• DocumentCode
    2533190
  • Title

    On using prefiltration in HMM-based bird species recognition

  • Author

    Wielgat, R. ; Swietojanski, P. ; Potempa, T. ; Krol, D.

  • Author_Institution
    Dept. of Technol., Higher State Vocational Sch. in Tarnow, Tarnow, Poland
  • fYear
    2012
  • fDate
    18-21 Sept. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Automatic bird species recognition method using their voices is presented in this paper. The selected bird species have been detected by hidden Markov models (HMM) classifier using Mel-frequency cepstral coefficients (MFCC). In order to support recognition process, analysed signals have been appropriately filtered before classification in the so called prefiltration process. The prefiltration strategy assumed using n-th order IIR Butterworth filter bank. Each filter from the filter bank was applied for band pass filtration in the bird species-specific and signal type band. Increase of recognition accuracy has been observed in case of prefiltration with properly chosen filter order. Experiments have been carried out on the set of bird voices containing 30 bird species, one of which is endangered with extinction.
  • Keywords
    Butterworth filters; IIR filters; band-pass filters; hidden Markov models; signal classification; HMM classifier detection; HMM-based bird species recognition; MFCC; automatic bird species recognition method; band pass filtration; bird species specific band; bird voices; hidden Markov models classifier detection; mel-frequency cepstral coefficients; n-th order IIR Butterworth filter bank; prefiltration process; signal analysis; signal type band; Birds; Feature extraction; Harmonic analysis; Hidden Markov models; Mel frequency cepstral coefficient; Noise measurement; Power harmonic filters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals and Electronic Systems (ICSES), 2012 International Conference on
  • Conference_Location
    Wroclaw
  • Print_ISBN
    978-1-4673-1710-8
  • Electronic_ISBN
    978-1-4673-1709-2
  • Type

    conf

  • DOI
    10.1109/ICSES.2012.6382258
  • Filename
    6382258