Speech emotion recognition research: an analysis of research focus

Abstract

This article analyses research in speech emotion recognition ("SER") from 2006 to 2017 in order to identify the current focus of research, and areas in which research is lacking. The objective is to examine what is being done in this field of research. Searching on selected keywords, we extracted and analysed 260 articles from well-known online databases. The analysis indicates that SER research is an active field of research, dozens of articles being published each year in journals and conference proceedings. The majority of articles concentrate on three critical aspects of SER, namely (1) databases, (2) suitable speech features, and (3) classification techniques to maximize the recognition accuracy of SER systems. Having carried out association analysis of the critical aspects and how they influence the performance of the SER system in term of recognition accuracy, we found that certain combination of databases, speech features and classifiers influence the recognition accuracy of the SER system. We have also suggested aspects of SER that could be taken into consideration in future works based on our review.