Joint Modeling of Big Five and HEXACO for Multimodal Apparent Personality-trait Recognition
This work addresses the need for more comprehensive personality recognition in psychology and AI applications, but it is incremental as it builds on existing multimodal methods by adding HEXACO modeling.
The paper tackles the problem of automatically recognizing apparent personality traits from multimodal human behavior by jointly modeling the Big Five and HEXACO traits, and it demonstrates that the proposed method can effectively recognize both sets of traits in experiments using a self-introduction video dataset.
This paper proposes a joint modeling method of the Big Five, which has long been studied, and HEXACO, which has recently attracted attention in psychology, for automatically recognizing apparent personality traits from multimodal human behavior. Most previous studies have used the Big Five for multimodal apparent personality-trait recognition. However, no study has focused on apparent HEXACO which can evaluate an Honesty-Humility trait related to displaced aggression and vengefulness, social-dominance orientation, etc. In addition, the relationships between the Big Five and HEXACO when modeled by machine learning have not been clarified. We expect awareness of multimodal human behavior to improve by considering these relationships. The key advance of our proposed method is to optimize jointly recognizing the Big Five and HEXACO. Experiments using a self-introduction video dataset demonstrate that the proposed method can effectively recognize the Big Five and HEXACO.