• DocumentCode
    2215948
  • Title

    Emotion recognition — An approach to identify the terrorist

  • Author

    Raju, N. ; Preethi, P. ; Priya, T. Lakshmi ; Mathini, S.

  • Author_Institution
    Dept. of Electron. & Commun. Eng., SASTRA Univ., Thanjavur, India
  • fYear
    2012
  • fDate
    21-23 March 2012
  • Firstpage
    422
  • Lastpage
    427
  • Abstract
    The emotional influence on human behavior can be identified by speech. Recognition of emotion plays a vital role in many fields such as automatic emotion recognition etc. In this paper, we distinguish a normal person from the terrorist/victim by identifying their emotional state from speech. Emotional states dealt with in this paper are neutral, sad, anger, fear, etc. Two different algorithm of pitch is used to extract the pitch here. Moreover, support vector machine is used to classify the emotional state. The accuracy level of the classifier differentiates the emotional state of the normal person from the terrorist/victim. For the classification of all emotions, the average accuracy of both male and female is 80%.
  • Keywords
    emotion recognition; signal classification; speech recognition; support vector machines; anger; emotion recognition; emotional state classification; fear; neutral; pitch extraction; sad; speech emotional state; support vector machine; terrorist identification; Cepstrum; Emotion recognition; Humans; Speech; Speech recognition; Support vector machines; Terrorism; Emotion Recognition; Emotional state; Pitch; SVM classifier;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, Informatics and Medical Engineering (PRIME), 2012 International Conference on
  • Conference_Location
    Salem, Tamilnadu
  • Print_ISBN
    978-1-4673-1037-6
  • Type

    conf

  • DOI
    10.1109/ICPRIME.2012.6208383
  • Filename
    6208383