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

arXiv: https://arxiv.org/abs/2206.14723 · HTML: https://mlsanity.com/paper/2206.14723/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 20 references that are in the map.
- First posted on arXiv 29 Jun 2022.

## Builds on (most cited first, 15 of 15)

- [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020)
- [Rethinking the Inception Architecture for Computer Vision](https://mlsanity.com/paper/1512.00567/) (2015)
- [Auto-Encoding Variational Bayes](https://mlsanity.com/paper/1312.6114/) (2013)
- [Progressive Growing of GANs for Improved Quality, Stability, and Variation](https://mlsanity.com/paper/1710.10196/) (2017)
- [Improved Training of Wasserstein GANs](https://mlsanity.com/paper/1704.00028/) (2017)
- [WaveNet: A Generative Model for Raw Audio](https://mlsanity.com/paper/1609.03499/) (2016)
- [Adversarial Audio Synthesis](https://mlsanity.com/paper/1802.04208/) (2018)
- [GANSynth: Adversarial Neural Audio Synthesis](https://mlsanity.com/paper/1902.08710/) (2019)
- [RAVE: A variational autoencoder for fast and high-quality neural audio synthesis](https://mlsanity.com/paper/2111.05011/) (2021)
- [The challenge of realistic music generation: modelling raw audio at scale](https://mlsanity.com/paper/1806.10474/) (2018)
- [CRASH: Raw Audio Score-based Generative Modeling for Controllable High-resolution Drum Sound Synthesis](https://mlsanity.com/paper/2106.07431/) (2021)
- [DrumGAN: Synthesis of Drum Sounds With Timbral Feature Conditioning Using Generative Adversarial Networks](https://mlsanity.com/paper/2008.12073/) (2020)
- [Upsampling artifacts in neural audio synthesis](https://mlsanity.com/paper/2010.14356/) (2020)
- [Neural Drum Machine : An Interactive System for Real-time Synthesis of Drum Sounds](https://mlsanity.com/paper/1907.02637/) (2019)
- [DarkGAN: Exploiting Knowledge Distillation for Comprehensible Audio Synthesis with GANs](https://mlsanity.com/paper/2108.01216/) (2021)

## Built on by (most cited first, 4 of 4)

- [Diff-A-Riff: Musical Accompaniment Co-creation via Latent Diffusion Models](https://mlsanity.com/paper/2406.08384/) (2024)
- [Improving Musical Accompaniment Co-creation via Diffusion Transformers](https://mlsanity.com/paper/2410.23005/) (2024)
- [SampleMatch: Drum Sample Retrieval by Musical Context](https://mlsanity.com/paper/2208.01141/) (2022)
- [LiLAC: A Lightweight Latent ControlNet for Musical Audio Generation](https://mlsanity.com/paper/2506.11476/) (2025)

## Abstract (arXiv)

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.