Using the Geneva Emotion Wheel to Measure Perceived Affect in Human-Robot Interaction

The ability to clearly communicate a wide range of emotional states is considered a desirable trait for social robots. This research proposes that the Geneva Emotion Wheel (GEW), a self-report instrument for measuring emotional reactions, has strong potential for use as a tool for evaluating the exp...

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Veröffentlicht in:2020 15th ACM/IEEE International Conference on Human-Robot Interaction (HRI) S. 491 - 498
Hauptverfasser: Coyne, Adam K., Murtagh, Andrew, McGinn, Conor
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: New York, NY, USA ACM 09.03.2020
Schriftenreihe:ACM Conferences
Schlagworte:
affect measurement
Design methodology
emotion
geneva emotion wheel
Human computer interaction
Human-centered computing > Human computer interaction (HCI) > HCI design and evaluation methods
Human-centered computing > Interaction design > Interaction design process and methods > User interface design
Human-centered computing > Interaction design > Systems and tools for interaction design
Human-centered computing > Visualization > Visualization techniques
Human-robot interaction
Information systems > Information retrieval > Retrieval tasks and goals > Sentiment analysis
Measurement
Statistical analysis
Stevie robot
Systematics
Wheels
human-robot interaction
stevie robot
emotion
geneva emotion wheel
affect measurement
ISBN:1450367461, 9781450367462
ISSN:2167-2148
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Beschreibung
Zusammenfassung:The ability to clearly communicate a wide range of emotional states is considered a desirable trait for social robots. This research proposes that the Geneva Emotion Wheel (GEW), a self-report instrument for measuring emotional reactions, has strong potential for use as a tool for evaluating the expression of affective content by robots. Factors that make the GEW advantageous over existing evaluation methods include: ease of administration, reduction in the importance of word labels, and coverage of "no emotion" states. Statistical analyses of the GEW are proposed, isolating quantitative metrics of emotion distinctness. An experiment requiring participants to rate the perceived emotion of a social robot was conducted, employing the proposed methods. Analysis using the GEW revealed significant differences in the reliability of different expressions to clearly convey emotional states. The GEW provided a repeatable, systematic framework for estimating perceived affect of robot expression. Thus, the results suggest the GEW offers a powerful tool for design purposes as well as analysis. To support future research using the GEW, the software used for the analysis has been packaged and made available as an open-source resource to the community.
ISBN:1450367461
9781450367462
ISSN:2167-2148
DOI:10.1145/3319502.3374834