Methods for automatically analyzing humpback song units

Rickwood, P; Taylor, A

Methods for automatically analyzing humpback song units

Rickwood, P Taylor, A

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Publication Type:: Journal Article
Citation:: Journal of the Acoustical Society of America, 2008, 123 (3), pp. 1763 - 1772
Issue Date:: 2008-03-19

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Field	Value	Language
dc.contributor.author	Rickwood, P	en_US
dc.contributor.author	Taylor, A	en_US
dc.date.issued	2008-03-19	en_US
dc.identifier.citation	Journal of the Acoustical Society of America, 2008, 123 (3), pp. 1763 - 1772	en_US
dc.identifier.issn	0001-4966	en_US
dc.identifier.uri	http://hdl.handle.net/10453/9314
dc.description.abstract	This paper presents mathematical techniques for automatically extracting and analyzing bioacoustic signals. Automatic techniques are described for isolation of target signals from background noise, extraction of features from target signals and unsupervised classification (clustering) of the target signals based on these features. The only user-provided inputs, other than raw sound, is an initial set of signal processing and control parameters. Of particular note is that the number of signal categories is determined automatically. The techniques, applied to hydrophone recordings of humpback whales (Megaptera novaeangliae), produce promising initial results, suggesting that they may be of use in automated analysis of not only humpbacks, but possibly also in other bioacoustic settings where automated analysis is desirable. © 2008 Acoustical Society of America.	en_US
dc.relation.ispartof	Journal of the Acoustical Society of America	en_US
dc.relation.isbasedon	10.1121/1.2836748	en_US
dc.subject.classification	Acoustics	en_US
dc.subject.mesh	Animals	en_US
dc.subject.mesh	Birds	en_US
dc.subject.mesh	Animal Communication	en_US
dc.subject.mesh	Noise	en_US
dc.subject.mesh	Mathematics	en_US
dc.subject.mesh	Acoustics	en_US
dc.subject.mesh	Automatic Data Processing	en_US
dc.subject.mesh	Signal Detection, Psychological	en_US
dc.subject.mesh	Electronic Data Processing	en_US
dc.title	Methods for automatically analyzing humpback song units	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	123	en_US
utslib.for	0913 Mechanical Engineering	en_US
dc.location.activity	ISI:000254208300053	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Research)
pubs.organisational-group	/University of Technology Sydney/DVC (Research)/Institute For Sustainable Futures
utslib.copyright.status	open_access
pubs.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	123	en_US

Abstract:

This paper presents mathematical techniques for automatically extracting and analyzing bioacoustic signals. Automatic techniques are described for isolation of target signals from background noise, extraction of features from target signals and unsupervised classification (clustering) of the target signals based on these features. The only user-provided inputs, other than raw sound, is an initial set of signal processing and control parameters. Of particular note is that the number of signal categories is determined automatically. The techniques, applied to hydrophone recordings of humpback whales (Megaptera novaeangliae), produce promising initial results, suggesting that they may be of use in automated analysis of not only humpbacks, but possibly also in other bioacoustic settings where automated analysis is desirable. © 2008 Acoustical Society of America.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/9314