Author’s Name : G.Saranya, G.Mary Amirtha Sagayee, G.S.Anandha Mala
Volume 01 Issue o5 Year 2014
ISSN no: 2348-3121
Page no: 110-113
Abstract—Emotional state of the human can be detected and analyzed by various aspects such as facial expressions, voice tone and body gestures. The detected expressions are analyzed and interrupted by the system. This method is very useful in Human Computer Interaction. Deblocking is the main step in detecting the various expressions of the human. Expressions are classified using respective classifiers for detecting emotional state using multi modalities. In the proposed approach facial expressions and voice tone are used to detect the emotional state. The key point detection in the image is obtained using Independent Component Analysis (ICA). Principal Component Analysis (PCA) is used for train the images. Similarly for speech Mel-Frequency Cepstral Coefficient (MFCC) and Sub band based Cepstral parameter (SBC) are used for feature extraction from the voice tone. Decision level fusion is used to combine the facial expressions and the emotional speech.
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