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Deep learning system developed for Quran pronunciation error correction

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a deep learning system to automatically detect and correct pronunciation errors in the recitation of the Holy Quran. The system utilizes a novel approach with a custom Quran Phonetic Script (QPS) to encode specific Tajweed rules, going beyond standard phonetic representations. This work introduces a large dataset of 848 hours of audio and a benchmark dataset called qdat_bench to evaluate performance on real recitation errors. AI

IMPACT This research could advance AI applications in specialized linguistic analysis and educational tools for religious texts.

RANK_REASON Academic paper detailing a new deep learning approach for a specific domain. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Deep learning system developed for Quran pronunciation error correction

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Academic paper detailing a new deep learning approach for a specific domain. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Abdullah Abdelfattah, Mahmoud I. Khalil, Hazem Abbas ·

    Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning

    arXiv:2509.00094v2 Announce Type: replace-cross Abstract: Assessing spoken language is challenging, and quantifying pronunciation metrics for machine learning models is even harder. However, for the Holy Quran, this task is enabled by the rigorous recitation rules (Tajweed) estab…

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