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Learning communication from first- and third-person POVs: how perceptual differences influence the interpretation of conversations whilst waiting

  • Sutasinee ThovuttikulEmail author
  • Yoshimasa Ohmoto
  • Toyoaki Nishida
Article
  • 25 Downloads

Abstract

The difficulties and social anxiety associated with living in unfamiliar places are often caused by different patterns of thinking, points of view (POVs) and physical styles. Learning to communicate better will help us understand that differences are normal, and that life can be lived in harmony. We study herein how participants learn and understand different behavioural patterns during interactions using experiments on perceived communication differences in first- and third-person POVs for simulated crowds. In our experiment, participants interact with autonomous agents and experimenters via avatars in a shared virtual space. We ask the participants to obtain multiple tickets from two service counters in the system. The virtual service avatar provides a ticket upon request. One or more autonomous customer agents then navigate the system to obtain the ticket. If a service counter is already occupied, other customers must wait in accordance with the “first-come, first-serve” rule. The fairness-of-waiting behaviour is interpreted using two features to understand the perceptual differences of varying perspectives: waiting styles (i.e. line and group waiting) and fairness (i.e. fair and unfair services). Participants with differing perspectives focus on different features whilst waiting. An analysis of variance of reactions and reasoning demonstrates that the participants in the first-person group tend to focus on interaction and feelings whilst waiting, whereas participants in the third-person group emphasised fairness.

Keywords

Communication learning system First- and third-person points of view (POVs) Perception of conversation Fairness of waiting Simulated crowd 

Notes

Acknowledgements

This research was supported by the RIKEN Center for Advanced Intelligence Project as part of the “Human–AI Communication project”.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Intelligence Science and Technology, Graduate School of InformaticsKyoto UniversityKyotoJapan
  2. 2.RIKEN Center for Advanced Intelligence ProjectTokyoJapan

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