Quran Verse-Level Multimodal Dataset

Quran-MD integrates textual, linguistic, and audio dimensions at the verse (ayah) and word levels. The dataset was created by Buraaq and the associated paper was accepted at the 5th Muslims in ML Workshop at NeurIPS 2025. It is part of a larger, complete Quran-MD collection.

Use Cases

• Train verse-level text classification models using linguistic features from the dataset.
• Develop audio-text alignment models for Quranic recitation using integrated audio dimensions.
• Analyze word-level linguistic patterns and morphology within Quranic verses.
• Build multimodal retrieval systems that can query Quranic content by text, audio, or linguistic attributes.

Strengths

• Dataset is part of a peer-reviewed publication accepted at a NeurIPS 2025 workshop.
• Provides fine-grained multimodal integration at both verse and word levels.

Limitations

• Specific row counts, column details, and sample sizes are unknown.
• The scope is limited to the text of the Quran, which may not generalize to other domains.

Provenance

Source

The Quran.

Collection Method

Constructed as a fine-grained multimodal dataset integrating textual, linguistic, and audio dimensions.

Freshness

Last updated on the Hugging Face platform on 2026-01-27.