• DocumentCode
    3100026
  • Title

    Research of detecting fatigue from speech by PNN

  • Author

    Zhang, Xiao-Jun ; Gu, Ji-Hua ; Tao, Zhi

  • Author_Institution
    Dept. of Phys. Sci. & Tech., Soochow Univ., Suzhou, China
  • Volume
    2
  • fYear
    2010
  • fDate
    18-19 Oct. 2010
  • Abstract
    Fatigue is a natural phenomenon which is a kind of self-regulation and protection for human body. Detection fatigue states have positive significance for all occupations now. This paper presents a feature-based parameters and the probabilistic neural network (PNN) speech recognition model to detect fatigue. Through training at different times of voice samples as the voice sources and establishing a comprehensive identification system. Experimental results show that this way can reflect the degree of fatigue. MFCC parameters is superior to LPCC.
  • Keywords
    cepstral analysis; fatigue; feature extraction; neural nets; speech recognition; PNN; comprehensive identification system; melfrequency cepstral coefficient; probabilistic neural network; speech fatigue detection; speech recognition model; voice sampling; Mel frequency cepstral coefficient; Fatique; LPCC; MFCC; PNN; Speech;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Networking and Automation (ICINA), 2010 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-8104-0
  • Electronic_ISBN
    978-1-4244-8106-4
  • Type

    conf

  • DOI
    10.1109/ICINA.2010.5636509
  • Filename
    5636509