Empathetic Robots Using Empathy Classifiers in HRI Settings

Abstract

Empathy is a vital part of human social interaction. It mediates emotional interaction and allows for increased rapport between individuals. We explore combining multi-modal empathy classifiers and empathetic text generation in a human-robot interaction setting. In particular, we designed a demo that uses the Haru social robot to engage in empathetic conversations with a human. We use our classifier to assess the empathy level of the user and the robot. The user's score is a metric for their experience with the robot. On the other hand, we use the robot's score to ensure highly empathetic behaviors. Our preliminary results with two participants show that our system can generate empathetic responses that we can adapt according to the user's empathy level.