The availability of extended reality (XR) devices has widened their adoption, yet authoring interactive experiences remains complex for non-programmers. We introduce Tell-XR, an intelligent agent leveraging large language models (LLMs) to guide end-users in defining the interaction in XR settings using automations described as Event-Condition-Action (ECA) rules. Through a formative study, we identified the key conversation stages to define and refine automations, which informed the design of the system architecture. The evaluation study in two scenarios (a VR museum and an AR smart home) demonstrates the effectiveness of Tell-XR across different XR interaction settings.

Tell-XR: conversational end-user development of XR automations

Mereu, Jacopo;Spano, Lucio Davide
2025-01-01

Abstract

The availability of extended reality (XR) devices has widened their adoption, yet authoring interactive experiences remains complex for non-programmers. We introduce Tell-XR, an intelligent agent leveraging large language models (LLMs) to guide end-users in defining the interaction in XR settings using automations described as Event-Condition-Action (ECA) rules. Through a formative study, we identified the key conversation stages to define and refine automations, which informed the design of the system architecture. The evaluation study in two scenarios (a VR museum and an AR smart home) demonstrates the effectiveness of Tell-XR across different XR interaction settings.
2025
9783032049988
9783032049995
End-User Development
eXtended Reality
Immersive Authoring
Large Language Models
Meta Design
Rules
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/494448
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