Abstract
Muslims aim to recite and memorize the Holy Quran correctly. However, traditional recitation verification approaches depend on humans who may not be available. On the other hand, Artificial Intelligence (AI) capabilities assist in developing intelligent recitation verification tools based on speech recognition techniques. This study aims to overview the current state of the intelligent Quran recitation recognition and verification solutions and highlight the related open issues. A systematic literature review was performed on the published paper since 2006 up to date to answer six research questions. The research questions covered the speech recognition techniques and methods used to develop Quran recitation recognition and verification models, the database and tools used, and the existing mobile application supporting real-time intelligent Quran recitation verification services. Based on the review results, a taxonomy of the Quran recitation recognition and verification techniques was generated, including traditional and end-to-end speech recognition methods. Moreover, the limitations of the existing AI-based Quran recitation verification applications were reported. Additionally, the available Quran audio datasets and tools capable of dealing with Quranic speech were identified. In conclusion, several open issues can be addressed in future research, e.g., considering AI-based approaches to ensure sequence recitation and recognize diacritics-based errors.