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Paper detail

White-box Audio VST Effect Programming

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.

preprint2021arXivOpen access
Christopher MitcheltreeHideki Koike
eess.ASMachine LearningSound
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Christopher MitcheltreeHideki Koike

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