Emotion Classification of Infant Voice Based on Features Derived from Teager Energy Operator

Abstract

To study effective speech features which can represent different emotion styles in infant voice, nonlinear features based on Teager Energy Operator are investigated. Neutral state and 4 emotional states (i.e. happiness, impatience, anger and fear) are classified from the infant voice database. MFCC extraction and HMM-based emotion classification are used as… (More)

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