Hey Haru, Let's Be Friends! Using the Tiers of Friendship to Build Rapport through Small Talk with the Tabletop Robot Haru

Conversation can play an essential role in forging bonds between humans and social robots, but participants need to feel like they are being listened to, remembered, and cared about in order to effectively build rapport. In this paper, we propose a novel strategy for conducting small talk with a social robot. Our approach is known as the Tiers of Friendship. It is centered around three core design elements: 1) Persuasive content and character is provided through topic modules created by professional creative writers to ensure engaging conversational content and a compelling personality for the social robot. 2) Conversational memory is achieved by allowing topic modules to specify required information that can be learned through conversation or recalled from previous interactions and organizing topic modules into a hierarchy that enforces information requirements between topics. 3) Dynamicity in conversation is promoted through topic navigation that supports fluid transitions to topics of human interest and employs elements of random ordering to create fresh conversation experiences. In this paper, we show how the Tiers of Friendship can be used to generate conversation content for a social robot that encourages the development of rapport. We describe a working implementation of a small talk system for a social robot based on the Tiers of Friendship that combines off-the-shelf ASR and NLU components and custom robot behavior components implemented via behavior trees on ROS. Finally, in order to evaluate our approach's effectiveness, we conduct an elicitation survey that evaluates conversations in terms of perceived engagement, personality traits, and rapport expectation and discuss the implications for social robotics.

I. Introduction

Rapport is “a warm, relaxed relationship of mutual under-standing, acceptance, and sympathetic compatibility between or among individuals” [31]. Its development is a crucial step in supporting successful long term interactions between humans and robots. Robotics researchers have sought to support rapport with robots through nonverbal cues, such as gesture mimicry [28], and with verbal cues, including the robot's backstory and emulation of children's verbalizations [18]. Another verbal mode of developing rapport that deserves further attention is the robot's ability to personalize its conversations based on previous interactions with the user, a form of behavioral adaptation shown in prior studies to improve users' perceptions and attitudes toward robots [19].