Abstract
This paper addresses the localization of an unknown number of acoustic sources in an enclosure. We extend a well established algorithm for localization of acoustic sources, which is based on the Expectation Maximization (EM) algorithm for clustering of phase differences by a Gaussian mixture model. Supporting a more appropriate probabilistic model for spherical data such as direction of arrival or phase differences, the von Mises distribution is used to derive a localization algorithm for multiple simultaneously active sources. Experiments with simulated room impulse responses confirm the superiority of the proposed algorithm to the existing method in terms of localization performance.
Original language | English |
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Title of host publication | 2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop, SAM 2018 |
Publisher | IEEE Computer Society |
Pages | 450-454 |
Number of pages | 5 |
ISBN (Print) | 9781538647523 |
DOIs | |
State | Published - 27 Aug 2018 |
Event | 10th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2018 - Sheffield, United Kingdom Duration: 8 Jul 2018 → 11 Jul 2018 |
Publication series
Name | Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop |
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Volume | 2018-July |
ISSN (Electronic) | 2151-870X |
Conference
Conference | 10th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2018 |
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Country/Territory | United Kingdom |
City | Sheffield |
Period | 8/07/18 → 11/07/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
Funding
ACKNOWLEDGMENT This work was supported by DFG under contract no <Ke890/10-1> within the Research Unit FOR2457 ”Acoustic Sensor Networks” Fig. 2: Box plot of the localization error as defined in (17) for the method [15] (abbreviated with GMM) and the proposed method (abbreviated with vM). The number after the abbreviation gives the number of microphone pairs.
Funders | Funder number |
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Deutsche Forschungsgemeinschaft | <Ke890/10-1 |