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.
Singh, Shubhr; Bromham, Gary; Sheng, Di; Fazekas, György
Affiliation: Centre for Digital Music (C4DM) Queen Mary University of London London, UK
JAES Volume 69 Issue 7/8 pp. 576-585; July 2021
Publication Date: July 7, 2021
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