• DocumentCode
    708790
  • Title

    Detection of anuran calling activity in long field recordings for bio-acoustic monitoring

  • Author

    Jie Xie ; Towsey, Michael ; Yasumiba, Kiyomi ; Jinglan Zhang ; Roe, Paul

  • Author_Institution
    Fac. of Sci. & Technol., Queensland Univ. of Technol., Brisbane, QLD, Australia
  • fYear
    2015
  • fDate
    7-9 April 2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents a system to analyze long field recordings with low signal-to-noise ratio (SNR) for bio-acoustic monitoring. A method based on spectral peak track, Shannon entropy, harmonic structure and oscillation structure is proposed to automatically detect anuran (frog) calling activity. Gaussian mixture model (GMM) is introduced for modelling those features. Four anuran species widespread in Queensland, Australia, are selected to evaluate the proposed system. A visualization method based on extracted indices is employed for detection of anuran calling activity which achieves high accuracy.
  • Keywords
    Gaussian processes; acoustic signal processing; bioacoustics; biology computing; entropy; feature extraction; harmonic analysis; mixture models; oscillations; GMM; Gaussian mixture model; Shannon entropy; anuran calling activity detection; anuran species; bio-acoustic monitoring; extracted indices; harmonic structure; long field recordings; oscillation structure; signal-to-noise ratio; spectral peak track; visualization method; Entropy; Feature extraction; Harmonic analysis; Indexes; Meteorology; Monitoring; Spectrogram;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2015 IEEE Tenth International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4799-8054-3
  • Type

    conf

  • DOI
    10.1109/ISSNIP.2015.7106925
  • Filename
    7106925