Huang, G. orcid.org/0000-0002-0266-6987 and Moore, R.K. (Submitted: 2023) One size does not fit all: personalised affordance design for social robots. [Preprint - arXiv] (Submitted)
Abstract
Personalisation is essential to achieve more acceptable and effective results in human-robot interaction. Placing users in the central role, many studies have focused on enhancing the abilities of social robots to perceive and understand users. However, little is known about improving user perceptions and interpretation of a social robot in spoken interactions. The work described in the paper aims to find out what affects the personalisation of affordance of a social robot, namely its appearance, voice and language behaviours. The experimental data presented here is based on an ongoing project. It demonstrates the many and varied ways in which people change their preferences for the affordance of a social robot under different circumstances. It also examines the relationship between such preferences and expectations of characteristics of a social robot, like competence and warmth. It also shows that individuals have different perceptions of the language behaviours of the same robot. These results demonstrate that one-sized personalisation does not fit all. Personalisation should be considered a comprehensive approach, including appropriate affordance design, to suit the user expectations of social roles.
Metadata
Item Type: | Preprint |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Author(s). This preprint is made available under a Creative Commons Attribution 4.0 International License. (https://creativecommons.org/licenses/by/4.0/) |
Keywords: | cs.RO; cs.RO; cs.HC |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 13 Mar 2024 16:13 |
Last Modified: | 13 Mar 2024 16:20 |
Status: | Submitted |
Identification Number: | 10.48550/arXiv.2312.06566 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:210104 |