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Responding to uncertainty in emotion recognition

Björn Schuller (Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Augsburg, Germany and GLAM – Group on Language, Audio and Music, Imperial College London, London, UK)

Journal of Information, Communication and Ethics in Society

ISSN: 1477-996X

Article publication date: 4 September 2019

Issue publication date: 17 September 2019




Uncertainty is an under-respected issue when it comes to automatic assessment of human emotion by machines. The purpose of this paper is to highlight the existent approaches towards such measurement of uncertainty, and identify further research need.


The discussion is based on a literature review.


Technical solutions towards measurement of uncertainty in automatic emotion recognition (AER) exist but need to be extended to respect a range of so far underrepresented sources of uncertainty. These then need to be integrated into systems available to general users.

Research limitations/implications

Not all sources of uncertainty in automatic emotion recognition (AER) including emotion representation and annotation can be touched upon in this communication.

Practical implications

AER systems shall be enhanced by more meaningful and complete information provision on the uncertainty underlying their estimates. Limitations of their applicability should be communicated to users.

Social implications

Users of automatic emotion recognition technology will become aware of their limitations, potentially leading to a fairer usage in crucial application context.


There is no previous discussion including the technical view point on extended uncertainty measurement in automatic emotion recognition.



Schuller, B. (2019), "Responding to uncertainty in emotion recognition", Journal of Information, Communication and Ethics in Society, Vol. 17 No. 3, pp. 299-303.



Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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