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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.<\/jats:p>","DOI":"10.1145\/3546738","type":"journal-article","created":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T23:14:30Z","timestamp":1663715670000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Troi"],"prefix":"10.1145","volume":"6","author":[{"given":"Vipula","family":"Dissanayake","sequence":"first","affiliation":[{"name":"The University of Auckland, Auckland, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vanessa","family":"Tang","sequence":"additional","affiliation":[{"name":"University of Auckland, Aucklad, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Don Samitha","family":"Elvitigala","sequence":"additional","affiliation":[{"name":"University of New South Wales, Sydney, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elliott","family":"Wen","sequence":"additional","affiliation":[{"name":"The University of Auckland, Auckland, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michelle","family":"Wu","sequence":"additional","affiliation":[{"name":"The University of Auckland, Auckland, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suranga","family":"Nanayakkara","sequence":"additional","affiliation":[{"name":"National University of Singapore, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,9,20]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Insights From Longitudinal Evaluation of Moodie Mental Health App. In CHI Conference on Human Factors in Computing Systems Extended Abstracts","author":"Alslaity Alaa","year":"2022","unstructured":"Alaa Alslaity , Gerry Chan , Rita Orji , and Richard Wilson . 2022 . 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