Memory-Based Personalization for Fostering a Long-Term Child-Robot Relationship

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Abstract

After the novelty effect wears off children need a new motivator to keep interacting with a social robot. Enabling children to build a relationship with the robot is the key for facilitating a sustainable long-term interaction. We designed a memory-based personalization strategy that safeguards the continuity between sessions and tailors the interaction to the child's needs and interests to foster the child-robot relationship. A longitudinal (five sessions in two months) user study (N = 46, 8-10 y.o) showed that the strategy kept children interested longer in the robot, fosters more closeness, elicits more positive social cues, and adds continuity between sessions.

Original languageEnglish
Title of host publication2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI)
Subtitle of host publication[Proceedings]
PublisherIEEE Computer Society
Pages80-89
Number of pages10
ISBN (Electronic)9781665407311
ISBN (Print)9781665407328
DOIs
Publication statusPublished - 29 Sept 2022
Event17th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2022 - Sapporo, Japan
Duration: 7 Mar 202210 Mar 2022

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
NumberMarch
Volume2022
ISSN (Electronic)2167-2148

Conference

Conference17th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2022
Country/TerritoryJapan
CitySapporo
Period7/03/2210/03/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • child-robot interaction
  • long-term
  • longitudinal user study
  • memory
  • personal-ization
  • social robots

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