Revolutionizing arabic learning: GNT and AI-enhanced Metaverse environments - Ali Syed, Toqeer; Khan, Sohail; Jan, Salman; Nauman, Mohammad (Frontiers in Computer Science, 2025)
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.