In “QURAN-MD: A Fine-Grained Multilingual Multimodal Dataset of the Quran” (Muslims in Machine Learning Workshop), Muhammad Umar Salman (Mohamed bin Zayed University of Artificial Intelligence) and others “present QURAN-MD, a comprehensive multimodal dataset of the Quran that integrates textual, linguistic, and audio dimensions at the verse and word levels.For each verse (ayah), the dataset provides its original Arabic text, English translation, and phonetic transliteration. To capture the rich oral tradition of Quranic recitation, we include verse-level audio from 32 distinct reciters, reflecting diverse recitation styles and dialectical nuances. At the word level, each token is paired with its corresponding Arabic script, English translation, transliteration, and an aligned audio recording, allowing fine-grained analysis of pronunciation, phonology, and semantic context.”
