• DocumentCode
    2265735
  • Title

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

  • Author

    Hansson-Sandsten, Maria ; Tarka, Maja ; Caissy-Martineau, Jessica ; Hansson, Bengt ; Hasselquist, Dennis

  • Author_Institution
    Centre for Math. Sci., Lund Univ., Lund, Sweden
  • fYear
    2011
  • fDate
    Aug. 29 2011-Sept. 2 2011
  • Firstpage
    966
  • Lastpage
    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 multitapers are compared to the more recently proposed locally stationary process multitapers.
  • Keywords
    bioacoustics; biology computing; feature extraction; signal classification; singular value decomposition; time-frequency analysis; SVD-based classification; Thomson multitapers; Welch method; bird singing; classification feature extraction; detecting syllables; doppler domains; locally stationary process multitapers; male great reed warblers; singular vectors; sonogram; syllable classification; time-frequency domains; Birds; Feature extraction; Kernel; Robustness; Spectrogram; Time-frequency analysis; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference, 2011 19th European
  • Conference_Location
    Barcelona
  • ISSN
    2076-1465
  • Type

    conf

  • Filename
    7073944