DrumGAN VST: A Plugin for Drum Sound Analysis/Synthesis With Autoencoding Generative Adversarial Networks

06/29/2022

∙

In contemporary popular music production, drum sound design is commonly performed by cumbersome browsing and processing of pre-recorded samples in sound libraries. One can also use specialized synthesis hardware, typically controlled through low-level, musically meaningless parameters. Today, the field of Deep Learning offers methods to control the synthesis process via learned high-level features and allows generating a wide variety of sounds. In this paper, we present DrumGAN VST, a plugin for synthesizing drum sounds using a Generative Adversarial Network. DrumGAN VST operates on 44.1 kHz sample-rate audio, offers independent and continuous instrument class controls, and features an encoding neural network that maps sounds into the GAN's latent space, enabling resynthesis and manipulation of pre-existing drum sounds. We provide numerous sound examples and a demo of the proposed VST plugin.

READ FULL TEXT

DrumGAN VST: A Plugin for Drum Sound Analysis/Synthesis With Autoencoding Generative Adversarial Networks

DrumGAN: Synthesis of Drum Sounds With Timbral Feature Conditioning Using Generative Adversarial Networks

Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs)

Variation Network: Learning High-level Attributes for Controlled Input Manipulation

Sound Model Factory: An Integrated System Architecture for Generative Audio Modelling

GANStrument: Adversarial Instrument Sound Synthesis with Pitch-invariant Instance Conditioning

Neural Percussive Synthesis Parameterised by High-Level Timbral Features

Unsupervised Feature Learning for Environmental Sound Classification Using Cycle Consistent Generative Adversarial Network

DrumGAN VST: A Plugin for Drum Sound Analysis/Synthesis With Autoencoding Generative Adversarial Networks

Related Research

DrumGAN: Synthesis of Drum Sounds With Timbral Feature Conditioning Using Generative Adversarial Networks

Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs)

Variation Network: Learning High-level Attributes for Controlled Input Manipulation

Sound Model Factory: An Integrated System Architecture for Generative Audio Modelling

GANStrument: Adversarial Instrument Sound Synthesis with Pitch-invariant Instance Conditioning

Neural Percussive Synthesis Parameterised by High-Level Timbral Features

Unsupervised Feature Learning for Environmental Sound Classification Using Cycle Consistent Generative Adversarial Network