A BML Based Embodied Conversational Agent for a Personality Detection Program

This paper presents a project in which an Embodied Conversational Agent (ECA) attemtps to detect the personality of the user by asking him (or her) a series of questions. The project uses the Elckerlyc platform, a Behavior Markup Language (BML) compliant behavior realizer for ECAs [1]. BML allows the design and implementation of verbal and nonverbal behaviors in an abstract way, without reference to the ECA model in question. This means the designer only needs to decide “what‿ kind of behaviors should be performed by the ECA and to specify “when‿ these behaviors should be performed, without needing to know how the realization engine actually displays these behaviors on the ECA’s embodiment. The aim of this research was to extend the Psychometer [2], a text based dialogue system for personality detection, with a virtual embodiment that uses gaze behavior and facial expressions. The Psychometer asks the user questions, adapted from an existing questionnaire, until it has enough answers to classify the user’s personality according to the well-known Big Five theory of personality traits.