SMUG-Explain: A Framework for Symbolic Music Graph Explanations

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.

Emmanouil Karystinaios

Senior Machine Learning Engineer and Postdoctoral Researcher

I work in music information retrieval as a Senior Machine Learning Engineer at Muse Group and a part-time Postdoctoral Researcher at Johannes Kepler University Linz.