Archives of Acoustics, 45, 1, pp. 129–140, 2020
10.24425/aoa.2020.132489

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

Željko NEDELJKOVIĆ
University of Belgrade
Serbia

Milana MILOŠEVIĆ
University of Belgrade
Serbia

Željko ĐUROVIĆ
University of Belgrade
Serbia

Today’s human-computer interaction systems have a broad variety of applications in which automatic human emotion recognition is of great interest. Literature contains many different, more or less successful forms of these systems. This work emerged as an attempt to clarify which speech features are the most informative, which classification structure is the most convenient for this type of tasks, and the degree to which the results are influenced by database size, quality and cultural characteristic of a language. The research is presented as the case study on Slavic languages.
Keywords: emotion recognition; speech processing; classification algorithms
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DOI: 10.24425/aoa.2020.132489

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