Symbolic music representations encode musical content at varying levels of completeness, from performance-oriented formats such as MIDI to fully notated scores such as MusicXML. Yet the impact of this representational richness on deep learning models remains poorly understood. While tokenisation has been extensively st...
Andrea Poltronieri, Matteo Spanio, Simone Chieppa et al.· 1 citation
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
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
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.