AUTOMATED TRANSLATION TOOLS FOR MUALAF: ARTIFICIAL INTELLIGENCE SOLUTIONS FOR ACCESSING ISLAMIC TEXTS AND RESOURCES ACROSS LANGUAGES

Abstract

This paper explores the potential of Automated Translation Tools (ATT) or AI-driven translation tools in enhancing the accessibility of Islamic knowledge for mualaf (new converts to Islam) who may face linguistic barriers. Machine translation (MT) and natural language processing (NLP) technologies let Mualaf access religious texts, educational videos, and learning materials in their native languages, bridging gaps in understanding and enabling more profound engagement with Islamic teachings. The study assesses current AI translation tools' effectiveness in religious contexts, identifies challenges in translating complex theological content, and provides recommendations for improving AI tools to support mualaf communities. The findings demonstrate that while current AI translation technologies show promise, specific cultural and religious sensitivities must be addressed for more accurate and contextually appropriate translations.