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The attribution of emotional state: How embodiment features and social traits affect the perception of an artificial agent
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. (Uppsala Social Robotics Lab)
Univ Paris Saclay, Telecom ParisTech, LTCI, F-75013 Paris, France.
Sorbonne Univ, Inst Syst Intelligents & Robot, CNRS, UMR7222, Paris, France.
Sorbonne Univ, Inst Syst Intelligents & Robot, CNRS, UMR7222, Paris, France.
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2018 (English)In: Proc. 27th International Symposium on Robot and Human Interactive Communication, IEEE, 2018, p. 495-502Conference paper, Published paper (Refereed)
Abstract [en]

Understanding emotional states is a challenging task which frequently leads to misinterpretation even in human observers. While the perception of emotions has been studied extensively in human psychology, little is known about what factors influence the human perception of emotions in robots and virtual characters. In this paper, we build on the Brunswik lens model to investigate the influence of (a) the agent's embodiment using a 2D virtual character, a 3D blended embodiment, a recording of the 3D platform and a recording of a human, as well as (b) the level of human-likeness on people's ability to interpret emotional facial expressions in an agent. In addition, we measure social traits of the human observers and analyze how they correlate to the success in recognizing emotional expressions. We find that interpersonal differences play a minor role in the perception of emotional states. However, both embodiment and human-likeness as well as related perceptual dimensions such as perceived social presence and uncanniness have an effect on the attribution of emotional states.

Place, publisher, year, edition, pages
IEEE, 2018. p. 495-502
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:uu:diva-398384DOI: 10.1109/ROMAN.2018.8525700ISI: 000494315600079ISBN: 978-1-5386-7980-7 (electronic)OAI: oai:DiVA.org:uu-398384DiVA, id: diva2:1375659
Conference
RO-MAN 2018, August 27–31, Nanjing, China
Available from: 2018-11-08 Created: 2019-12-05 Last updated: 2019-12-10Bibliographically approved

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Paetzel, MaikeCastellano, Ginevra

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