Real-Time Drum Accompaniment Using Transformer Architecture

Authors

Haki B, Nieto M, Pelinski T, Jordà S

UPF authors

Type

Conference proceedings

Book Authors

AA. VV.

Book title

Proceedings of the 3rd Conference on AI Music Creativity (AIMC 2022)

Publisher

AIMC

Publication year

2022

Pages

1-10

Abstract

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.

Complete citation

Haki B, Nieto M, Pelinski T, Jordà S. Real-Time Drum Accompaniment Using Transformer Architecture. In: AA. VV.. Proceedings of the 3rd Conference on AI Music Creativity (AIMC 2022). 1 ed. AIMC; 2022. p. 1-10.