Access
## Source Code
Compile from source via GitHub.
Packaged releases coming soon — check the repository for updates.
License
## License
See the GitHub repository for license information.
Publication

Real-Time Drum Accompaniment Using Transformer Architecture
Proceedings of the 3rd International Conference on on AI and Musical Creativity · 2022Abstract
This paper presents a real-time drum generation system capable of accompanying a human instrumentalist. The drum generation model is a transformer encoder trained to predict a short drum pattern given a reduced rhythmic representation. We demonstrate that with certain design considerations, the short drum pattern generator can be used as a real-time accompaniment in musical sessions lasting much longer than the duration of the training samples. A discussion on the potentials, limitations and possible future continuations of this work is provided.
BibTeX
@inproceedings{haki_behzad_2022_7088343, author = {Haki, Behzad and Nieto, Marina and Pelinski, Teresa and Jordà, Sergi}, title = {{Real-Time Drum Accompaniment Using Transformer Architecture}}, booktitle = {{Proceedings of the 3rd International Conference on on AI and Musical Creativity}}, year = {2022}, publisher = {AIMC}, month = sep, doi = {10.5281/zenodo.7088343}, url = {https://doi.org/10.5281/zenodo.7088343}, }
Contact
## Contact
Behzad Haki — behzad.haki@upf.edu
Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain
Overview
## Overview
Groove2Drum is the first drum accompaniment system I released in VST3 plugin format. It generates real-time MIDI drum accompaniments based on an input groove extracted from a live MIDI performance.
This work was presented at AIMC 2022.