A11yShape: AI-Assisted 3-D Modeling for Blind and Low-Vision Programmers
Name
3663547.3746362.pdf
Size
7.13 MB
Format
Adobe PDF
Checksum (MD5)
52a8879edb82cf893f5e71feb8d5e7e1
Author(s)
Zhang, Zhuohao (Jerry)
Li, Haichang
Yu, Chun Meng
Faruqi, Faraz
Xie, Junan
Kim, Gene
Fan, Mingming
Forbes, Angus
Wobbrock, Jacob
Guo, Anhong
Date Issued
October 22, 2025
Publisher
ACM|The 27th International ACM SIGACCESS Conference on Computers and Accessibility
Citation
Zhuohao (Jerry) Zhang, Haichang Li, Chun Meng Yu, Faraz Faruqi, Junan
Xie, Gene S-H Kim, Mingming Fan, Angus Forbes, Jacob O. Wobbrock,
Anhong Guo, and Liang He. 2025. A11yShape: AI-Assisted 3-D Modeling
for Blind and Low-Vision Programmers. In The 27th International ACM
SIGACCESS Conference on Computers and Accessibility (ASSETS ’25), October
26–29, 2025, Denver, CO, USA. ACM, New York, NY, USA, 20 pages.
Version
Final published version
Abstract
Building 3-D models is challenging for blind and low-vision (BLV) users due to the inherent complexity of 3-D models and the lack of support for non-visual interaction in existing tools. To address this issue, we introduce A11yShape, a novel system designed to help BLV users who possess basic programming skills understand, modify, and iterate on 3-D models. A11yShape leverages LLMs and integrates with OpenSCAD, a popular open-source editor that generates 3-D models from code. Key functionalities of A11yShape include accessible descriptions of 3-D models, version control to track changes in models and code, and a hierarchical representation of model components. Most importantly, A11yShape employs a cross-representation highlighting mechanism to synchronize semantic selections across all model representations—code, semantic hierarchy, AI description, and 3-D rendering. We conducted a multi-session user study with four BLV programmers, where, after an initial tutorial session, participants independently completed 12 distinct models across two testing sessions, achieving results that aligned with their own satisfaction. The result demonstrates that participants were able to comprehend provided 3-D models, as well as independently create and modify 3-D models—tasks that were previously impossible without assistance from sighted individuals.
Description
ASSETS ’25, Denver, CO, USA
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3663547.3746362
