Abstract
n this work, we present Score MUsic Graph (SMUG)-Explain, a framework for generating and visualizing explanations of graph neural networks applied to arbitrary prediction tasks on musical scores. Our system allows the user to visualize the contribution of input notes (and note features) to the network output, directly in the context of the musical score. We provide an interactive interface based on the music notation engraving library Verovio. We showcase the usage of SMUG-Explain on the task of cadence detection in classical music.
Type
Publication
In Proceedings of the Sound and Music Computing Conference 2024 (SMC2024), Porto, Portugal
Emmanouil Karystinaios
Postdoctoral Researcher in Artificial Intelligence
My research interests include Music Information Retrieval and Graph Neural Networks