Project Description

2022–Present
Voice assistants (VAs) like Siri and Alexa have transformed how humans interact with technology; however, their inability to consider a user’s spatiotemporal context, such as surrounding objects, dramatically limits natural dialogue. We introduce GazePointAR, a wearable augmented reality (AR) system that supports context-aware speech queries using eye gaze, pointing gesture, and conversation history. With GazePointAR, a user can ask “what’s over there?” or “how do I solve this math problem?” simply by looking and/or pointing. GazePointAR disambiguates queries using user inputs, real-time CV, and an LLM.

Publications

GazePointAR: A Context-Aware Multimodal Voice Assistant for Pronoun Disambiguation in Wearable Augmented Reality

Jaewook Lee, Jun Wang, Elizabeth Brown, Liam Gene Ping Chu, Sebastian S. Rodriguez, Jon E. Froehlich

CHI 2024 | Acceptance Rate: 26.3% (1060 / 4028)

Towards Designing a Context-Aware Multimodal Voice Assistant for Pronoun Disambiguation: A Demonstration of GazePointAR

Jaewook Lee, Jun Wang, Elizabeth Brown, Liam Gene Ping Chu, Sebastian S. Rodriguez, Jon E. Froehlich

Extended Abstract Proceedings of UIST 2023