Methods for automatically analyzing humpback song units

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...

Full description

Bibliographic Details
Main Authors: Rickwood, P, Taylor, A
Format: Article in Journal/Newspaper
Language:unknown
Published: 2008
Subjects:
Online Access:http://hdl.handle.net/10453/9314
id ftunivtsydney:oai:opus.lib.uts.edu.au:10453/9314
record_format openpolar
spelling ftunivtsydney:oai:opus.lib.uts.edu.au:10453/9314 2023-05-15T17:10:49+02:00 Methods for automatically analyzing humpback song units Rickwood, P Taylor, A 2008-03-19 application/pdf http://hdl.handle.net/10453/9314 unknown Journal of the Acoustical Society of America 10.1121/1.2836748 Journal of the Acoustical Society of America, 2008, 123 (3), pp. 1763 - 1772 0001-4966 http://hdl.handle.net/10453/9314 Acoustics Animals Birds Animal Communication Noise Mathematics Automatic Data Processing Signal Detection Psychological Electronic Data Processing Journal Article 2008 ftunivtsydney 2022-03-13T13:57:24Z 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. Article in Journal/Newspaper Megaptera novaeangliae University of Technology Sydney: OPUS - Open Publications of UTS Scholars
institution Open Polar
collection University of Technology Sydney: OPUS - Open Publications of UTS Scholars
op_collection_id ftunivtsydney
language unknown
topic Acoustics
Animals
Birds
Animal Communication
Noise
Mathematics
Automatic Data Processing
Signal Detection
Psychological
Electronic Data Processing
spellingShingle Acoustics
Animals
Birds
Animal Communication
Noise
Mathematics
Automatic Data Processing
Signal Detection
Psychological
Electronic Data Processing
Rickwood, P
Taylor, A
Methods for automatically analyzing humpback song units
topic_facet Acoustics
Animals
Birds
Animal Communication
Noise
Mathematics
Automatic Data Processing
Signal Detection
Psychological
Electronic Data Processing
description 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.
format Article in Journal/Newspaper
author Rickwood, P
Taylor, A
author_facet Rickwood, P
Taylor, A
author_sort Rickwood, P
title Methods for automatically analyzing humpback song units
title_short Methods for automatically analyzing humpback song units
title_full Methods for automatically analyzing humpback song units
title_fullStr Methods for automatically analyzing humpback song units
title_full_unstemmed Methods for automatically analyzing humpback song units
title_sort methods for automatically analyzing humpback song units
publishDate 2008
url http://hdl.handle.net/10453/9314
genre Megaptera novaeangliae
genre_facet Megaptera novaeangliae
op_relation Journal of the Acoustical Society of America
10.1121/1.2836748
Journal of the Acoustical Society of America, 2008, 123 (3), pp. 1763 - 1772
0001-4966
http://hdl.handle.net/10453/9314
_version_ 1766067479045472256