Overview of existing algorithms for emotion classification. Uncertainties in evaluations of accuracies

A numerous techniques and algorithms are dedicated to extract emotions from input data. In our investigation it was stated that emotion-detection approaches can be classified into 3 following types: Keyword based / lexical-based, learning based, and hybrid. The most commonly used techniques, such as...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 772; no. 1; pp. 12039 - 12044
Main Authors Avetisyan, H, Bruna, O, Holub, J
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.11.2016
Subjects
Algorithms
Emotions
Markov chains
Physics
Support vector machines
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Summary:A numerous techniques and algorithms are dedicated to extract emotions from input data. In our investigation it was stated that emotion-detection approaches can be classified into 3 following types: Keyword based / lexical-based, learning based, and hybrid. The most commonly used techniques, such as keyword-spotting method, Support Vector Machines, Naïve Bayes Classifier, Hidden Markov Model and hybrid algorithms, have impressive results in this sphere and can reach more than 90% determining accuracy.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/772/1/012039