An Ensemble Classifiers Approach for Emotion Classification
| Autor: | Mohamed Walid Chaibi |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Computer science Emotion classification Machine learning computer.software_genre Variety (cybernetics) Random subspace method State (computer science) Artificial intelligence Emotion recognition business computer Protocol (object-oriented programming) Cascading classifiers Decoding methods |
| Zdroj: | Intelligent Interactive Multimedia Systems and Services 2017 ISBN: 9783319594798 IIMSS |
| Popis: | Decoding the emotional state of a person has a variety of applications. It could be used in human-computer interaction (HCI) or like follow-ups in the therapeutic techniques. Recently, emotion recognition is one of topic that researchers are most interested in and until now, there are several studies relating to the emotion using devices and techniques. To recognize human emotions, various physiological signals have been widely used. In this research, we propose a novel approach for the emotion classification using several physiological signals to classify eight emotions according to the Clynes sentograph protocol of Manfred Clynes. The study has two main objectives. On the one hand a comparative study to choose the best classifiers that addresses the emotion classification problem. And On the other hand to develop an ensemble classifiers approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|