摘要
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 fl-scores, mean squared errors, and multi-stimulus listening tests.
- 出版日期2017-2