Spatial Audio | Yiyang "Diana" Wang

CompanionCast

Thu, 11 Dec 2025 00:00:00 +0000

Shared experiences are central to social connection, yet media consumption is increasingly solitary. CompanionCast is a general framework for orchestrating multiple specialized AI agents as social collaborators within a live shared context. It combines multimodal event detection, rolling context caching for better grounding, and spatial audio to enhance co-presence, with an LLM-as-a-judge step that refines the agents’ dialogue.

My role. I led this work, developed during a Ph.D. research internship at Dolby Laboratories. We validated CompanionCast in the domain of sports viewing; pilot studies with soccer fans showed significant improvements in perceived social presence and emotional sharing compared to viewing alone. The work was accepted at the ACM CHI 2026 Workshop on Human-Agent Collaboration.

CompanionCast: Toward Social Collaboration with Multi-Agent Systems in Shared Experiences

Thu, 11 Dec 2025 00:00:00 +0000

Abstract

Shared experiences are fundamental to social connection, yet media consumption is increasingly solitary. We present CompanionCast, a general framework for orchestrating multiple specialized AI agents as social collaborators within a live shared context, integrating multimodal event detection, rolling context caching, and spatial audio to enhance co-presence. Validated through sports viewing, pilot studies with soccer fans show that CompanionCast significantly improves perceived social presence and emotional sharing compared to solitary viewing. This work was conducted in part during a Ph.D. research internship at Dolby Laboratories and accepted at the ACM CHI 2026 Workshop on Human-Agent Collaboration.