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Quranic text mapping and recitation validator released

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method for mapping Quranic text between its Uthmani and Standard Arabic orthographic forms, addressing discrepancies caused by the Unicode character U+0670. This work includes a 2,290-pair word mapping and a seven-step normalization pipeline that achieves 90.9% verse alignment. Building on this, a deterministic, LLM-free validator was created to assess Quranic recitation accuracy, achieving 98.4% on a test suite and correctly identifying verses in all tested Arabic ASR transcripts. AI

IMPACT This research provides tools for more accurate processing and validation of Quranic text, potentially improving NLP applications and ASR systems for Arabic.

RANK_REASON The cluster contains an academic paper detailing a new corpus-aligned mapping and a deterministic validator. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.CL →

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

Quranic text mapping and recitation validator released

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The cluster contains an academic paper detailing a new corpus-aligned mapping and a deterministic validator. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Yahya Mohamed Elnawasany ·

    A Corpus-Aligned Uthmani-to-Standard Quranic Word Mapping and a Deterministic Recitation Validator

    arXiv:2609.14967v1 Announce Type: new Abstract: Quranic text is distributed in two orthographic forms that are byte-level distinct: the Uthmani script used in every printed mushaf, and the Standard (Imla'i) Arabic form that every mainstream Arabic NLP tool is built for. The gap i…

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