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.
@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},}
