Work

Revolutionizing arabic learning: GNT and AI-enhanced Metaverse environments

Year: 2025

Type: article

Abstract: 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.

Source: Frontiers in Computer Science

DOI: 10.3389/fcomp.2025.1626092

Authors: Toqeer Ali Syed, Sohail Khan, Salman Jan, Mohammad Nauman

Institutions: Islamic University of Madinah, Effat University, Arab Open University

Language: English

Topic: Augmented Reality Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $1,418