Demonstration of AI-Powered Accessibility Auditing TPAC Breakout Session Recording

Good morning, everyone. I’m excited to share our Demonstration of AI-Powered Accessibility Auditing TPAC Breakout Session Recording: https://www.helixopp.com/ottitor-demo/index.html
In the video our Helix Opportunity Product Manager, Neha Jadhav, explains how we have automated the use of real artificial intelligence to identify complex accessibility issues that would otherwise require tedious manual intervention. Rather than feeding our own internal documentation to an LLM (Large Language Model) we leverage documentation from every corner of the World Wide Web. We employ a combined technique that includes global LLM’s, Natural Language Processing, prompt engineering, machine learning, optical character recognition, and much more. We talk about how Ottitor takes a classical, yet modern, approach to AI that empowers our accessibility auditing tool as a rule based expert, Explainable AI, system to give users super human auditing capabilities.

If you find this interesting, please watch the video. We are happy to receive any feedback.

The TPAC Session Submission details are below:

Session description

This session will demonstrate how Artificial Intelligence can be used for a number of accessibility analysis tasks in natural language processing, image understanding and design evaluation.

Session goal

Demonstrate the power of AI-driven rule engines to enhance accessibility auditing capabilities and reduce the need for manual auditing efforts.

Agenda for the meeting.

Share & Discuss Current Implementation:

  *   Abbreviations
  *   Idioms and Phrases
  *   Text from Images
  *   Localization
  *   Language and Context Analysis (Link Titles)
Future Implementation

  *   Screen Recording Analysis
  *   Video/Audio File Analysis
  *   Image Analysis
  *   Pattern and Relationship Recognition
  *   Dynamic Content Analysis


David Fazio



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