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Discovering SOCIABLE: Using a Conceptual Model to Evaluate the Legibility and Effectiveness of Backchannel Cues in an Entertainment Scenario

Authors: Antonio Andriella; Rubén Huertas-García; Santiago Forgas-Coll; Carme Torras; Guillem Alenyà;

Discovering SOCIABLE: Using a Conceptual Model to Evaluate the Legibility and Effectiveness of Backchannel Cues in an Entertainment Scenario

Abstract

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Robots are expected to become part of everyday life. However, while there have been important breakthroughs during the recent decades in terms of technological advances, the ability of robots to interact with humans intuitively and effectively is still an open challenge. In this paper, we aim to evaluate how humans interpret and leverage backchannel cues exhibited by a robot which interacts with them in an entertainment context. To do so, a conceptual model was designed to investigate the legibility and the effectiveness of a designed social cue, called SOCial ImmediAcy BackchanneL cuE (SOCIABLE), on participant’s performance. In addition, user’s attitude and cognitive capability were integrated into the model as an estimator of participants’ motivation and ability to process the cue. In working toward such a goal, we conducted a two-day long user study (N=114) at an international event with untrained participants who were not aware of the social cue the robot was able to provide. The results showed that participants were able to perceive the social signal generated from SOCIABLE and thus, they benefited from it. Our findings provide some important insights for the design of effective and instantaneous backchannel cues and the methodology for evaluating them in social robots. This work has been partially funded by the EU project SOCRATESH2020-MSCA-ITN-721619, by the European Union ́s Horizon 2020 underERC Advanced Grant CLOTHILDE (no. 741930), by the Spanish Ministryof Science and Innovation HuMoUR TIN2017-90086-R, and by the StateResearch Agency through the Mar ́ıa de Maeztu Seal of Excellence to IRI(MDM-2016-0656). Peer Reviewed

Country
Spain
Keywords

Àrees temàtiques de la UPC::Informàtica::Robòtica, Service robots, Social aspects of automation, Classificació INSPEC::Automation::Robots, Intelligent robots, :Automation::Robots [Classificació INSPEC], Humanoid robots, :Informàtica::Robòtica [Àrees temàtiques de la UPC]

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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