This paper introduces a software pipeline that leverages AI to automatically generate 3D-printable tactile graphs, significantly improving accessibility to statistical data for blind and low-vision students.

In plain terms

Statistical graphs are typically visual, making them difficult for blind and low-vision students to understand. While 3D-printed tactile graphs allow these students to 'feel' and interpret data, their creation has been limited due to the specialized skills and manual effort required to design each graph. To solve this, researchers developed a three-layer software pipeline written in JavaScript that automates the entire process. The first two layers use tactile perception research and modular builders for common chart types (like bar and scatter plots) to design the graphs. The crucial third layer utilizes a large language model (LLM), an advanced AI, to extract chart specifications directly from an uploaded image of a graph, though a teacher must review it before printing. This pipeline can generate print-ready 3D files in less than 250 milliseconds, making accessible educational materials much faster and easier to produce.