Improving Quality of Life with a Narrative Robot Companion: II – Creating Group Cohesion via Shared Narrative Experience

Abstract

One of the most difficult things for social robots is to enter the realm of human social relations. Here, we exploit recent advances in natural language processing (NLP) that provide robots access to human experience, which can allow them to enter into human social relations. When people are put together in arbitrary conditions, as in a home for the elderly, it can be difficult for them to share experience. To address this, we use recent advances in NLP to allow the robot to discover shared narratives between such group members. Our narrative companion extends the human capability to make social narrative links for building group coherence through sharing experience.Requirements are identified for a narrative companion to allow individuals within a group to focus their interactions on shared experiences and interests, to improve group coherence. The system should collect and organize members’ experiences, and should discover semantic similarity between different members’ experiences in order to create a group narrative. It should then accompany the group in their cohesion-enhancing experience of this narrative. Based on these requirements, and extending our previous work, we implement the V2.0 narrative companion on the Pepper robot.The system is validated in a case study where participants provide 5 favorite photographs and short answers to questions. The Narrative Semantic Similarity Analysis System (NarSim) generates a meaningful trajectory of narrative linking people and events depicted in the photographs. With this, Pepper then accompanies the group and prompts group members to enrich the shared narrative, to further enhance the group pleasure and cohesion. Results are presented, and future applications for improved quality of life are discussed.