The 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.

翻译：《古兰经》诵读艺术与科学（泰吉威德），作为一门受严格语音、韵律和神学原则规范的学科，在当今数字时代面临着重大的教育挑战。尽管现代技术提供了前所未有的学习机会，但现有的自动化诵读评估系统难以获得广泛认可或证明其教育有效性。本文献综述审视了这一关键差距，对过去二十年间开发的学术研究、数字平台和商业工具进行了全面分析。我们的分析揭示了当前采用自动语音识别（ASR）系统方法的一个根本缺陷，即强调词汇识别而非定性的声学评估。这些系统存在诸多局限性，如依赖有偏数据集、人口统计学差异，以及无法提供有意义的改进反馈。针对这些以数据为中心的方法论，我们倡导向基于知识的计算框架进行范式转变。通过利用《古兰经》文本的不变性和泰吉威德明确定义的规则，我们提出有效的评估系统应建立在以规范发音原则和发音部位（Makhraj）为核心的基于规则的声学建模之上，而非依赖于从有缺陷或有偏数据中得出的统计模式。综述结论指出，自动化《古兰经》诵读评估的未来在于将语言学专业知识与先进音频处理相结合的混合系统。这种方法为开发可靠、公平且具有教学实效的工具铺平了道路，从而能够真正帮助全球的学习者。