A Machine-Learning Approach to Application of Intelligent Artificial Reverberation
Emmanouil Chourdakis, Joshua D. Reiss · Journal of the Audio Engineering Society · 2017
We propose a design of an adaptive digital audio effect for artificial reverberation, controlled directly by desired reverberation characteristics, that allows it to learn from the user in a supervised way.The user provides monophonic examples of desired reverberation characteristics for individual tracks taken from the Open Multitrack Testbed.We use this data to train a set of models to automatically apply reverberation to similar tracks.We evaluate those models using classifier f1-scores, mean squared errors, and multi-stimulus listening tests.