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Ontologies and Open Data for Enriching Personalized Social Moments in Human Robot Interaction

Cristina Gena, Rossana Damiano, Claudio Mattutino, Alessandro Mazzei, Stefania Brighenti, Matteo Nazzario, Andrea Meirone, Camilla Quarato, Elisabetta Miraglio, Giulia Ricciardiello, Francesco Petriglia, Federica Liscio, Giuseppe Piccinni, Loredana Mazzotta, Cesare Pecone, Valeria Ricci

Year
2022
Citations
3

Abstract

This paper describes our proposal for enriching personalized social moments and dialogues between human and robot in the context of the Sugar, Salt & Pepper laboratory. The lab focused on the use of the Pepper robot in a therapeutic context to promote autonomies and functional acquisitions in highly functioning (Asperger) children with autism. This paper is focused on a post-hoc work aimed at improving the robot's autonomous dialogue strategies. In particular we are integrating the robot's dialogue with a knowledge base to have the robot able to move and reason on an ontology, and thus enriching its dialogue's strategies. For instance, the taxonomic structure of the ontology could allow Pepper to drive the focus of the conversation to related topics or to more general or specific topics, and, in general, it could improve its capability to manage the conversation and disambiguate the input from the user.

Keywords

ConversationOntologyComputer scienceHuman–computer interactionContext (archaeology)RobotHuman–robot interactionArtificial intelligenceMobile robotSocial robot

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