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Expressing Personality Through Non-verbal Behaviour in Real-Time Interaction
Maryam Saberi1, Steve DiPaola1, Ulysses Bernardet2
1School of Interactive Arts and Technology, Simon Fraser University, Vancouver, BC, Canada.
This study introduces a novel generative personality model for virtual humans, successfully enabling them to display realistic non-verbal behaviors that convey distinct personality traits to users.
Area of Science:
- Artificial Intelligence
- Psychology
- Human-Computer Interaction
Background:
- Traditional personality models are analytical, classifying traits from observed behavior.
- A generative approach, where personality models produce behavior, is less explored.
Purpose of the Study:
- To develop and evaluate a generative personality model for virtual humans.
- To enable artificial social agents to exhibit believable personality traits through non-verbal behaviors.
- To shift from analytical to generative methods in personality research.
Main Methods:
- Developed a model controlling non-verbal behaviors (gaze, facial expression, gesture, posture) for a virtual human.
- Model parameters are based on empirical behavioral science findings, focusing on extra/introversion and stability/neuroticism.
- Evaluated the model through passive (video ratings) and presential (real-time interaction) experiments.
Main Results:
- The generative personality model effectively conveyed distinct personality impressions to users.
- Participants successfully attributed personality characteristics to the virtual human based on its behavior.
- Real-time interaction with the embodied model proved effective in generating personality perceptions.
Conclusions:
- The generative approach, embodied in interactive artificial social agents, is a promising new direction for personality research.
- This methodology opens novel research questions in personality theory and artificial social intelligence.
- Virtual human behavior generation can be a powerful tool for understanding and attributing personality.
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