《古兰经》诵读的自动化评估:模式识别的视角

Nur Ramizah Ramino Rashid, Ibrahim Venkat, F. Damanhoori, Norlia Mustaffa, W. Husain, A. T. Khader
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引用次数: 6

摘要

学习如何背诵《古兰经》的传统方法是通过一种叫做Talaqqi Musyafahah的方法,学生们与合格的《古兰经》老师面对面学习。由于学生与古兰经老师的课程有限,他们采用计算机辅助学习(CAL)方法来进一步提高他们的背诵质量。不幸的是,现有的辅助CAL的应用程序并没有提供任何反馈机制,比如对最终用户的背诵质量进行评级/评分。这种反馈机制的好处对于《古兰经》学习者逐步提高学习过程是至关重要的。迄今为止,使用计算技术自动评估《古兰经》背诵的问题仍然是研究人员面临的一个公开挑战。在本研究中,我们将简要调查这一潜在问题,提出一个基于模式识别视角的基本框架来解决这一问题,并报告我们的初步结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Automating the Evaluation of  Holy Quran Recitations: A Pattern Recognition Perspective
The traditional way of learning how to recite Holy Quran is through a method called Talaqqi Musyafahah where students learn face to face from a qualified Quran teacher. As students have limited sessions with Quran teachers, they resort to Computer Aided Learning (CAL) methods to further enhance their quality of recitations. Unfortunately existing applications that aid in CAL don't provide any feedback mechanisms in terms of ratings/scores about the quality of recitations to end users. The benefits of such feedback mechanisms are quite vital to learners of Holy Quran to improve their learning process stage by stage. Till date, the problem of automating evaluation of Holy Quran recitations using computational techniques remains as a open challenge to researchers. In this research we would investigate this potential problem in brief, propose a basic framework based on a pattern recognition perspective to address the problem and report our preliminary results.
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