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

arXiv: https://arxiv.org/abs/2008.12073 · HTML: https://mlsanity.com/paper/2008.12073/

## Key facts

- Cited by 35 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Aug 2020.

## Built on by (most cited first, 30 of 35)

- [Diffsound: Discrete Diffusion Model for Text-to-sound Generation](https://mlsanity.com/paper/2207.09983/) (2022)
- [Taming Visually Guided Sound Generation](https://mlsanity.com/paper/2110.08791/) (2021)
- [Conditional Generation of Audio from Video via Foley Analogies](https://mlsanity.com/paper/2304.08490/) (2023)
- [CRASH: Raw Audio Score-based Generative Modeling for Controllable High-resolution Drum Sound Synthesis](https://mlsanity.com/paper/2106.07431/) (2021)
- [Foundation Models for Music: A Survey](https://mlsanity.com/paper/2408.14340/) (2024)
- [Diff-A-Riff: Musical Accompaniment Co-creation via Latent Diffusion Models](https://mlsanity.com/paper/2406.08384/) (2024)
- [Music2Latent: Consistency Autoencoders for Latent Audio Compression](https://mlsanity.com/paper/2408.06500/) (2024)
- [Full-band General Audio Synthesis with Score-based Diffusion](https://mlsanity.com/paper/2210.14661/) (2022)
- [Musika! Fast Infinite Waveform Music Generation](https://mlsanity.com/paper/2208.08706/) (2022)
- [T-FOLEY: A Controllable Waveform-Domain Diffusion Model for Temporal-Event-Guided Foley Sound Synthesis](https://mlsanity.com/paper/2401.09294/) (2024)
- [TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series](https://mlsanity.com/paper/2305.11567/) (2023)
- [DDX7: Differentiable FM Synthesis of Musical Instrument Sounds](https://mlsanity.com/paper/2208.06169/) (2022)
- [Neural Waveshaping Synthesis](https://mlsanity.com/paper/2107.05050/) (2021)
- [JukeDrummer: Conditional Beat-aware Audio-domain Drum Accompaniment Generation via Transformer VQ-VAE](https://mlsanity.com/paper/2210.06007/) (2022)
- [GANStrument: Adversarial Instrument Sound Synthesis with Pitch-invariant Instance Conditioning](https://mlsanity.com/paper/2211.05385/) (2022)
- [CoDiCodec: Unifying Continuous and Discrete Compressed Representations of Audio](https://mlsanity.com/paper/2509.09836/) (2025)
- [DarkGAN: Exploiting Knowledge Distillation for Comprehensible Audio Synthesis with GANs](https://mlsanity.com/paper/2108.01216/) (2021)
- [CycleDRUMS: Automatic Drum Arrangement For Bass Lines Using CycleGAN](https://mlsanity.com/paper/2104.00353/) (2021)
- [Neural Synthesis of Footsteps Sound Effects with Generative Adversarial Networks](https://mlsanity.com/paper/2110.09605/) (2021)
- [Differentiable Digital Signal Processing Mixture Model for Synthesis Parameter Extraction from Mixture of Harmonic Sounds](https://mlsanity.com/paper/2202.00200/) (2022)
- [DrumGAN VST: A Plugin for Drum Sound Analysis/Synthesis With Autoencoding Generative Adversarial Networks](https://mlsanity.com/paper/2206.14723/) (2022)
- [Music2Latent2: Audio Compression with Summary Embeddings and Autoregressive Decoding](https://mlsanity.com/paper/2501.17578/) (2025)
- [VQCPC-GAN: Variable-Length Adversarial Audio Synthesis Using Vector-Quantized Contrastive Predictive Coding](https://mlsanity.com/paper/2105.01531/) (2021)
- [LoopNet: Musical Loop Synthesis Conditioned On Intuitive Musical Parameters](https://mlsanity.com/paper/2105.10371/) (2021)
- [Real-time Timbre Remapping with Differentiable DSP](https://mlsanity.com/paper/2407.04547/) (2024)
- [The Inverse Drum Machine: Source Separation Through Joint Transcription and Analysis-by-Synthesis](https://mlsanity.com/paper/2505.03337/) (2025)
- [LiLAC: A Lightweight Latent ControlNet for Musical Audio Generation](https://mlsanity.com/paper/2506.11476/) (2025)
- [LiveBand: Live Accompaniment Generation in the Audio Domain](https://mlsanity.com/paper/2606.03803/) (2026)
- [Example-Based Framework for Perceptually Guided Audio Texture Generation](https://mlsanity.com/paper/2308.11859/) (2023)
- [HyperGANStrument: Instrument Sound Synthesis and Editing with Pitch-Invariant Hypernetworks](https://mlsanity.com/paper/2401.04558/) (2024)

## Abstract (arXiv)

Synthetic creation of drum sounds (e.g., in drum machines) is commonly performed using analog or digital synthesis, allowing a musician to sculpt the desired timbre modifying various parameters. Typically, such parameters control low-level features of the sound and often have no musical meaning or perceptual correspondence. With the rise of Deep Learning, data-driven processing of audio emerges as an alternative to traditional signal processing. This new paradigm allows controlling the synthesis process through learned high-level features or by conditioning a model on musically relevant information. In this paper, we apply a Generative Adversarial Network to the task of audio synthesis of drum sounds. By conditioning the model on perceptual features computed with a publicly available feature-extractor, intuitive control is gained over the generation process. The experiments are carried out on a large collection of kick, snare, and cymbal sounds. We show that, compared to a specific prior work based on a U-Net architecture, our approach considerably improves the quality of the generated drum samples, and that the conditional input indeed shapes the perceptual characteristics of the sounds. Also, we provide audio examples and release the code used in our experiments.