Analysis of Features and Classifiers in Emotion Recognition Systems: Case Study of Slavic Languages

Today’s human-computer interaction systems have a broad variety of applications in which automatic human emotion recognition is great interest. Literature contains many different, more or less successful forms these systems. This work emerged as an attempt to clarify speech features are the most informative, classification structure convenient for this type tasks, and degree results influenced by database size, quality cultural characteristic language. The research presented case study on Slavic languages.