@inproceedings{c7733e5ff06f42ec8c6a55e1186d954c,
title = "SARA: Smart AI Reading Assistant for Reading Comprehension",
abstract = "SARA integrates Eye Tracking and state-of-the-art large language models in a mixed reality framework to enhance the reading experience by providing personalized assistance in real-time. By tracking eye movements, SARA identifies the text segments that attract the user's attention the most and potentially indicate uncertain areas and comprehension issues. The process involves these key steps: text detection and extraction, gaze tracking and alignment, and assessment of detected reading difficulty. The results are customized solutions presented directly within the user's field of view as virtual overlays on identified difficult text areas. This support enables users to overcome challenges like unfamiliar vocabulary and complex sentences by offering additional context, rephrased solutions, and multilingual help. SARA's innovative approach demonstrates it has the potential to transform the reading experience and improve reading proficiency.",
keywords = "Augmented Reality, Eye tracking, Large Language Models, Reading Comprehension",
author = "Enkeleda Thaqi and Mantawy, {Mohamed Omar} and Enkelejda Kasneci",
note = "Publisher Copyright: {\textcopyright} 2024 Owner/Author.; 16th Annual ACM Symposium on Eye Tracking Research and Applications, ETRA 2024 ; Conference date: 04-06-2024 Through 07-06-2024",
year = "2024",
month = jun,
day = "4",
doi = "10.1145/3649902.3655661",
language = "English",
series = "Eye Tracking Research and Applications Symposium (ETRA)",
publisher = "Association for Computing Machinery",
editor = "Spencer, {Stephen N.}",
booktitle = "Proceedings - ETRA 2024, ACM Symposium on Eye Tracking Research and Applications",
}