Multimodal recognition of personality traits in human-computer collaborative tasks

  • Authors:
  • Ligia Batrinca;Bruno Lepri;Nadia Mana;Fabio Pianesi

  • Affiliations:
  • CIMeC, University of Trento & FBK, Rovereto, Italy;FBK and Massachusettes Institute of Technology, Trento, Italy;FBK, Trento, Italy;FBK, Trento, Italy

  • Venue:
  • Proceedings of the 14th ACM international conference on Multimodal interaction
  • Year:
  • 2012

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Abstract

The user's personality in Human-Computer Interaction (HCI) plays an important role for the overall success of the interaction. The present study focuses on automatically recognizing the Big Five personality traits from 2-5 min long videos, in which the computer interacts using different levels of collaboration, in order to elicit the manifestation of these personality traits. Emotional Stability and Extraversion are the easiest traits to automatically detect under the different collaborative settings: all the settings for Emotional Stability and intermediate and fully-non collaborative settings for Extraversion. Interestingly, Agreeableness and Conscientiousness can be detected only under a moderately non-collaborative setting. Finally, our task does not seem to activate the full range of dispositions for Creativity.