# White-box Audio VST Effect Programming

arXiv: https://arxiv.org/abs/2102.03170 · HTML: https://mlsanity.com/paper/2102.03170/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 13 references that are in the map.
- First posted on arXiv 5 Feb 2021.

## Builds on (most cited first, 4 of 4)

- [DDSP: Differentiable Digital Signal Processing](https://mlsanity.com/paper/2001.04643/) (2020)
- [Deep Learning for Tube Amplifier Emulation](https://mlsanity.com/paper/1811.00334/) (2018)
- [InverSynth: Deep Estimation of Synthesizer Parameter Configurations from Audio Signals](https://mlsanity.com/paper/1812.06349/) (2018)
- [A Feature Learning Siamese Model for Intelligent Control of the Dynamic Range Compressor](https://mlsanity.com/paper/1905.01022/) (2019)

## Abstract (arXiv)

Learning to program an audio production VST plugin is a time consuming process, usually obtained through inefficient trial and error and only mastered after extensive user experience. We propose a white-box, iterative system that provides step-by-step instructions for applying audio effects to change a user's audio signal towards a desired sound. We apply our system to Xfer Records Serum: currently one of the most popular and complex VST synthesizers used by the audio production community. Our results indicate that our system is consistently able to provide useful feedback for a variety of different audio effects and synthesizer presets.