Author

Roser Batlle-Roca

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#artificial intelligence Preprint Sep 2026

On the Human and Computer Alignment of Attribute-Based Music Matches

This work designs a triplet-based forced-choice task comprising 300 cases, including plagiarism examples, cover songs, and AI-generated music, and introduces the MATCHA dataset, a collection of 1105 perceptual assessments of attribute-based music matches from 83 expert participants.

Roser Batlle-Roca, Woo-Sung Choi, Joan Serrà et al. · 0 citations

#artificial intelligence Preprint Aug 2026

MusGU+: Toward a Musician-Centered Evaluation Framework and Discovery Tool for Generative Music AI

MusGU+ is introduced, a musician-centered evaluation framework organized around three dimensions: Adaptability, Usability, and Controllability that supports informed selection and practical adoption of generative systems by musicians.

Laura Ibáñez-Martínez, Roser Batlle-Roca, Xavier Serra et al. · 1 citation