Adaptive radio system using metasounds for serious VR game

Damastuti, Fardani Annisa, Firmansyah, Kenan, Arif, Yunifa Miftachul ORCID: https://orcid.org/0000-0002-2183-0762, Pramadihanto, Dadet and Criollo-C, Santiago (2025) Adaptive radio system using metasounds for serious VR game. IEEE Access, 13. pp. 189188-189202. ISSN 2169-3536

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Abstract

Background: Adaptive audio can deepen immersion in VR, yet many pipelines still rely on fixed playlists or ad-hoc triggers that break narrative coherence during rapid context shifts in serious games. Methods: We implement an adaptive in-game radio using Unreal Engine MetaSounds and a finite-state machine (FSM). Three affective stations (Happy, Excited, Intense) drive procedural ambient music with equal-power crossfades, loudness normalization, and optional beat-synchronous transitions. We integrate Blueprint–MetaSounds graphs and evaluate usability and perceived immersion with 30 participants in VR. Results: The interface was rated intuitive by 90% of users; 85% reported higher immersion than a non-adaptive baseline; 80% felt the adaptive music heightened emotions at key events. Overall satisfaction averaged 4.5/5, and 70% indicated replay intent to explore audio variants. We provide the audio graph, state logic, and transition envelopes, and quantify transition smoothness via envelope and loudness metrics. Conclusions: An engine-native MetaSounds–FSM pattern is practical to deploy and can improve engagement in serious VR contexts. We discuss design trade-offs, limitations (sample size and demographics), and avenues for broader deployment in training and therapeutic simulations.

Item Type:	Journal Article
Keywords:	adaptive radio system; virtual reality; serious games; metasounds; immersive audio; finite state machines
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0803 Computer Software > 080305 Multimedia Programming
Divisions:	Faculty of Technology > Department of Informatics Engineering
Depositing User:	Yunifa Miftachul Arif
Date Deposited:	10 Jul 2026 09:14

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