Troi-Reference-Cited by-同舟云学术

Troi

Published:2022-09-19 Issue:MHCI Volume:6 Page:1-22
ISSN:2573-0142
Container-title:Proceedings of the ACM on Human-Computer Interaction
language:en
Short-container-title:Proc. ACM Hum.-Comput. Interact.

Author:

Dissanayake Vipula¹,Tang Vanessa²,Elvitigala Don Samitha³,Wen Elliott¹,Wu Michelle¹,Nanayakkara Suranga⁴

Affiliation:

1. The University of Auckland, Auckland, New Zealand

2. University of Auckland, Aucklad, New Zealand

3. University of New South Wales, Sydney, Australia

4. National University of Singapore, Singapore, Singapore

Abstract

Emotional Self-Awareness (ESA) plays a vital role in physical and mental well-being. Recent advancements in artificial intelligence technologies have shown promising emotion recognition results, opening new opportunities to build systems to support ESA. However, little research has been done to understand users' perspectives on artificial-intelligence-based emotion recognition systems. We introduce Troi, an automatic emotion recognition mobile app using wearable signals. With Troi, we ran a multi-day user study with 12 users to understand user preference parameters, such as perceived accuracy, confidence, preferred emotion representations, effect of self-awareness of emotions, and real-time use cases. Further, we extend our study to evaluate the machine learning model in-the-wild to understand behaviours in-the-wild. We found that users perceived accuracy of the emotion recognition model is higher than the actual model prediction accuracy; there was no strong preference for one specific emotion representation, and users' self-awareness of emotions improved over time.

Funder

Tertiary Education Commission New Zealand

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)

Link

https://dl.acm.org/doi/pdf/10.1145/3546738

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