• DocumentCode
    3461179
  • Title

    Automatic identification of bird species based on sinusoidal modeling of syllables

  • Author

    Härmä, Aki

  • Author_Institution
    Lab. of Acoust. & Audio Signal Process., Helsinki Univ. of Technol., Espoo, Finland
  • Volume
    5
  • fYear
    2003
  • fDate
    6-10 April 2003
  • Abstract
    Syllables are elementary building blocks of bird song. In the sounds of many songbirds, a large class of syllables can be approximated as amplitude and frequency varying brief sinusoidal pulses. We test how well bird species can be recognized by comparing simple sinusoidal representations of isolated syllables. Results are encouraging and show that, with limited sets of bird species, a recognizer based on this signal model may already be sufficient.
  • Keywords
    audio signal processing; identification; pattern recognition; signal representation; zoology; biology; bird song; bird species identification; bird species recognition; digital representations; sinusoidal modeling; songbirds; syllables; Acoustic pulses; Acoustic signal processing; Biomedical signal processing; Birds; Energy resolution; Frequency; Humans; Laboratories; Speech; Tongue;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7663-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.2003.1200027
  • Filename
    1200027