In recent years, foundation models (FMs) such as large language models (LLMs) and latent
diffusion models (LDMs) have profoundly impacted diverse sectors, including music. This …

Roman Numeral analysis is the important task of identifying chords and their functional
context in pieces of tonal music. This paper presents a new approach to automatic Roman …

Graph Neural Networks (GNNs) have recently gained traction in symbolic music tasks, yet a
lack of a unified framework impedes progress. Addressing this gap, we present GraphMuse …

In 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 …

We propose a new graph convolutional block, called MusGConv, specifically designed for
the efficient processing of musical score data and motivated by general perceptual …

This paper approaches the problem of separating the notes from a quantized symbolic
music piece (eg, a MIDI file) into multiple voices and staves. This is a fundamental part of the …

In breaking, which features two dancers breakdancing against each other to the rhythm of
music remixed by a disc jockey (DJ), it is important to match the technique to the timing of the …

Music analysis, as a scholarly field and as a set of techniques, is crucial for comprehending
and appreciating music. It systematically examines elements such as harmony, melody …