All Meet: Accessibility Enhancement Project

The All Meet platform was designed to address the communication challenges faced by students and professionals with disabilities, including hearing, visual, cognitive, and physical impairments.

This project was part of my coursework in Accessibility and Assistive Technology, where I applied user-centered design principles and WCAG 2.1 guidelines to create a solution that enhances communication for students and professionals. The platform supports multiple devices, ensuring inclusivity for all users.

I conducted interviews and created personas to understand the specific challenges faced by users with disabilities. User research revealed issues like poor captioning, incompatible screen readers, and complex navigation. These barriers hindered effective communication for users with disabilities. Existing platforms lacked comprehensive accessibility features.

The problem was addressed through iterative design and user testing. Data analysis helped identify key pain points of the users with disabilities. Such as poor captioning, incompatible screen readers, and complex navigation in existing platforms. After testing of the platform I analyzed user feedback and task completion times during usability testing to identify areas for improvement. Based on the user feedback and testing iterations was done.

After conducting usability testing with participants (including users with disabilities), I identified key areas for improvement and iterated on the design to enhance accessibility and usability.

Based on user feedback, I made key improvements to All Meet, including a resizable AI sign language window, speech-to-text in chats, and enhanced live captions. These changes addressed issues like small sign language windows, overlapping captions, and typing difficulties, making the platform more inclusive and user-friendly for individuals with disabilities.