Extended Reality Accessibility & Inclusion

We present VRSight, an end-to-end system that recognizes VR scenes post hoc through a set of AI models (e.g., object detection, depth estimation, LLM-based atmosphere interpretation) and generates tone-based, spatial audio feedback, empowering blind users to interact in VR without developer intervention.

Our work aim to advance the avatar design practices by delivering a set of centralized, comprehensive, and validated design guidelines that are easy to adopt, disseminate, and update. Through a systematic literature review and interview with 60 participants with various disabilities, we derived 20 initial design guidelines that cover diverse disability expression methods through five aspects, including avatar appearance, body dynamics, assistive technology design, peripherals around avatars, and customization control. We further evaluated the guidelines via a heuristic evaluation study with 10 VR practitioners, validating the guideline coverage, applicability, and actionability. Our evaluation resulted in a final set of 17 design guidelines with recommendation levels.

We interviewed 13 transgender and gender-nonconforming users of social VR platforms, focusing on their experiences with and without voice changers to explore the connection between avatar embodiment and voice representation (Povinelli and Zhao 2024).

We conducted a diary study with 10 People with Disabilities who freely explored VRChat for two weeks, comparing their experiences between using regular avatars and avatars with disability signifiers (i.e., avatar features that indicate the user’s disability in real life) (Zhang et al. 2023).

We investigated XR developers' practices, challenges, and needs when integrating accessibility in their projects (Ji et al. 2023).

We explored people with disabilities’ avatar perception and disability disclosure preferences in social VR by (1) conducting a systematic review of fifteen popular social VR applications to evaluate their avatar diversity and accessibility support and (2) interviewing 19 participants with different disabilities to understand their avatar experiences (Zhang et al. 2022).

We designed VRBubble, an audio-based VR technique that provides surrounding avatar information based on social distances. Based on Hall’s proxemic theory, VRBubble divides the social space with three Bubbles—Intimate, Conversation, and Social Bubble—generating spatial audio feedback to distinguish avatars in different bubbles and provide suitable avatar information (Ji, Cochran, and Zhao 2022).