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.

翻译：在文章中,我们展示了Musicaiz(Musicaiz),这是一个用于分析、生成和评价象征性音乐的面向对象的图书馆。包的子模块允许用户从零开始创建象征性的音乐数据,建立算法分析象征性音乐,将MIDI数据编码为象征物,以培训深层学习序列模型,修改现有的音乐数据并评价音乐生成系统。评价小模块以先前的工作为基础,客观测量音乐生成系统,并能够复制音乐生成模型的结果。图书馆可以在网上公开查阅。我们鼓励社区贡献和提供反馈。