TitleMatching Artificial Reverb Settings to Unknown Room Recordings: a Recommendation System for Reverb Plugins
Publication TypeMiscellaneous
Year of Publication2012
AuthorsPeters, N, Choi, J, Lei, H
Abstract

For creating artificial room impressions, numerous reverb plugins exist, often equipped with a large number of reverb parameters.To efficiently create the desired room impression, a sound engineer must be familiar with all his available reverb options.Although plugins are usually shipped with many factory presets for exploring available reverb options, it can often be tedious and time-consuming to find the ideal reverb settings for creating the desired room impression, especially if various reverberation plugins are available.For creating a desired room impression, we present a method to automatically classify the best reverb preset across different reverb plugins.Our method uses a supervised machine-learning approach and can dramatically reduce the time spent on the reverb selection process.