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dc.contributor.authorNordholm, Sven
dc.contributor.authorDavis, A.
dc.contributor.authorYong, P.
dc.contributor.authorDam, Hai Huyen Heidi
dc.date.accessioned2017-01-30T11:52:30Z
dc.date.available2017-01-30T11:52:30Z
dc.date.created2015-12-10T04:26:02Z
dc.date.issued2015
dc.identifier.citationNordholm, S. and Davis, A. and Yong, P. and Dam, H.H. 2015. Assistive listening headsets for high noise environments: Protection and communication, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5753-5757. South Brisbane, QLD: IEEE.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/15882
dc.identifier.doi10.1109/ICASSP.2015.7179074
dc.description.abstract

© 2015 IEEE. In industrial noise environments, the use of assistive listening headsets is a means to provide adequate access to voice communication while wearing hearing protection. This paper presents a performance evaluation and comparison of two different methods to provide the binaural speech enhancement in real industrial noise scenarios. The investigated binaural methods based on differential beamforming and multichannel Wiener filter show different strengths and weaknesses. A transient noise suppression algorithm is also proposed and evaluated. Performance evaluation shows that this algorithm, together with the binaural multi-channel Wiener filter approach, can successfully reduce the hammering noise. This can be observed from the PESQ scores and the signal characteristics.

dc.titleAssistive listening headsets for high noise environments: Protection and communication
dc.typeConference Paper
dcterms.source.volume2015-August
dcterms.source.startPage5753
dcterms.source.endPage5757
dcterms.source.titleICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
dcterms.source.seriesICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
dcterms.source.isbn9781467369978
curtin.note

Copyright © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusOpen access


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