Blind Arbitrary Reverb Matching

Andy Sarroff; Roth Michaels
DAFx-2020 - Vienna (virtual)
Reverb provides psychoacoustic cues that convey information concerning relative locations within an acoustical space. The need arises often in audio production to impart an acoustic context on an audio track that resembles a reference track. One tool for making audio tracks appear to be recorded in the same space is by applying reverb to a dry track that is similar to the reverb in a wet one. This paper presents a model for the task of “reverb matching,” where we attempt to automatically add artificial reverb to a track, making it sound like it was recorded in the same space as a reference track. We propose a model architecture for performing reverb matching and provide subjective experimental results suggesting that the reverb matching model can perform as well as a human. We also provide open source software for generating training data using an arbitrary Virtual Studio Technology plug-in.