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Journal Article

Intelligent Control Method for the Dynamic Range Compressor: A User Study

Authors: Singh, Shubhr; Bromham, Gary; Sheng, Di; Fazekas, György

Journal of the Audio Engineering Society · Volume 69 · Issue 7/8 · pp. 576–585 · July 2021

Abstract

Music producers and casual users often seek to replicate dynamic range compression used in a particular recording or production context for their own track. However, not knowing the parameter settings used to produce the audio using the effect may become an impediment, especially for beginners or untrained users who may lack critical listening skills. We address this issue by presenting an automatic compressor plugin relying on a neural network to extract relevant features from a reference signal and estimate compression parameters. The plugin automatically adjusts its parameters to match the input signal with a reference audio recording as closely as possible. Quantitative and qualitative usability evaluation of the plugin was conducted with amateur, pro-amateur and professional music producers. The results established acceptance of the core idea behind the proposed control method across these user groups.

Details

Publication
Journal of the Audio Engineering Society
Volume
69
Issue
7/8
Pages
576–585
Publication date
July 6, 2021
Affiliation
Centre for Digital Music (C4DM) Queen Mary University of London London, UK (See document for exact affiliation information.)
Type
Journal Article