Prompting an Embodied AI Agent: How Embodiment and Multimodal Signaling Affects Prompting Behaviour

要旨

Current voice agents wait for a user to complete their verbal instruction before responding; yet, this is misaligned with how humans engage in everyday conversational interaction, where interlocutors use multimodal signaling (e.g. nodding, grunting, or looking at referred to objects) to ensure conversational grounding. We designed an embodied VR agent that exhibits multimodal signaling behaviors in response to situated prompts, by turning its head, or by visually highlighting objects being discussed or referred to. We explore how people prompt this agent to design and manipulate the objects in a VR scene. Through a Wizard of Oz study, we found that participants interacting with an agent that indicated its understanding of spatial and action references were able to prevent errors 30% of the time, and were more satisfied and confident in the agent's abilities. These findings underscore the importance of designing multimodal signalling communication techniques for future embodied agents.

受賞
Honorable Mention
著者
Tianyi Zhang
Singapore Management University, Singapore, Singapore
Colin Au Yeung
University of Calgary, Calgary, Alberta, Canada
Emily Aurelia
Singapore Management University, Singapore, Singapore
Yuki Onishi
Tohoku University, Sendai, Japan
Neil Chulpongsatorn
University of Calgary, Calgary, Alberta, Canada
Jiannan Li
Singapore Management University , Singapore, Singapore
Anthony Tang
Singapore Management University, Singapore, Singapore
DOI

10.1145/3706598.3713110

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713110

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Agent Design

G301
7 件の発表
2025-05-01 01:20:00
2025-05-01 02:50:00
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