ORIGINAL RESEARCH article
Front. Comput. Sci.
Sec. Human-Media Interaction
Volume 7 - 2025 | doi: 10.3389/fcomp.2025.1626092
This article is part of the Research TopicAI Innovations in Education: Adaptive Learning and BeyondView all 20 articles
Revolutionizing Arabic Learning: GNT and AI-Enhanced Metaverse Environments
Provisionally accepted
- 1Islamic University Madinah, Madinah, Saudi Arabia
- 2Department of Computer Science, Effat college of Engineering, Effat University, Jeddah, Saudi Arabia
- 3Arab Open University, A'Ali, Bahrain
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The rapid evolution of artificial intelligence and extended reality technologies has opened new frontiers in language learning. Traditional methods often lack engagement, while modern approaches utilizing enhanced immersion (Augmented Reality (AR) and Virtual Reality (VR)) but remain constrained by static content. This research proposes an innovative framework integrating the Generalizable NeRF Transformer (GNT) with the Metaverse to facilitate Arabic language learning. By leveraging AI-driven dynamic 3D scene generation, the system allows learners to interact with virtual environments and engage in contextual conversations with intelligent avatars. The platform supports real-time speech-to-text conversion, AI-generated responses, and interactive 3D object generation corresponding to Arabic vocabulary, fostering a multisensory learning experience. This study outlines the architecture, algorithms, and implementation strategy, demonstrating how Metaverse-integrated GNT can revolutionize language acquisition through immersive, adaptive, and scalable methodologies.
Keywords: Metaverse, AR, VR, Metaverse-Based Language Learning, conversational AI, Arabic Vocabulary Acquisition
Received: 10 May 2025; Accepted: 02 Sep 2025.
Copyright: © 2025 Ali, Khan, Jan and Nauman. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Salman Jan, Arab Open University, A'Ali, Bahrain
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