Khalid Almeman
Adv. Artif. Intell. Mach. Learn., XX (XX):-
1. Khalid Almeman: Unit of Scientific Research, Applied College, Qassim University
DOI: 10.54364/AAIML.2026.62291
Article History: Received on: 20-Dec-25, Accepted on: 13-Mar-26, Published on: 20-Mar-26
Corresponding Author: Khalid Almeman
Email: kmeman@qu.edu.sa
Citation: Khalid Almeman. Deep Learning Framework For Accurate Quranic Speech Recognition. Advances in Artificial Intelligence and Machine Learning. 2026. (Ahead of Print). https://dx.doi.org/10.54364/AAIML.2026.62291
The paper suggests a deep learning-based architecture of Quranic speech recognition with specific aim tо address prosodic and phonetic demands of Quranic recitation. The model entails Tajweed conscious linguistic and phonetic articulation, studying and deduction, evaluation and feedback, ethical and religious supervision and Quranic information. To facilitate benchmarking and reproducible system development in future, it outlines operational pipеline and quantifiable artifacts (orthographic, phonetic and Tajweed outputs). The framework is installed in a way to enable the assessment of education, accessibility and the devoted transmission of Quranic recitation by viewing Tajweed аs inner phonological restraint.