Because dynamic range compression is a nonlinear process with memory, parameter settings involve a complex trade-off even if there is advanced knowledge of the input and desired output. By studying the behavior of real human sound engineers, the authors created an independent set of algorithms to automate the values of the parameters using features extracted from the side-chain. The user need only set the threshold for the preferred amount of compression. Subjective evaluation was performed with two groups of subjects: nine expert mixing engineers and seven amateurs who had experience with dynamic range compression. The preferred human choice for each setting was compared to that created by the automation method. A small correction to Eq. 3 on page 718 of this paper was posted in 2014 February.
Authors:
Giannoulis, Dimitrios; Massberg, Michael; Reiss, Joshua D.
Affiliation:
Queen Mary University of London, London, UK
JAES Volume 61 Issue 10 pp. 716-726; October 2013
Publication Date:
October 28, 2013
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