Automatic Assessment of Human Personality Traits: A Step Towards Intelligent Human-Robot Interaction

Abstract

Personality is nothing but individual differences in the way we tend to think, feel and behave. It is ingrained in our basic instincts which tend to answer the question of why people differ in behavioral aspects in our day-to-day life. The assessment of personality traits is highly significant in human-human interaction. However, the topic has not been studied extensively in the context of human-robot interaction. This study focuses on the significance of nonverbal cues with respect to personality traits. A supervised learning approach has been used to recognize 3 personality traits of the big five model namely extroversion, agreeableness and neuroticism traits. Nonverbal cues such as head gestures, postures, proxemics, facial expressions and bodily cues are used to construct a feature vector for classification. A humanoid robot, ROBIN, is used for the assessment of personality traits in different scenarios. Sequences are labeled with the help of a psychology expert. The system shows above 90 % accuracy in the automatic assessment of personality traits.