Synchronized Swept-Sine: Theory, Application, and Implementation - October 2015
Effect of Microphone Number and Positioning on the Average of Frequency Responses in Cinema Calibration - October 2015
The Measurement and Calibration of Sound Reproducing Systems - July 2015
Matching Artificial Reverb Settings to Unknown Room Recordings: A Recommendation System for Reverb Plugins
For creating artificial room impressions, numerous reverb plugins exist and are often controllable by many parameters. To efficiently create a desired room impression, the sound engineer must be familiar with all the available reverb setting possibilities. Although plugins are usually equipped with many factory presets for exploring available reverb options, it is a time-consuming learning process to find the ideal reverb settings to create the desired room impression, especially if various reverberation plugins are available. For creating a desired room impression based on a reference audio sample, we present a method to automatically determine the best matching 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.
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