Evaluating a Spoken Dialogue System that Detects and Adapts to User Affective States

We present an evaluation of a spoken dialogue system that detects and adapts to user disengagement and uncertainty in real-time. We compare this version of our system to a version that adapts to only user disengagement, and to a version that ig-nores user disengagement and uncertainty entirely. We find a significant increase in task success when comparing both affect-adaptive versions of our system to our non-adaptive baseline, but only for male users.