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The vast amount of metadata available to audio researchers has been used in a number of ways, including music transcription, music genre classification, and automatic mixing. Of particular interest to us is the way that metadata can be used to assist in the music production process. In this paper, we explore the potential benefits of using this data when controlling artificial reverberation. Using the psychophysical method of magnitude estimation, we gather data on the perceived intensity of reverberation for a range of reverberation ratios, sources and listening levels. We show that whilst reverberation intensity is related to the ratio, this relationship is nonlinear. We also show that reverberation intensity is dependent on the source, and strongly dependent upon the listening level. We suggest that using metadata related to source type and either mixing or reproduction environment could be used to simplify the control of reverberation audio effects.
Author (s): Bussey, Carl; Terrell, Michael; Rahman, Raihan; Sandler, Mark
Affiliation:
Queen Mary University of London, London, UK
(See document for exact affiliation information.)
Publication Date:
2014-01-06
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Session subject:
Intelligent Audio Effects
Permalink: https://aes2.org/publications/elibrary-page/?id=17113
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Bussey, Carl; Terrell, Michael; Rahman, Raihan; Sandler, Mark; 2014; Metadata Features that Affect Artificial Reverberator Intensity [PDF]; Queen Mary University of London, London, UK; Paper P2-10; Available from: https://aes2.org/publications/elibrary-page/?id=17113
Bussey, Carl; Terrell, Michael; Rahman, Raihan; Sandler, Mark; Metadata Features that Affect Artificial Reverberator Intensity [PDF]; Queen Mary University of London, London, UK; Paper P2-10; 2014 Available: https://aes2.org/publications/elibrary-page/?id=17113