[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-242903-105":53,"doc-detail-242903-en":126},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":119,"head_meta":121,"extra_data":123,"updated_unix":125},105,"en","a-critical-review-a-preprint-knowledge-centric-evaluation-of-quranic-recitation","A CRITICAL REVIEW - A PREPRINT - Knowledge-Centric Evaluation of Quranic Recitation","","The art and science of Quranic recitation (Tajweed) relies on meticulous phonetic, rhythmic, and theological principles, yet faces serious educational obstacles in the digital era. Even with powerful learning technology, automated systems for evaluating recitation have not earned broad acceptance or proven educational effectiveness. This literature review analyzes two decades of research, platforms, and commercial tools, showing that ASR-driven methods often prioritize word identification over qualitative acoustic assessment. It proposes a knowledge-based, rule-driven acoustic evaluation grounded in canonical pronunciation and Makhraj, and concludes that hybrid systems combining linguistic expertise with advanced audio processing can deliver fair, reliable, pedagogically effective feedback.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":11,"@type":70,"position":76},"https://docshare.wps.com/template/presentations/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/a-critical-review-a-preprint-knowledge-centric-evaluation-of-quranic-recitation/242903/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/a-critical-review-a-preprint-knowledge-centric-evaluation-of-quranic-recitation/242903.png","ImageObject",442,249,{"name":88,"@type":89},"Mabel","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-11","2026-09-12",true,{"@type":98,"interactionType":99,"userInteractionCount":73},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"What problem does the review identify with current automated Tajweed evaluation systems?","Question",{"text":108,"@type":109},"Existing systems, often adapted from Automatic Speech Recognition, tend to emphasize word identification rather than qualitative acoustic evaluation. They also suffer from issues like biased datasets, demographic disparities, and limited improvement-oriented feedback.","Answer",{"name":111,"@type":106,"acceptedAnswer":112},"What alternative does the review advocate for building an effective evaluation system?",{"text":113,"@type":109},"The review advocates a paradigm shift to a knowledge-based computational framework. It recommends rule-based acoustic modeling using canonical pronunciation principles and articulation points (Makhraj) rather than relying on statistical patterns from flawed or biased data.",{"name":115,"@type":106,"acceptedAnswer":116},"What direction does the review conclude for the future of automated recitation assessment?",{"text":117,"@type":109},"It concludes that future systems should be hybrid, combining linguistic expertise with advanced audio processing. This design aims to produce tools that are reliable, fair, and pedagogically effective for learners worldwide.","https://schema.org",{"og:url":78,"og:type":120,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":122,"canonical":78},"index,follow",{"doc_id":124,"site_id":56},242903,1791733786,{"code":4,"msg":5,"data":127},{"doc_id":124,"user_id":128,"nickname":88,"user_avatar":129,"doc_module":9,"category_id":8,"category_name":11,"doc_title":59,"doc_description":61,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":135,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":136,"language":137,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":138,"faqs":139,"seo_title":140,"seo_description":61,"update_tm":141,"read_time":8},7971474920318,"https://ap-avatar.wpscdn.com/avatar/74000ee537e6b0ca360?x-image-process=image/resize,m_fixed,w_180,h_180&k=1788430171632181674","A CRITICAL REVIEW OF THE NEED FOR KNOWLEDGE–CENTRIC EVALUATION OF QURANIC RECITATION  \nA PREPRINT  \nMohammed Hilal Al-Kharusi 1 ,  Khizar Hayat, Khalil Bader Al Ruqeishi 1 , and Haroon Rashid Lone2  \n1 College of Arts and Sciences, University of Nizwa, Sultanate of Oman.  \n2Ascend Solutions, Riyadh, Kingdom of Saudi Arabia.  \nNovember 10, 2025  \nABSTRACT  \nThe art and science of Quranic recitation (Tajweed), a discipline governed by meticulous phonetic, rhythmic, and theological principles, confronts substantial educational challenges in today’s digital age. Although modern technology offers unparalleled opportunities for learning, existing automated systems for evaluating recitation have struggled to gain broad acceptance or demonstrate educational effectiveness. This literature review examines this crucial disparity, offering a thorough analysis of scholarly research, digital platforms, and commercial tools developed over the past twenty years. Our analysis uncovers a fundamental flaw in current approaches that adapt Automatic Speech Recognition (ASR) systems, which emphasize word identification over qualitative acoustic evaluation. These systems suffer from limitations such as reliance on biased datasets, demographic disparities, and an inability to deliver meaningful feedback for improvement. Challenging these data-centric methodologies, we advocate for a paradigm shift toward a knowledge-based computational framework. By leveraging the unchanging nature of the Quranic text and the well-defined rules of Tajweed, we propose that an effective evaluation system should be built upon rule-based acoustic modeling centered on canonical pronunciation principles and articulation points (Makhraj), rather than depending on statistical patterns derived from flawed or biased data. The review concludes that the future of automated Quranic recitation assessment lies in hybrid systems that combine linguistic expertise with advanced audio processing. Such an approach paves the way for developing reliable, fair, and pedagogically effective tools that can authentically assist learners across the globe.  \nKeywords Quranic Recitation · Tajweed · Automated Evaluation · Automatic Speech Recognition · Speech Processing  \n1 Introduction  \nThe Qur’an, the foundational sacred book of Islam, holds profound spiritual, legal, and linguistic significance for over two billion Muslims globally. Its recitation (Tajweed) transcends mere reading; it is a sacred act governed by precise rules of pronunciation, rhythm, and intonation, as emphasized in the Qur’an: ”and recite the Qur’an with measured recitation”(Surah Al-Muzammil, 73:4) . The importance of this practice is further underscored in the Prophetic tradition, as the Prophet Muhammad (PBUH) said,”The example of one who recites the Quran and memorizes it is that of one with the ’righteous and noble scribes’. The example of one who recites the Quran and is committed to it, although it is difficult for him, is that of one with a double reward.”[Source: Sahih al-Bukhari 4937, Sahih Muslim 798] . Historically, Quranic recitation pedagogy has relied on direct oral transmission from teacher to student (Mushafa’ha), a method authenticated through chains of authority (Esnad) . This rigorous tradition has preserved the Qur’an’s authentic pronunciation and meaning for centuries, culminating in formal certification (Ejazah) granted only to those demonstrating mastery – a process demanding significant dedication from both student and teacher (Mujaz) . However, contemporary challenges, including time constraints for learners and teachers, the scarcity of qualified instructors  \n∗[khizar.hayat@unizwa.edu.om](khizar.hayat@unizwa.edu.om)  \n(especially outside Muslim-majority regions), and the difficulty of achieving Ejazah mastery later in life, create barriers to this traditional path.  \nThe advent of digital technology in the 21st century offers transformative potential. Digital solutions – including mobile applicati","cbCaisR7xVnq8sJY","https://ap.wps.com/l/cbCaisR7xVnq8sJY","pdf",2984637,7,32,"English","# 1 Introduction\n## Tajweed as an Oral Tradition\n## Digital Technology and Learning Platforms\n## The Unresolved Paradox of Automated Evaluation\n## Purpose and Scope of the Review","[{\"question\":\"What problem does the review identify with current automated Tajweed evaluation systems?\",\"answer\":\"Existing systems, often adapted from Automatic Speech Recognition, tend to emphasize word identification rather than qualitative acoustic evaluation. They also suffer from issues like biased datasets, demographic disparities, and limited improvement-oriented feedback.\"},{\"question\":\"What alternative does the review advocate for building an effective evaluation system?\",\"answer\":\"The review advocates a paradigm shift to a knowledge-based computational framework. It recommends rule-based acoustic modeling using canonical pronunciation principles and articulation points (Makhraj) rather than relying on statistical patterns from flawed or biased data.\"},{\"question\":\"What direction does the review conclude for the future of automated recitation assessment?\",\"answer\":\"It concludes that future systems should be hybrid, combining linguistic expertise with advanced audio processing. This design aims to produce tools that are reliable, fair, and pedagogically effective for learners worldwide.\"}]","A CRITICAL REVIEW - A PREPRINT - Knowledge-Centric Evaluation of Quranic Recitation | PDF",1789196667]