Exam documents are essential educational materials for exam preparation. However, they pose a significant academic barrier for blind and visually impaired students, as they are often created without accessibility considerations. Typically, these documents are incompatible with screen readers, contain excessive white space, and lack alternative text for visual elements. This situation frequently requires intervention by experienced sighted individuals to modify the format and content for accessibility. We propose ACCSAMS, a semi-automatic system designed to enhance the accessibility of exam documents. Our system offers three key contributions: (1) creating an accessible layout and removing unnecessary white space, (2) adding navigational structures, and (3) incorporating alternative text for visual elements that were previously missing. Additionally, we present the first multilingual manually annotated dataset, comprising 1,293 German and 900 English exam documents which could serve as a good training source for deep learning models.

提出了一个名为ACCSAMS的半自动系统，用于提高考试文档的可访问性。该系统通过创建可访问的布局、去除不必要的空白、添加导航结构以及补充以前缺失的视觉元素的替代文本，解决了盲人和视障学生面临的学术障碍。此外，还提供了一个包括1,293份德语和900份英语考试文档的多语言手动标注数据集，可作为深度学习模型的良好训练来源。

ACCSAMS：自動將考試文件轉換為盲人和視覺障礙者可接觸的學習資料