# MusPy: A Toolkit for Symbolic Music Generation

arXiv: https://arxiv.org/abs/2008.01951 · HTML: https://mlsanity.com/paper/2008.01951/

## Key facts

- Cited by 37 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Aug 2020.

## Built on by (most cited first, 30 of 37)

- [HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection](https://mlsanity.com/paper/2202.00874/) (2022)
- [Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs](https://mlsanity.com/paper/2101.02402/) (2021)
- [Anticipatory Music Transformer](https://mlsanity.com/paper/2306.08620/) (2023)
- [Video Background Music Generation: Dataset, Method and Evaluation](https://mlsanity.com/paper/2211.11248/) (2022)
- [Multitrack Music Transformer](https://mlsanity.com/paper/2207.06983/) (2022)
- [Zero-shot Audio Source Separation through Query-based Learning from Weakly-labeled Data](https://mlsanity.com/paper/2112.07891/) (2021)
- [miditok: A Python package for MIDI file tokenization](https://mlsanity.com/paper/2310.17202/) (2023)
- [DadaGP: A Dataset of Tokenized GuitarPro Songs for Sequence Models](https://mlsanity.com/paper/2107.14653/) (2021)
- [PDMX: A Large-Scale Public Domain MusicXML Dataset for Symbolic Music Processing](https://mlsanity.com/paper/2409.10831/) (2024)
- [Frechet Music Distance: A Metric For Generative Symbolic Music Evaluation](https://mlsanity.com/paper/2412.07948/) (2024)
- [Deep Performer: Score-to-Audio Music Performance Synthesis](https://mlsanity.com/paper/2202.06034/) (2022)
- [Controlling Perceived Emotion in Symbolic Music Generation with Monte Carlo Tree Search](https://mlsanity.com/paper/2208.05162/) (2022)
- [Generating music with sentiment using Transformer-GANs](https://mlsanity.com/paper/2212.11134/) (2022)
- [GTR-CTRL: Instrument and Genre Conditioning for Guitar-Focused Music Generation with Transformers](https://mlsanity.com/paper/2302.05393/) (2023)
- [Towards Automatic Instrumentation by Learning to Separate Parts in Symbolic Multitrack Music](https://mlsanity.com/paper/2107.05916/) (2021)
- [ProgGP: From GuitarPro Tablature Neural Generation To Progressive Metal Production](https://mlsanity.com/paper/2307.05328/) (2023)
- [The NES Video-Music Database: A Dataset of Symbolic Video Game Music Paired with Gameplay Videos](https://mlsanity.com/paper/2404.04420/) (2024)
- [A Survey on Artificial Intelligence for Music Generation: Agents, Domains and Perspectives](https://mlsanity.com/paper/2210.13944/) (2022)
- [Between the AI and Me: Analysing Listeners' Perspectives on AI- and Human-Composed Progressive Metal Music](https://mlsanity.com/paper/2407.21615/) (2024)
- [BEAT: Tokenizing and Generating Symbolic Music by Uniform Temporal Steps](https://mlsanity.com/paper/2604.19532/) (2026)
- [An Comparative Analysis of Different Pitch and Metrical Grid Encoding Methods in the Task of Sequential Music Generation](https://mlsanity.com/paper/2301.13383/) (2023)
- [From Words to Music: A Study of Subword Tokenization Techniques in Symbolic Music Generation](https://mlsanity.com/paper/2304.08953/) (2023)
- [MusER: Musical Element-Based Regularization for Generating Symbolic Music with Emotion](https://mlsanity.com/paper/2312.10307/) (2023)
- [A Survey of Music Generation in the Context of Interaction](https://mlsanity.com/paper/2402.15294/) (2024)
- [Time-Shifted Token Scheduling for Symbolic Music Generation](https://mlsanity.com/paper/2509.23749/) (2025)
- [An Order-Complexity Model for Aesthetic Quality Assessment of Symbolic Homophony Music Scores](https://mlsanity.com/paper/2301.05908/) (2023)
- [Evaluating Co-Creativity using Total Information Flow](https://mlsanity.com/paper/2402.06810/) (2024)
- [MMT-BERT: Chord-aware Symbolic Music Generation Based on Multitrack Music Transformer and MusicBERT](https://mlsanity.com/paper/2409.00919/) (2024)
- [Prevailing Research Areas for Music AI in the Era of Foundation Models](https://mlsanity.com/paper/2409.09378/) (2024)
- [ViTex: Visual Texture Control for Multi-Track Symbolic Music Generation via Discrete Diffusion Models](https://mlsanity.com/paper/2603.01984/) (2026)

## Abstract (arXiv)

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 .