Automated Text Simplification for the Task Guidance in Augmented Reality
Guande Wu, Jing Qian, Sonia Castelo, Shaoyu Chen, João Rulff, Claudio T. Silva · 2023
Text presentation in augmented reality (AR) poses unique challenges due to the limited field of view, small display regions, and occlusion of the environment. In this study, we explore and address challenges in presenting text in augmented reality (AR) by exploring text simplification methods. We propose an automatic text simplification approach called TSimer for AR, improving text presentation and user performance. We conducted an expert interview to aid the development of our method. The resulting system/method is evaluated with a user study with 16 participants and demonstrated the advantages over traditional methods on user’s cognitive load and performance. Our work further bridges the gap for automatically optimizing batch text data into AR for readability and overall performance.