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In this work, we consider the multiple sound source location estimation and counting problem in a wireless acoustic sensor network, where each sensor consists of a microphone array. Our method is based on inferring a location estimate for each frequency of the captured signals. A clustering approach-where the number of clusters (i.e., sound sources) is also an unknown parameter-is then employed to...
In this paper, we consider the data association problem that arises when localizing multiple sound sources using direction of arrival (DOA) estimates from multiple microphone arrays. In such a scenario, the association of the DOAs across the arrays that correspond to the same source is unknown and must be found for accurate localization. We present an association algorithm that finds the correct DOA...
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