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
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;
Conference_Titel :
Pattern Recognition, Informatics and Medical Engineering (PRIME), 2012 International Conference on
Conference_Location :
Salem, Tamilnadu
Print_ISBN :
978-1-4673-1037-6
DOI :
10.1109/ICPRIME.2012.6208383