MusicRecoIntent-NLP4MusA26

This repository contains the dataset presented in the paper: "Beyond Musical Descriptors: Extracting Preference-Bearing Intent in Music Queries", accepted for publication at NLP4MusA 2026.

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MusicRecoIntent Dataset

MusicRecoIntent is a manually annotated dataset of music-related user queries designed to capture not only musical descriptors but also the preference-bearing intent associated with each descriptor.

Built on top of MusicRecoNER (Epure and Hennequin, 2023), the dataset contains:

• 2,291 English-language Reddit music recommendation requests
• 3,935 annotated musical descriptors (Genre, Mood, Instrument, Listening Context, Decade, Country and Musical Named Entities).

Each descriptor is annotated with a preference-bearing intent:

• + : positive (explicitly desired)
• - : negative (explicitly rejected)
• ~ : referential (similarity / inspiration)

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Citation

If you use the MusicRecoIntent dataset in your work, please cite:

@InProceedings{Baranes2026MusicRecoIntent,
 	title={Beyond Musical Descriptors: Extracting Preference-Bearing Intent in Music Queries},
  	author={Baranes, Marion and Hennequin, Romain and Epure, Elena V.},
  	booktitle={Proceedings of the 4rd Workshop on NLP for Music and Audio (NLP4MusA2026)},
  	month={March},
  	year={2026},
  	publisher = {Association for Computational Linguistics},
}