This blog serves as supplementary material to our paper
"DrumGAN: synthesis of drum sounds with timbral feature conditioning using Generative Adversarial Networks"accepted for ISMIR2020. DrumGAN is a Generative Adversarial Network (GAN) that synthesizes drum sounds and offers high-level control of the sound's timbre characteristics. By conditioning a
Progressive-growing GAN (P-GAN) on descriptors extracted using the
Audio Commons timbre models, it enables the parametrization of the synthesis process on perceptual and musically meaningful features (e.g., boominess, sharpness, brightness, etc.). We encourage the reader to check out the paper for details regarding the architecture, the conditional features, and the quantitative results. Below, we show some examples of drum loops created by a music producer using DrumGAN. These examples give a good taste of the quality and variety of the sounds produced by DrumGAN.