Stepping Into Stories: Envisioning a Generative AI Pipeline to Create Story-based VR Reading Environments

Where you read matters—so what if you could read literally inside your book? Reading in Virtual Reality (VR) has been shown to support deep immersion and narrative engagement. We argue that Generative Artificial Intelligence (GenAI) can significantly expand what is currently possible in VR reading by dynamically producing story-driven environments from text. In this vision paper, we present a pipeline that combines recent advances in language, audio, and 3D scene generation to allow automatically augmenting fiction reading with environmental backdrops. As the reader progresses, these AI-generated environments transition in real time, acting as cognitive props for visual imagery. We also describe a user evaluation, discuss limitations, and address implications and open questions raised by the proposed approach.

Publication Details

Journal
Gesellschaft für Informatik (GI)
Published
2025-01-01
DOI
https://doi.org/10.18420/muc2025-mci-ws09-144
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Stepping Into Stories: Envisioning a Generative AI Pipeline to Create Story-based VR Reading Environments

Gesellschaft für Informatik (GI)
Geochemistry and Geologic Mapping
article

Stepping Into Stories: Envisioning a Generative AI Pipeline to Create Story-based VR Reading Environments

article en

Abstract

Where you read matters—so what if you could read literally inside your book? Reading in Virtual Reality (VR) has been shown to support deep immersion and narrative engagement. We argue that Generative Artificial Intelligence (GenAI) can significantly expand what is currently possible in VR reading by dynamically producing story-driven environments from text. In this vision paper, we present a pipeline that combines recent advances in language, audio, and 3D scene generation to allow automatically augmenting fiction reading with environmental backdrops. As the reader progresses, these AI-generated environments transition in real time, acting as cognitive props for visual imagery. We also describe a user evaluation, discuss limitations, and address implications and open questions raised by the proposed approach.

Gesellschaft für Informatik (GI)
Quality Education
Openalex Percentile: Top 69%
Geochemistry and Geologic Mapping
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