Machine Translation of Quranic Verses: A Transformer-Based Approach to Urdu Rendering
Journal Title: International Journal of Innovations in Science and Technology - Year 2025, Vol 7, Issue 2
Abstract
Translate Quranic Arabic into Urdu is a Challenge due to linguistics and theological differences. While machine translation has advanced significantly, transformer-based Neural Machine Translation (NMT) models have not yet been utilized for Quranic Arabic to Urdu translation. This study addresses this gap by developing a transformer-based model that ensuresaccurate and context-sensitive translation of Quranic verses. A dataset has been initialized that contains Quranic Arabic text and Urdu translation of respected. I performed preprocessing on the dataset by applying it towards tokenization, stemming,and lemmatization, without compromising the theological nature of the theme. To enrich the model to mine the linguistic and stylistic cues, transformer architectures such as Helsinki NLP/MiarinMT were used with the transfer learning. Finally, the model was evaluated for theological correctness by Islamic scholars, and, secondly, by some automated metrics (BLEU, Rouge, and Cosine Similarity). Results show that the transformer model is a better model by far that provides better translation quality in the sense that meanings are preserved, that is, contextual meaning as well as religious meaning, implying better accessibility to Urdu-speaking Muslims. This research proposes a new approach to the problem of translating sacred texts and solves, albeit theologically correct, otherwise unsolvable problemsin Quranic translation, computational linguistics,and AI development. This research introduces a novel approach toQuranic translation, and Future work will explore multimodal learning for deeper contextual understanding.
Authors and Affiliations
Danish Khaleeq, Dr. Muhammad Arshad Awan, Muhammad Tariq, Jamshaid Iqbal
Design of a High Gain Dual Band Patch Antenna with T Slot Ground Structure for Millimeter Wave Communication Applications
This paper introduces a novel design approach for achieving high gain, dual-band operation, and enhanced bandwidth in a microstrip patch antenna tailored for 5G applications. The antenna operates at the millimeter-wave...
ML-Driven Lightweight Botnet Detection System for IoT-Networks
The integration of cloud computing with the Internet of Things (IoT) seeks to create seamless connections between humans and devices, enhancing applications in areas like smart healthcare and home automat...
Effect of Crack Location and Orientation on Crack Growth in Boiler Tube: Theoretical and Computational Investigation
Introduction/Importance of Study: Safety is the paramount concern in the operations and inspections of pressure vessels, such as water tube boilers. Defects in the boiler tubes can lead to the development of cracks. N...
EvaluatingFasterR-CNNandYOLOv8forTrafficObject Detection andClass-Based Counting
Real-time traffic object detection is a critical component necessary for achieving a fully autonomous traffic system. Traffic object detection, along with background classification, is a significant area of research ai...
Exploring Agile Testing Methodologies: A Perspective from the Software Industry
Agile testing is a fast-paced testing method that adheres to the principles outlined in the Agile Manifesto. This research paper explores the adoption of Agile testing methodologies in the context of software houses in...