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A SVD-based classification of bird singing in different time-frequency domains using multitapers

Author:
  • Maria Sandsten
  • Maja Tarka
  • Jessica Caissy-Martineau
  • Bengt Hansson
  • Dennis Hasselquist
Publishing year: 2011
Language: English
Pages: 966-970
Volume: 2011
Document type: Conference paper
Publisher: European Association for Signal Processing (EURASIP)

Abstract english

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.

Keywords

  • Probability Theory and Statistics

Other

19th European Signal Processing Conference, EUSIPCO 2011
2011-08-29 - 2011-09-02
Barcelona, Spain
Published
  • Stochastics in Medicine-lup-obsolete
  • Statistical Signal Processing-lup-obsolete
  • Statistical Signal Processing Group
  • ISSN: 2219-5491
Dennis Hasselquist
E-mail: dennis [dot] hasselquist [at] biol [dot] lu [dot] se

Professor

MEMEG

+46 46 222 37 08

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