MusPy: A Toolkit for Symbolic Music Generation

• URL: http://arxiv.org/abs/2008.01951v1
• Date: Wed, 5 Aug 2020 06:16:13 GMT
• Title: MusPy: A Toolkit for Symbolic Music Generation
• Authors: Hao-Wen Dong, Ke Chen, Julian McAuley, Taylor Berg-Kirkpatrick
• Abstract summary: MusPy is an open source Python library for symbolic music generation. In this paper, we present statistical analysis of the eleven datasets currently supported by MusPy.
• Score: 32.01713268702699
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we present MusPy, an open source Python library for symbolic music generation. MusPy provides easy-to-use tools for essential components in a music generation system, including dataset management, data I/O, data preprocessing and model evaluation. In order to showcase its potential, we present statistical analysis of the eleven datasets currently supported by MusPy. Moreover, we conduct a cross-dataset generalizability experiment by training an autoregressive model on each dataset and measuring held-out likelihood on the others---a process which is made easier by MusPy's dataset management system. The results provide a map of domain overlap between various commonly used datasets and show that some datasets contain more representative cross-genre samples than others. Along with the dataset analysis, these results might serve as a guide for choosing datasets in future research. Source code and documentation are available at https://github.com/salu133445/muspy .

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