Localization of moving microphone arrays from moving sound sources for robot audition
Localization of moving microphone arrays from moving sound sources for robot audition
Acoustic Simultaneous Localization and Mapping (a-SLAM) jointly localizes the trajectory of a microphone array installed on a moving platform, whilst estimating the acoustic map of surrounding sound sources, such as human speakers. Whilst traditional approaches for SLAM in the vision and optical research literature rely on the assumption that the surrounding map features are static, in the acoustic case the positions of talkers are usually time-varying due to head rotations and body movements. This paper demonstrates that tracking of moving sources can be incorporated in a-SLAM by modelling the acoustic map as a Random Finite Set (RFS) of multiple sources and explicitly imposing models of the source dynamics. The proposed approach is verified and its performance evaluated for realistic simulated data.
1008-1012
European Signal Processing Conference
Evers, Christine
93090c84-e984-4cc3-9363-fbf3f3639c4b
Moore, Alastair H.
58d011fd-6a02-449a-9b77-651e8c86166e
Naylor, Patrick A.
13079486-664a-414c-a1a2-01a30bf0997b
28 November 2016
Evers, Christine
93090c84-e984-4cc3-9363-fbf3f3639c4b
Moore, Alastair H.
58d011fd-6a02-449a-9b77-651e8c86166e
Naylor, Patrick A.
13079486-664a-414c-a1a2-01a30bf0997b
Evers, Christine, Moore, Alastair H. and Naylor, Patrick A.
(2016)
Localization of moving microphone arrays from moving sound sources for robot audition.
In 2016 24th European Signal Processing Conference, EUSIPCO 2016.
vol. 2016-November,
European Signal Processing Conference.
.
(doi:10.1109/EUSIPCO.2016.7760400).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Acoustic Simultaneous Localization and Mapping (a-SLAM) jointly localizes the trajectory of a microphone array installed on a moving platform, whilst estimating the acoustic map of surrounding sound sources, such as human speakers. Whilst traditional approaches for SLAM in the vision and optical research literature rely on the assumption that the surrounding map features are static, in the acoustic case the positions of talkers are usually time-varying due to head rotations and body movements. This paper demonstrates that tracking of moving sources can be incorporated in a-SLAM by modelling the acoustic map as a Random Finite Set (RFS) of multiple sources and explicitly imposing models of the source dynamics. The proposed approach is verified and its performance evaluated for realistic simulated data.
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Published date: 28 November 2016
Venue - Dates:
24th European Signal Processing Conference, EUSIPCO 2016, , Budapest, Hungary, 2016-08-28 - 2016-09-02
Identifiers
Local EPrints ID: 444979
URI: http://eprints.soton.ac.uk/id/eprint/444979
ISSN: 2219-5491
PURE UUID: 6a49ea50-2287-432b-97bb-977899de6d86
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Date deposited: 13 Nov 2020 17:34
Last modified: 17 Mar 2024 04:01
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Contributors
Author:
Christine Evers
Author:
Alastair H. Moore
Author:
Patrick A. Naylor
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