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Survey on AI-Based Multimodal Methods for Emotion Detection

Catherine Maréchal, Dariusz Mikołajewski, Krzysztof Tyburek, Piotr Prokopowicz, Lamine Bougueroua, Corinne Ancourt, Katarzyna Węgrzyn-Wolska

Year
2019
Citations
134
Access
Open access

Abstract

Automatic emotion recognition constitutes one of the great challenges providing new tools for more objective and quicker diagnosis, communication and research. Quick and accurate emotion recognition may increase possibilities of computers, robots, and integrated environments to recognize human emotions, and response accordingly to them a social rules. The purpose of this paper is to investigate the possibility of automated emotion representation, recognition and prediction its state-of-the-art and main directions for further research. We focus on the impact of emotion analysis and state of the arts of multimodal emotion detection. We present existing works, possibilities and existing methods to analyze emotion in text, sound, image, video and physiological signals. We also emphasize the most important features for all available emotion recognition modes. Finally, we present the available platform and outlines the existing projects, which deal with multimodal emotion analysis.

Keywords

Emotion detectionEmotion recognitionComputer scienceFocus (optics)Representation (politics)Affective computingEmotion classificationState (computer science)Human–computer interactionArtificial intelligence

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