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

被引：3
|
作者：
Nedeljkovic, Zeljko [1 ]
Milosevic, Milana [1 ]
Durovic, Zeljko [1 ]
机构：
[1] Univ Belgrade, Sch Elect Engn, Bulevar Kralja Aleksandra 73, Belgrade, Serbia
来源：
ARCHIVES OF ACOUSTICS | 2020年 / 45卷 / 01期
关键词：
emotion recognition; speech processing; classification algorithms;
D O I：
10.24425/aoa.2020.132489
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
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.
引用
收藏
页码：129 / 140
页数：12
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