Blind detection of exclusive source activity periods in reverberant acoustic environments

R. M. Nickel
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Abstract

Blind separation and dereverberation of acoustic sources is still considered a very challenging task despite many years of research and the availability of increasingly powerful computation engines. The complexity of the task can be significantly reduced for sources that exhibit sufficiently long exclusive activity periods (EAPs). EAPs are time intervals during which only one source is active and all other sources are inactive (i.e. zero). During EAPs the estimation of the underlying system parameters simplifies from a MIMO type to a SIMO type. The existence of EAPs is not guaranteed for arbitrary signal classes. EAPs occur very frequently, however, in recordings of conversational speech. In this paper we propose a new low complexity method for EAP detection which significantly outperforms earlier approaches.
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混响声环境中唯一声源活动周期的盲检测
尽管经过多年的研究和越来越强大的计算引擎的可用性,声源的盲分离和去噪仍然被认为是一个非常具有挑战性的任务。对于具有足够长的独占活动周期(eap)的源,可以显著降低任务的复杂性。eap是指只有一个源处于活动状态,所有其他源处于非活动状态(即零)的时间间隔。在eap过程中,底层系统参数的估计从MIMO类型简化为SIMO类型。对于任意信号类,不能保证eap的存在。然而,在会话语音的记录中,eap却非常频繁地出现。在本文中,我们提出了一种新的低复杂度的EAP检测方法,该方法明显优于先前的方法。
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