Multiple TDOA estimation by using a state coherence transform for solving the permutation problem in frequency-domain BSS

F. Nesta, M. Omologo, P. Svaizer
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引用次数: 18

Abstract

A novel method to solve the permutation problem for Blind Source Separation (BSS) is presented. According to the acoustic propagation model, in frequency-domain, each separation matrix can be represented with a set of states associated with each source. We formulate a novel transform of the states which is independent of the aliasing and of the permutations since states belonging to all the sources are exploited at the same time. The estimated TDOAs are used to model the propagation of the acoustic wave and to cluster all the frequency components associated to the same source. Experimental results show that the novel approach can be applied to localize and separate sources in challenging situations: two sources have been separated estimating long demixing filters (0.25-0.5s) using widely spaced microphones (0.25 m) in reverberant environment (T60 = 700 ms) and using very short signals (0.5-1 s).
基于状态相干变换的多重TDOA估计解决频域BSS中的排列问题
提出了一种解决盲源分离(BSS)中排列问题的新方法。根据声传播模型,在频域中,每个分离矩阵可以用与每个声源相关联的一组状态来表示。由于同时利用了属于所有源的状态,我们提出了一种新的状态变换,它与混叠和排列无关。估计的tdoa用于模拟声波的传播,并将与同一声源相关的所有频率分量聚类。实验结果表明,这种新方法可以应用于具有挑战性的情况下的声源定位和分离:在混响环境(T60 = 700 ms)和使用非常短的信号(0.5-1 s)下,使用宽间距麦克风(0.25 m)估计长除混滤波器(0.25-0.5s)分离了两个声源。
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