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Multimodal analysis of personality traits on videos of self-presentation and induced behavior

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Abstract

Personality analysis is an important area of research in several fields, including psychology, psychiatry, and neuroscience. With the recent dramatic improvements in machine learning, it has also become a popular research area in computer science. While the current computational methods are able to interpret behavioral cues (e.g., facial expressions, gesture, and voice) to estimate the level of (apparent) personality traits, accessible assessment tools are still substandard for practical use, not to mention the need for fast and accurate methods for such analyses. In this study, we present multimodal deep architectures to estimate the Big Five personality traits from (temporal) audio-visual cues and transcribed speech. Furthermore, for a detailed analysis of personality traits, we have collected a new audio-visual dataset, namely: Self-presentation and Induced Behavior Archive for Personality Analysis (SIAP). In contrast to the available datasets, SIAP introduces recordings of induced behavior in addition to self-presentation (speech) videos. With thorough experiments on SIAP and ChaLearn LAP First Impressions datasets, we systematically assess the reliability of different behavioral modalities and their combined use. Furthermore, we investigate the characteristics and discriminative power of induced behavior for personality analysis, showing that the induced behavior indeed includes signs of personality traits.

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Data Availability Statement

The collected SIAP dataset will be made available for research purposes upon requests with a signed EULA.

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Acknowledgements

Authors would like to thank Mr. Alper Dağgez, Ms. Merve Nur Doğanlı and Prof. Gül Günaydin for their contributions to this study.

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Author notes

  1. Dersu Giritlioğlu, Burak Mandira, Selim Firat Yilmaz, Can Ufuk Ertenli have equally contributed.

Authors and Affiliations

  1. Department of Computer Engineering, Bilkent University, Ankara, Turkey

    Dersu Giritlioğlu, Burak Mandira & Hamdi Dibeklioğlu

  2. Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey

    Selim Firat Yilmaz

  3. Department of Computer Engineering, Middle East Technical University, Ankara, Turkey

    Can Ufuk Ertenli

  4. Department of Neuroscience, Bilkent University, Ankara, Turkey

    Berhan Faruk Akgür, Merve Kınıklıoğlu & Aslı Gül Kurt

  5. Psychiatry Clinic, Etimesgut Şehit Sait Ertürk State Hospital, Ankara, Turkey

    Emre Mutlu

  6. Department of Psychiatry, Hacettepe University, Ankara, Turkey

    Şeref Can Gürel

  7. Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands

    Şeref Can Gürel

Authors
  1. Dersu Giritlioğlu
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Giritlioğlu, D., Mandira, B., Yilmaz, S.F. et al. Multimodal analysis of personality traits on videos of self-presentation and induced behavior. J Multimodal User Interfaces 15, 337–358 (2021). https://doi.org/10.1007/s12193-020-00347-7

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