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AI Assisted ePub & Content Remediation: Enhancing Accessibility with Large Language Models

taught by: Christine Foushi

Session Summary

In today's digital age, ePubs and content have become essential tools for disseminating information and knowledge. However, ensuring these platforms are accessible to all users, including those with disabilities, remains a challenge.


Explore how Large Language Models (LLMs) can be trained on the latest accessibility standards to remediate ePubs and content. Bring your experiences to learn together and explore several examples of how AI can assist including image to accessible HTML tables, image contextual alt text, table remediation, image to MathML, automated content conversion (e.g., LateX to MathML), and automatic meta text generation. Leveraging these technologies will enhance content making it more inclusive and user-friendly for all and provide insights into the potential of AI-assisted remediation and its impact on the future of digital accessibility.

Practical Skills

  • Gain insights into AI on the future of digital accessibility and the potential for advancements.
  • Understand the challenges of digital accessibility for ePubs and content.
  • Uncover pros and cons of AI.