Emotion recognition in non-structured utterances for human-robot interaction

Abstract

The aim of our research is to provide robots the capability to interpret the emotions of their counterparts. The lack of automatic recognition of emotional expression in speech presents an important challenge to the pattern analysis and human-robot interaction research community. Emotion recognition in speech provides useful information of the state of the speaker which enhances communication between humans and robots. In this paper, the results obtained from applying well-known techniques for pattern recognition to emotion recognition in speech are described. The novelty of the paper relies on testing these techniques over non-structured utterances. While classifiers have been trained with synthetic data, the validation set has been created using utterances extracted from movies. Classifiers' performance has been measured against human classification for the same validation set.