A SVD-based classification of bird singing in different time-frequency domains using multitapers
(2011) 19th European Signal Processing Conference, EUSIPCO 2011 2011. p.966-970- Abstract
- In this paper, a novel method for analysing a bird’s song is presented. The song of male great reed warblers is used for developing and testing the methods. A robust method for detecting syllables is proposed and a classification of those syllables as compared to reference syllables is done. The extraction of classification features are based on the use of singular vectors in different time-frequency domains, such as the ambiguity and the doppler domains, in addition to the usual sonogram. The analysis is also made using multitaper analysis where the Welch method and the Thomson multi- tapers are compared to the more recently proposed locally stationary process multitapers.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2225102
- author
- Sandsten, Maria LU ; Tarka, Maja LU ; Caissy-Martineau, Jessica ; Hansson, Bengt LU and Hasselquist, Dennis LU
- organization
-
- Stochastics in Medicine-lup-obsolete (research group)
- Statistical Signal Processing-lup-obsolete (research group)
- eSSENCE: The e-Science Collaboration
- Statistical Signal Processing Group (research group)
- Mathematical Statistics
- MEMEG
- BECC: Biodiversity and Ecosystem services in a Changing Climate
- Molecular Ecology and Evolution Lab (research group)
- publishing date
- 2011
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- European Signal Processing Conference
- volume
- 2011
- pages
- 5 pages
- publisher
- European Association for Signal Processing (EURASIP)
- conference name
- 19th European Signal Processing Conference, EUSIPCO 2011
- conference location
- Barcelona, Spain
- conference dates
- 2011-08-29 - 2011-09-02
- external identifiers
-
- scopus:84863743980
- ISSN
- 2219-5491
- language
- English
- LU publication?
- yes
- id
- d9e2f018-bd60-4a65-b4af-ec66c7fc1b54 (old id 2225102)
- alternative location
- http://www.eurasip.org/Proceedings/Eusipco/Eusipco2011/papers/1569422961.pdf
- date added to LUP
- 2016-04-01 13:50:11
- date last changed
- 2024-05-09 13:11:19
@inproceedings{d9e2f018-bd60-4a65-b4af-ec66c7fc1b54, abstract = {{In this paper, a novel method for analysing a bird’s song is presented. The song of male great reed warblers is used for developing and testing the methods. A robust method for detecting syllables is proposed and a classification of those syllables as compared to reference syllables is done. The extraction of classification features are based on the use of singular vectors in different time-frequency domains, such as the ambiguity and the doppler domains, in addition to the usual sonogram. The analysis is also made using multitaper analysis where the Welch method and the Thomson multi- tapers are compared to the more recently proposed locally stationary process multitapers.}}, author = {{Sandsten, Maria and Tarka, Maja and Caissy-Martineau, Jessica and Hansson, Bengt and Hasselquist, Dennis}}, booktitle = {{European Signal Processing Conference}}, issn = {{2219-5491}}, language = {{eng}}, pages = {{966--970}}, publisher = {{European Association for Signal Processing (EURASIP)}}, title = {{A SVD-based classification of bird singing in different time-frequency domains using multitapers}}, url = {{http://www.eurasip.org/Proceedings/Eusipco/Eusipco2011/papers/1569422961.pdf}}, volume = {{2011}}, year = {{2011}}, }