Source Localization for Multiple Speech Sources Using Low Complexity Non-Parametric Source Separation and Clustering

Mikael Swartling, Benny Sällberg, Nedelko Grbic

Research output: Contribution to journalArticlepeer-review

Abstract

This article presents a new method for localization of multiple concurrent speech sources that relies on simultaneous blind signal separation and direction of arrival (DOA) estimation, as well as a method to solve the intersection point selection problem that arises when locating multiple speech sources using multiple sensor arrays. The proposed method is based on a low complexity non-parametric blind signal separation method, making is suitable for real-time applications on embedded platforms. On top of reduced complexity in comparison to a previously presented method, the DOA estimation accuracy is also improved. Evaluation of the performance is done with both real recording and simulations, and a real-time prototype of the proposed method has been implemented on a DSP platform to evaluate the computational and the memory complexities in a real application.
Original languageEnglish
Pages (from-to)1781–1788
Number of pages8
JournalSignal Processing
Volume91
Issue number8
DOIs
Publication statusPublished - 2011 Aug
Externally publishedYes

Subject classification (UKÄ)

  • Signal Processing

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