Quran-MD: Fine-Grained Multimodal Quran Data at the Verse Level

Quran-MD is a multimodal dataset of the Qur'an integrating textual, linguistic, and audio dimensions at the verse and word levels. The dataset was created by 'yourmumisacow' and is associated with a paper accepted at the 5th Muslims in ML Workshop co-located with NeurIPS 2025. The specific ayah-level subset was last updated on February 21, 2026.

Use Cases

• Train multimodal language models based on integrated textual and audio features mentioned in the description.
• Conduct linguistic analysis of the Quran based on verse and word-level annotations.
• Develop text-to-speech or speech recognition systems for religious recitation based on the audio dimension.
• Perform comparative studies of religious texts using the fine-grained, structured data.

Strengths

• Dataset is part of a larger, complete Quran-MD collection, suggesting a structured scope.
• Associated with a peer-reviewed paper accepted at a NeurIPS 2025 workshop, indicating academic rigor.
• Integrates multiple data dimensions (textual, linguistic, audio) at fine-grained levels.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and sample data are unknown, which may limit suitability assessment.
• License information is unknown, which could restrict commercial or derivative use.

Provenance

Source

huggingface user 'yourmumisacow'.

Collection Method

Method of data gathering is not specified in the provided input.

Freshness

Last updated 2026-02-21 10:10:26; freshness should be verified.