CulturAI: Exploring Mixed Reality Art Exhibitions with Large Language Models for Personalized Immersive Experiences
Nicolas Constantinides, Argyris Constantinides, Dimitrios Koukopoulos, Christos Fidas, Marios Belk
Abstract
Mixed Reality (MR) technologies have transformed the way in which we interact and engage with digital content, offering immersive experiences that blend the physical and virtual worlds. Over the past years, there has been increasing interest in employing Artificial Intelligence (AI) technologies to improve user experience and trustworthiness in cultural contexts. However, the integration of Large Language Models (LLMs) into MR applications within the Cultural Heritage (CH) domain is relatively underexplored. In this work, we present an investigation into the integration of LLMs within MR environments, focusing on the context of virtual art exhibitions. We implemented a HoloLens MR application, which enables users to explore artworks while interacting with an LLM through voice. To evaluate the user experience and perceived trustworthiness of individuals engaging with an LLM-based virtual art guide, we adopted a between-subject study design, in which participants were randomly assigned to either the LLM-based version or a control group using conventional interaction methods. The LLM-based version allows users to pose inquiries about the artwork displayed, ranging from details about the creator to information about the artwork’s origin and historical significance. This paper presents the technical aspects of integrating LLMs within MR applications and evaluates the user experience and perceived trustworthiness of this approach in enhancing the exploration of virtual art exhibitions. Results of an initial evaluation provide evidence about the positive aspect of integrating LLMs in MR applications. Findings of this work contribute to the advancement of MR technologies for the development of future interactive personalized art experiences.