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Can Robots Impact Human Comfortability During a Live Interview?

Authors: Lechuga Redondo M. E.; Sciutti A.; Incao S.; Rea F.; Niewiadomski R.;

Can Robots Impact Human Comfortability During a Live Interview?

Abstract

Interaction among humans does not always proceed without errors; situations might happen in which a wrong word or attitude can cause the partner to feel uneasy. However, humans are often very sensitive to these interaction failures and may be able to fix them. Our research aims to endow robots with the same skill. Thus the first step, presented in this short paper, investigates to what extent a humanoid robot can impact someone's Comfortability in a realistic setting. To capture natural reactions, a set of real interviews performed by the humanoid robot iCub (acting as the interviewer) were organized. The interviews were designed in collaboration with a journalist from the press office of our institution and are meant to appear on the official institutional online magazine. The dialogue along with fluent human-like robotic actions were chosen not only to gather information about the participants' personal interests and professional career, necessary for the magazine column, but also to influence their Comfortability. Once the experiment is completed, the participants' self-report and spontaneous reactions (physical and physiological cues) will be explored to tackle the way people's Comfortability may be manifested through non-verbal cues, and the way it may be impacted by the humanoid robot.

Country
Italy
Keywords

Comfortability, Human-Robot Social Interaction, Affective Com- puting, Humanoid Robot, Affective computing; Comfortability; Human-robot social interaction; Humanoid robot

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selected citations
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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).
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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.
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