Automatic modeling of personality states in small group interactions.

In this paper, we target the automatic recognition of personality states in a meeting scenario employing visual and acoustic features. The social psychology literature has coined the name personality state to refer to a specific behavioral episode wherein a person behaves as more or less introvert/extrovert, neurotic or open to experience, etc. Personality traits can then be reconstructed as density distributions over personality states. Different machine learning approaches were used to test the effectiveness of the selected features in modeling the dynamics of personality states.