Facial expression recognition (FER) has emerged as a promising approach to the development of emotion-aware intelligent systems. The performance of FER in multiple domains is continuously being improved, especially through advancements in data-driven learning approaches. However, a key challenge remains in utilizing FER in real-world contexts, namely ensuring user understanding of these systems and establishing a suitable level of user trust towards this technology. We conducted an empirical user study to investigate how explanations of FER can improve trust, understanding and performance in a human-computer interaction task that uses FER to trigger helpful hints during a navigation game. Our results showed that users provided with explanations of the FER system demonstrated improved control in using the system to their advantage, leading to a significant improvement in their understanding of the system, reduced collisions in the navigation game, as well as increased trust towards the system.
@article{arxiv.2410.09743,
title = {"I think you need help! Here's why": Understanding the Effect of Explanations on Automatic Facial Expression Recognition},
author = {Sanjeev Nahulanthran and Mor Vered and Leimin Tian and Dana Kulić},
journal= {arXiv preprint arXiv:2410.09743},
year = {2024}
}
Comments
8 pages, Submitted and Accepted to the ACII2024 conference