Al-Quran Recitation or Sound Processing Analysis : A Systematic Literature Review on Methods

Muslims strive to correctly recite and memorize the Quran. However, traditional methods for memorization verification rely on individuals who may not always be available. Conversely, the capabilities of artificial intelligence (AI) enable the development of intelligent memorization tools that use speech recognition methods for information verification. This work aims to review the acknowledgment and verification of Quran recitation techniques. The research methodology involved a systematic review of the literature, utilizing 90 scientific publications sourced from the Google Scholar database. Researchers found that several sound processing technologies can be used. These include wavelet packet decomposition (WPD), Mel-frequency kestrel coefficients (MFCC), and linear predictive coefficients (LPC). AI-driven systems offer the potential to revolutionize the process of Quran memorization and recitation verification by providing consistent and accurate assessments. This approach reduces the dependency on human resources, which can sometimes be scarce or inconsistent. Furthermore, the implementation of these advanced technologies can ensure a higher standard of precision in recitation acknowledgment, making it more accessible for Muslims worldwide to maintain the authenticity and correctness of their memorization efforts. Thus, the integration of AI in Quran recitation verification holds great promise for enhancing the traditional practices and supporting the religious needs of the community.