One-Shot Parametric Audio Production Style Transfer With Application to Frequency Equalization

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

Publication date: May 4, 2020

Stylianos I. Mimilakis, Nicholas J. Bryan, Paris Smaragdis

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Audio production is a difficult process for many people, and properly manipulating sound to achieve a certain effect is non-trivial. In this paper, we present a method that facilitates this process by inferring appropriate audio effect parameters in order to make an input recording sound similar to an unrelated reference recording. We frame our work as a form of \emph{parametric} style transfer that, by design, leverages existing audio production semantics and manipulation algorithms, avoiding several issues that have plagued audio style transfer algorithms in the past. To demonstrate our approach, we consider the task of controlling a parametric, four-band infinite impulse response equalizer and show that we are able to predict the parameters necessary to transform the equalization style of one recording to another. The framework we present, however, is applicable to a wider range of parametric audio effects.

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Research Areas:  Adobe Research iconAI & Machine Learning Adobe Research iconAudio