基于时间相关信号卷积盲源分离的双路声回波消除

T. Moon, J. Gunther
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引用次数: 0

摘要

本文提出了一种基于卷积混合信号的盲源分离(BSS)的双路声回波消除算法,更准确地说,是声回波分离算法。信号模型假设信号源之间独立,但时间样本之间具有时间相关性,即向量信号具有一阶马尔可夫相关性。源分离是使用最大似然方法完成的。源分离并不总是提供分离,因为在分离上有太多的自由度。然而,当应用于声学回波抵消问题时,回波系统的约束条件很好地解决了这一问题。算例表明,双腔回波可以很好地分离。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Acoustic Echo Cancellation During Doubletalk Using Convolutive Blind Source Separation of Signals Having Temporal Dependence
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.
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