StyleWaveGAN: Style-based synthesis of drum sounds with extensive controls using generative adversarial networks

StyleWaveGAN is a style based drum sound generator that is a variation of StyleGAN, a state-of-the-art image generator by Karras et al. By conditioning StyleWaveGAN on both the type of drum and several audio descriptors, we are able to synthesize waveforms faster than real-time on a GPU directly in CD quality up to a duration of 1.5s while retaining a great amount of control over the generation. We also introduce an alternative to the progressive growing of GANs and experimented on the effect of dataset balancing for generative tasks. The experiments are carried out on an augmented subset of a publicly available dataset comprised of different drums and cymbals.