• DocumentCode
    1901526
  • Title

    Recognition of Fruit Fly Wings Vibration Sound Based on HMM

  • Author

    Zhang, Ningxian ; Guo, Min

  • Author_Institution
    Coll. of Comput. Sci., Shaanxi Normal Univ., Xi´´an, China
  • fYear
    2010
  • fDate
    25-26 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper classifies and recognizes three different strains of fruit fly by their wings vibration sounds. It uses Mel-Frequency Cepstrum Coefficient to extract features of fruit fly wings vibration sound, then applies Hidden Markov Model to establish models of three different strains of fruit fly wings vibration sound and recognize three strains of fruit fly. Experiment shows that the recognition rates of the three strains of fruit fly reach over 70%, and the result is satisfying. Thus, the method used by the paper is feasible and effective, and provides a new basis for fruit fly´s research.
  • Keywords
    acoustic signal processing; feature extraction; hidden Markov models; vibrations; HMM; feature extraction; fruit fly wings vibration sounds; hidden Markov model; mel-frequency cepstrum coefficient; recognition rates; Computational modeling; Feature extraction; Hidden Markov models; Mel frequency cepstral coefficient; Strain; Training; Vibrations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
  • Conference_Location
    Wuhan
  • ISSN
    2156-7379
  • Print_ISBN
    978-1-4244-7939-9
  • Electronic_ISBN
    2156-7379
  • Type

    conf

  • DOI
    10.1109/ICIECS.2010.5678369
  • Filename
    5678369