Unsupervised Multiple Source Localization Using Relative Harmonic Coefficients
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Hu, Yonggang
Samarasinghe, Prasanga
Abhayapala, Thushara
Gannot, Sharon
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Institute of Electrical and Electronics Engineers Inc.
Abstract
This paper presents an unsupervised multi-source localization algorithm using a recently introduced feature called the relative harmonic coefficients. We derive a closed-form expression of the feature and briefly summarize its unique properties. We then exploit this feature to develop a single-source frame/bin detector which simplifies the challenging problem of multiple source localization into a single source localization problem. We show that the underlying method is suitable for localization using overlapped, disjoint as well as simultaneous multi-source recordings. Experimental results in both simulated and real-life reverberant environments confirm improved localization accuracy of the proposed method in comparison with the existing state-of-art approach.
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Proceedings of the 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing
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2099-12-31