TY - JOUR N2 - 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. L1 - http://www.czasopisma.pan.pl/Content/115757/PDF/aoa.2020.132489.pdf L2 - http://www.czasopisma.pan.pl/Content/115757 PY - 2020 IS - No 1 EP - 140 DO - 10.24425/aoa.2020.132489 KW - emotion recognition KW - speech processing KW - classification algorithms A1 - Nedeljković, Željko A1 - Milošević, Milana A1 - Đurović, Željko PB - Polish Academy of Sciences, Institute of Fundamental Technological Research, Committee on Acoustics VL - vol. 45 DA - 2020.02.26 T1 - Analysis of Features and Classifiers in Emotion Recognition Systems: Case Study of Slavic Languages SP - 129 UR - http://www.czasopisma.pan.pl/dlibra/publication/edition/115757 T2 - Archives of Acoustics ER -