Managing emotional dialogue for a virtual cancer patient: a schema-guided approach

Abstract

In this paper, we describe a general-purpose dialogue management framework used to design SOPHIE (Standardized Online Patient for Healthcare Interaction Education). SOPHIE simulates a virtual standardized cancer patient that allows physicians to practice skills such as empathy and patient empowerment in end-of-life communication. To provide the user with an opportunity to practice these skills, SOPHIE must produce a natural, emotionally appropriate conversation, yet handle topic shifts and open-ended questions from the user. To accomplish this, our approach to dialogue management loosely followsschemas– explicit representations of thetypicalflows of dialogue in end-of-life communication – while also using flexible pattern-driven methods for interpretation and generation. We conduct a crowdsourced evaluation of conversations between medical students and SOPHIE. Our agent is judged to produce responses that are natural, emotionally appropriate, and consistent with her role as a cancer patient. Furthermore, it significantly outperforms an end-to-end neural model fine-tuned on a human standardized patient corpus, attesting to the advantages of a schema-guided approach in this domain. However, the system is currently limited in its ability to generate responses that are judged to demonstrate deep understanding of the user, suggesting that future work should place focus on integrating this framework with robust natural language understanding and commonsense reasoning methods.