Year: 2023
Type: article
Abstract: An interesting application for social robots is to act as a presenter, for example as a museum guide. In this paper, we present a fully automated system architecture for building adaptive presentations for embodied agents. The presentation is generated from a knowledge graph, which is also used to track the grounding state of information, based on multimodal feedback from the user. We introduce a novel way to use large-scale language models (GPT-3 in our case) to lexicalise arbitrary knowledge graph triples, greatly simplifying the design of this aspect of the system. We also present an evaluation where 43 participants interacted with the system. The results show that users prefer the adaptive system and consider it more human-like and flexible than a static version of the same system, but only partial results are seen in their learning of the facts presented by the robot.
Authors: Axelsson, Agnes, Skantze, Gabriel
Institution: KTH Royal Institute of Technology
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
Funder: Energimyndigheten
Award: G1504529383
OpenAlex ID: W7055723780