Modeling the Emotional State of Computer Users

We describe the structure of a Bayesian network designed to monitor the behavior of a user interacting with a conversational computer and use that information to estimate the user’s emotional state. Our model of emotional state uses two discrete dimensions, valence (bad to good) and arousal (calm to excited), to capture the dominant aspects of physical emotional response. Emotion is expressed behaviorally in a variety of ways, including by linguistic choices, qualities of vocal expression, and movement. In this paper, we focus on vocal expression, and its correlation with emotional state, using the psychological literature to suggest the appropriate parameterization of our Bayesian model.