musicaiz: A Python Library for Symbolic Music Generation, Analysis and Visualization
Sound
2022-09-19 v1 Multimedia
Audio and Speech Processing
Abstract
In this article, we present musicaiz, an object-oriented library for analyzing, generating and evaluating symbolic music. The submodules of the package allow the user to create symbolic music data from scratch, build algorithms to analyze symbolic music, encode MIDI data as tokens to train deep learning sequence models, modify existing music data and evaluate music generation systems. The evaluation submodule builds on previous work to objectively measure music generation systems and to be able to reproduce the results of music generation models. The library is publicly available online. We encourage the community to contribute and provide feedback.
Cite
@article{arxiv.2209.07974,
title = {musicaiz: A Python Library for Symbolic Music Generation, Analysis and Visualization},
author = {Carlos Hernandez-Olivan and Jose R. Beltran},
journal= {arXiv preprint arXiv:2209.07974},
year = {2022}
}