musicaiz: A Python Library for Symbolic Music Generation, Analysis and Visualization

TL;DR

musicaiz is a comprehensive Python library that facilitates symbolic music analysis, generation, modification, and evaluation, supporting deep learning applications and reproducible research in music AI.

Contribution

introduces musicaiz, an object-oriented, open-source Python library with modular tools for symbolic music processing and evaluation, enhancing reproducibility and community collaboration.

Findings

Provides tools for symbolic music creation and analysis.

Enables training of deep learning models on MIDI data.

Supports objective evaluation of music generation systems.

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.