MusPyExpress: Extending MusPy with Enhanced Expression Text Support

Abstract:Current work in modeling symbolic music primarily relies on representations extracted from MIDI-like data. While such formats allow for modeling symbolic music as sequences of notes, they omit the large space of symbolic annotations common in western sheet music broadly known as expression text, such as tempo or dynamics, which specify time- and velocity-dependent controls on the musical composition and performance. To alleviate this gap, we present MusPyExpress, an extension to the popular symbolic music processing library MusPy that enables the extraction of expression text along with symbolic music for downstream modeling. Utilizing this extension, we parse the PDMX dataset to illustrate the wealth of expression text available in MusicXML datasets. Additionally, we introduce multiple generative tasks, including joint expression-note generation, expression-conditioned music generation, and expression tagging, that take advantage of this additional notational information.

Sound (cs.SD); Machine Learning (cs.LG); Audio and Speech Processing (eess.AS)

arXiv:2608.21678 [cs.SD]

(or arXiv:2608.21678v1 [cs.SD] for this version)

https://doi.org/10.48550/arXiv.2608.21678 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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