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AltAuthor: A Context-Aware Alt Text Authoring Tool with Image Classification and LMM-Powered Accessibility Compliance

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Authors

Song, Hyungwoo; Shin, Minjeong; Kim, Yeonjoon; Jang, Kyochul; Choi, Jaehoon; Jung, Hyunggu; Suh, Bongwon

Issue Date
2025
Publisher
Association for Computing Machinery
Citation
International Conference on Intelligent User Interfaces, Proceedings IUI, pp.124-128
Abstract
Web accessibility remains a persistent challenge, particularly in providing appropriate alternative text (alt text) for images that meet the needs of people with visual impairments. Existing tools often generate generic descriptions without taking into account image types and webpage context, leading to alt text that fails to align with established accessibility guidelines. To overcome these limitations, we present AltAuthor, an authoring tool designed to assist developers in managing alt text on existing websites. AltAuthor consists of three key components: (1) Image Classifier, which identifies visual content and its type, (2) Alt Text Generator, leveraging a Large Multimodal Model to generate compliant descriptions by incorporating identified image type, webpage context, and Section 508 accessibility guidelines, and (3) Interactive Authoring Interface, allowing developers to customize automated suggestions. Through this integrated approach, AltAuthor provides developers with tools to enhance accessibility management.
URI
https://hdl.handle.net/10371/217819
DOI
https://doi.org/10.1145/3708557.3716366
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  • College of Nursing
  • Dept. of Nursing
Research Area Artificial Intelligence, Health Informatics, Human-Computer Interaction, 보건의료정보학, 인간컴퓨터상호작용, 인공지능

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