Information provision-timing control for informational assistance robot

This paper proposes a HMM-based user's information demand estimation model for autonomous informational assistance robots to avoid providing information prematurely. The model estimates the user's implicit information demands by predicting a user's next information request using user's head movements. Through a word-association quiz-dialog experiment, our model demonstrated superior prediction performance over the usual HMM-based classifier.