echo cancellation problem, the constraints of the echo system neatly solve this problem. An example shows that acoustic echoes can be cleanly separated during doubletalk.
机译:本文介绍了一种新算法,该算法基于卷积混合信号的盲源分离(BSS),可以在双音通话或更准确地说是声波回波分离期间消除声波回波。信号模型假设源之间具有独立性,但时间样本之间具有时间依赖性,特别是矢量信号具有一阶马尔可夫依赖性。使用最大似然方法完成源分离。源分离并不总是提供分离,因为分离的自由度太多。但是,当应用于声学回声消除问题时,回声系统的约束可以很好地解决该问题。一个示例表明,在双向通话期间可以清晰地分离出回声。

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