A Deep Learning Approach for Recognizing the Noon Rule for Reciting Holy Quran

المجلة: Protek : Jurnal Ilmiah Teknik Elektro

سنة النشر: 2024

تاريخ النشر: 2024-05-01

Abstract Ahkam Al-Tajweed represents the most precious religious heritage that is in critical need to be preserved and kept for the next generation. This study tackles the challenge of learning Ahkam Al-Tajweed by developing a model that considers one of the rules experienced by early learners in the Holy Quran. The proposed model focuses, specifically, on the "Hukm Al-Noon Al-Mushaddah," which pertains to the proper pronunciation of the letter "Noon" when it is accompanied by a Shaddah symbol in Arabic. By incorporating this rule into the proposed model, learners will benefit the model because it will improve their Tajweed skills and facilitate the learning process for those who do not have access to private tutors or experts. The proposed approach involved three models namely, Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and Random Forest models in the context of a classification task. The models were evaluated based on their validation accuracy, and the results indicate that the CNN model achieved the highest validation accuracy of 0.8613. The other contribution of this work is collecting a novel dataset for this kind of study. The findings show that the Random Forest model outperformed the other models in terms of accuracy.

QDAT: A data set for Reciting the Quran

المجلة: International Journal on Islamic Applications in Computer Science And Technology

سنة النشر: 2021

تاريخ النشر: 2021-03-01

Dataset are considered as an important part of any audio research and an important resource forspeech processing. Availability of dataset in speech processing field is important. The effort andtime needed to build a complete good dataset are very long. The available public dataset in Arabiclanguage are very little. This paper presents the "QDAT" dataset of audio Arabic speech files.The audio files are manually annotated by expert to show the correctness of the Reciting theQuran with Tajwid according to three rules of recitation of Quran. The dataset can be used fortraining and classification models based on machine learning and deep learning algorithms (6) (PDF) QDAT: A data set for Reciting the Quran. Available from: https://www.researchgate.net/publication/350785609_QDAT_A_data_set_for_Reciting_the_Quran#fullTextFileContent [accessed Aug 20 2024].