An AI Guide to Enhance Accessibility of Social Virtual Reality for Blind People
Jazmin Collins, Kaylah Myranda Nicholson, Yusuf Khadir, Andrea Stevenson Won, Shiri Azenkot

TL;DR
This paper presents an AI-powered guide designed to improve accessibility in social VR for blind and low vision users by providing customizable guidance and visual interpretation features.
Contribution
The paper introduces a novel AI guide with multiple personas and functionalities to address limitations of human guides in social VR for BLV users.
Findings
AI guide offers six customizable personas for diverse user needs.
The guide provides visual interpretation and navigation assistance.
Future work includes understanding BLV user preferences.
Abstract
The rapid growth of virtual reality (VR) has led to increased use of social VR platforms for interaction. However, these platforms lack adequate features to support blind and low vision (BLV) users, posing significant challenges in navigation, visual interpretation, and social interaction. One promising approach to these challenges is employing human guides in VR. However, this approach faces limitations with a lack of availability of humans to serve as guides, or the inability to customize the guidance a user receives from the human guide. We introduce an AI-powered guide to address these limitations. The AI guide features six personas, each offering unique behaviors and appearances to meet diverse user needs, along with visual interpretation and navigation assistance. We aim to use this AI guide in the future to help us understand BLV users' preferences for guide forms and…
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