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

  • Maria Sandsten
  • Maja Tarka
  • Jessica Caissy-Martineau
  • Bengt Hansson
  • Dennis Hasselquist
Publishing year: 2011
Language: English
Pages: 966-970
Publication/Series: European Signal Processing Conference
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.


  • Probability Theory and Statistics


19th European Signal Processing Conference, EUSIPCO 2011
2011-08-29 - 2011-09-02
Barcelona, Spain
  • 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



+46 46 222 37 08



Research group


Doctoral students and postdocs

Research fellows


Jacob Roved

PhD Students, main supervisor

PhD Students, assistant supervisor


Interview about my research in the Swedish podcast "Forskarn & jag"