ACCSAMS：考试文档自动转换为盲人和视障人士可访问学习材料
ACCSAMS: Automatic Conversion of Exam Documents to Accessible Learning Material for Blind and Visually Impaired
AI总结：
针对考试文档对盲人和视障学生造成的可访问性障碍，提出半自动系统ACCSAMS，通过布局优化、导航结构和替代文本增强可访问性，并构建多语言标注数据集。
摘要：
考试文档是备考的重要教育材料。然而，它们对盲人和视障学生构成了重大的学术障碍，因为这些文档通常在创建时未考虑可访问性。通常，这些文档与屏幕阅读器不兼容，包含过多空白，并且缺乏视觉元素的替代文本。这种情况经常需要经验丰富的视力正常人士介入，以修改格式和内容以实现可访问性。我们提出了ACCSAMS，一个半自动系统，旨在增强考试文档的可访问性。我们的系统提供了三个关键贡献：（1）创建可访问的布局并移除不必要的空白，（2）添加导航结构，以及（3）为之前缺失的视觉元素加入替代文本。此外，我们提出了首个多语言人工标注数据集，包含1,293份德语和900份英语考试文档，这些文档可以作为深度学习模型的良好训练来源。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
