Ma, N. orcid.org/0000-0002-4112-3109, May, T., Wierstorf, H. et al. (1 more author) (2015) A machine-hearing system exploiting head movements for binaural sound localisation in reverberant conditions. In: Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on. ICASSP 2015, 19-24 Apr 2015, Brisbane. IEEE ISBN 978-1-4673-6997-8
Abstract
This paper is concerned with machine localisation of multiple active speech sources in reverberant environments using two (binaural) microphones. Such conditions typically present a problem for `classical' binaural models. Inspired by the human ability to utilise head movements, the current study investigated the influence of different head movement strategies on binaural sound localisation. A machine-hearing system that exploits a multi-step head rotation strategy for sound localisation was found to produce the best performance in simulated reverberant acoustic space. This paper also reports the public release of a free binaural room impulse responses (BRIRs) database that allows the simulation of head rotation used in this study.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 IEEE. This is an author produced version of a paper subsequently published in Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - FP6/FP7 TWO!EARS - 618075 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 21 Feb 2017 13:31 |
Last Modified: | 21 Mar 2018 11:36 |
Published Version: | https://doi.org/10.1109/ICASSP.2015.7178461 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/ICASSP.2015.7178461 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:110110 |