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

2016 Joint IMEKO TC1-TC7-TC13 Symposium: Metrology Across the Sciences: Wishful Thinking?

Avetisyan, H.^1 ; Bruna, O.^1 ; Holub, J.^1

Department of Measurement, Faculty of Electrical Engineering, Czech Technical University in Prague, Technicka 2, Prague 6

166 27, Czech Republic^1

关键词: Bayes Classifier;    Emotion classification;    Emotion detection;    Hybrid algorithms;    Input datas;    Keyword spotting method;    Keyword-based;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/772/1/012039/pdf
DOI  :  10.1088/1742-6596/772/1/012039

来源: IOP

【 摘 要 】

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, Naï ve Bayes Classifier, Hidden Markov Model and hybrid algorithms, have impressive results in this sphere and can reach more than 90% determining accuracy.