Haroon Rashid Lone2024-11-042024-11-0420242024https://repository.iou.edu.gm/handle/123456789/25This study sheds light on the lesser-known fact that the Qurān was revealed in Sab’at Aḥruf, with the wisdom to accommodate the diverse dialects of the Arab tribes at that specific time. The detailed preservation of these recitations through a chain of reciters traced back to the Messenger of Allāh, Muḥammad صلى الله عليه وسلم, emphasizes their enduring importance. It presents a compelling perspective on the Sab’at Aḥruf, proposing a Seven Language Aspects framework wherein each word with a difference can be classified accordingly. The motive was to construct 19 corpora, aligning each with one of the 19 Ruwāt, thereby comprehensively encapsulating the Ten Qira`āt within a structured linguistic framework. This research not only contributes to raising awareness about Qira`āt Sciences but also serves as an introductory exploration of the Ten Qira`āt, highlighting their principal characteristics and comparative differences. It includes the development of a Java-based application to streamline comprehensive conversions between Buckwalter Transliteration and its reverse, specifically designed to facilitate Corpus Development for a targeted Riwāyah. During the process of corpus development, we focused on preserving the 'Usmāni Muṣḥaf syntax during Arabic text modifications, utilizing calculated Token Count and Root Word Count fields to address subsequent occurrences of each word in the Qur`ān systematically. In an exhaustive examination, the Farash for each Rāwī of the Ten Qira`āt was precisely studied, referencing numerous literary sources. The quantification of Farash words, totaling 29,302, concluded in successfully realizing the objective to categorize every differing word into one of the Seven Language Aspects categories. Furthermore, Natural Language Processing Corpus Development for the Riwāyah of Shu’bah was completed for the whole Qur`ān, and methodology was laid for the rest. This developed corpus was applied to various ML models related to Text Classification and Text Clustering. Additionally, Natural Language Processing techniques were applied to develop sentiment analysis for the entire Qur`ān. This research also introduces a distinct approach by categorizing variations according to Seven Language Aspects rather than the conventional method found in Qira`āt literature, which typically focuses on emphasizing differences in ḥarakāt and letters when contrasting with the Riwāyah of Ḥafṣ. This provides a deeper understanding of the reasons behind such changes, including shifts in meaning or morphological forms. Additionally, this methodology enables the quantification of specific words, facilitating targeted practice by identifying verses where particular linguistic features appear most frequently. It is imperative to emphasize that the words of Allah (سبحانه وتعالى ) are flawless, free from any errors, and stand unparalleled. The endeavor undertaken here is a humble attempt to categorize the words of the Perfect One according to the Qira`āt Sciences. It is essential to acknowledge that, as a servant and human being, I am susceptible to errors. Hence, any truth and benefit contained in this work are solely attributable to the assistance and guidance of Allah (سبحانه وتعالى ). Conversely, any errors are solely mine, as Allah alone possesses the ultimate knowledgeenDissertation