Sound based human emotion recognition using MFCC & multiple SVM

Emotion recognition using human speech is one of the latest challenges in speech processing and Human Machine Interaction (HMI) for the purpose of addressing varied operational needs for the real world applications. Besides human facial expressions, speech has been proven to be one of the most valuable modalities for automatic recognition of human emotions. Speech is a spontaneous medium of perceiving emotions which provides in-depth. Here in this paper, we have used MFCC for extraction of features and Multiple Support Vector Machine (SVM) as a classifier. We have performed extensive experiment on happy, anger, sad, disgust, surprise and neutral emotion sound database. Performance analysis of multiple SVM revealed that non-linear kernel SVM achieved greater accuracy than linear SVM.