Joint Modeling of Big Five and HEXACO for Multimodal Apparent Personality-trait Recognition
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915557193809920 |
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| author | Masumura, Ryo Orihashi, Shota Ihori, Mana Tanaka, Tomohiro Makishima, Naoki Yamane, Taiga Kawata, Naotaka Suzuki, Satoshi Katayama, Taichi |
| author_facet | Masumura, Ryo Orihashi, Shota Ihori, Mana Tanaka, Tomohiro Makishima, Naoki Yamane, Taiga Kawata, Naotaka Suzuki, Satoshi Katayama, Taichi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_14203 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Joint Modeling of Big Five and HEXACO for Multimodal Apparent Personality-trait Recognition Masumura, Ryo Orihashi, Shota Ihori, Mana Tanaka, Tomohiro Makishima, Naoki Yamane, Taiga Kawata, Naotaka Suzuki, Satoshi Katayama, Taichi Computer Vision and Pattern Recognition Computation and Language Multimedia 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. |
| title | Joint Modeling of Big Five and HEXACO for Multimodal Apparent Personality-trait Recognition |
| topic | Computer Vision and Pattern Recognition Computation and Language Multimedia |
| url | https://arxiv.org/abs/2510.14203 |