Attention Estimation for Child-Robot Interaction.

In this paper, we present a method of estimating a child's attention, one of the more important human mental states, in a free-play scenario of child-robot interaction. First, we developed a system that could sense a child's verbal and non- verbal multimodal signals such as gaze, facial expression, proximity, and so on. Then, the observed information was used to train a Support Vector Machine (SVM) to estimate a human's attention level. We investigated the accuracy of the proposed method by comparing with a human judge's estimation, and obtained some promising results which we discuss here.