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Found 3 papers, 2 papers with code
Predicting Music Hierarchies with a Graph-Based Neural Decoder
This paper describes a data-driven framework to parse musical sequences into dependency trees, which are hierarchical structures used in music cognition research and music analysis.
Musical Voice Separation as Link Prediction: Modeling a Musical Perception Task as a Multi-Trajectory Tracking Problem
Our approach builds a graph from a musical piece, by creating one node for every note, and separates the melodic trajectories by predicting a link between two notes if they are consecutive in the same voice/stream.
Concept-Based Techniques for "Musicologist-friendly" Explanations in a Deep Music Classifier
Current approaches for explaining deep learning systems applied to musical data provide results in a low-level feature space, e. g., by highlighting potentially relevant time-frequency bins in a spectrogram or time-pitch bins in a piano roll.
