An Automatic Drum Machine with Touch UI Based on a Generative Neural Network

Drum machines are an important tool for music production in the context of electronic dance music. In this work we introduce a drum machine which automatically generates drum patterns according to the high-level stylistic cues of musical genre, complexity, and loudness, controlled by the user. In comparable tools, usually a predefined collection of drum patterns serves as the source for suggestions. In order to yield a greater variety of patterns and to create original patterns, we suggest the use of stochastic generative models. Therefore, in this work, drum patterns are generated using a generative adversarial network, trained on a large-scale drum pattern library. As a method to enter, edit, visualize, and generate patterns, a touch-based step sequencer interface is augmented with controls of the semantic dimensions of genre, complexity, and loudness.