Official release for the paper "SyMuPe: Affective and Controllable Symbolic Music Performance" (ACM MM 2025 Outstanding Paper Award)
Proceedings of the 33rd ACM International Conference on Multimedia (ACM MM '25), Dublin, Ireland, 2025
Authors: Ilya Borovik, Dmitrii Gavrilev, and Vladimir Viro
SyMuPe is a framework for creating controllable, transformer-based models for rendering symbolic music performances.
Its flagship model, PianoFlow, applies conditional flow matching to solve diverse multi-mask performance inpainting tasks. By design, the model supports both unconditional generation and infilling of expressive performance features.
For more details, please refer to the paper and the demo page with samples.
@inproceedings{borovik2025symupe,
title = {{SyMuPe: Affective and Controllable Symbolic Music Performance}},
author = {Borovik, Ilya and Gavrilev, Dmitrii and Viro, Vladimir},
year = {2025},
booktitle = {Proceedings of the 33rd ACM International Conference on Multimedia},
pages = {10699--10708},
doi = {10.1145/3746027.3755871}
}The materials in this repository are licensed under the Creative Commons Attribution–NonCommercial–ShareAlike 4.0 International License (CC BY-NC-SA 4.0).