A study of automatic feature selection system based on KL-divergence for emotion recognition in speech

Abstract

We focuses on emotion recognition using prosodic features in speech.There are some differences in prosodic features among indivisuals.Therefore, the accuracy of emotion recognition goes down.This paper proposes evaluation method of feature selection.We apply KL-divergence to measure a distribution of prosodic features in emotional speech.It can quantify a effectiveness of individuals and of speaker's emotion on prosodic features.So, we can choose the most suitable features for emotion recognition system.Furthermore, we propose a method of feature selection system, using Genetic Algorithm(GA)making use of benchmark based on KL-divergence.We can make more effective features choices from a variety of options using this method.