journal article·2021-07-13Open access

Modelling the Microphone-Related Timbral Brightness of Recorded Signals

Andy Pearce, Tim Brookes, Russell Mason

Applied Sciences· Volume 11· Issue 14

Abstract

Brightness is one of the most common timbral descriptors used for searching audio databases, and is also the timbral attribute of recorded sound that is most affected by microphone choice, making a brightness prediction model desirable for automatic metadata generation. A model, sensitive to microphone-related as well as source-related brightness, was developed based on a novel combination of the spectral centroid and the ratio of the total magnitude of the signal above 500 Hz to that of the full signal. This model performed well on training data (r = 0.922). Validating it on new data showed a slight gradient error but good linear correlation across source types and overall (r = 0.955). On both training and validation data, the new model out-performed metrics previously used for brightness prediction.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Music and Audio Processing · Speech and Audio Processing · Music Technology and Sound Studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute of Sound Recording, Department of Music and Media, University of Surrey, Guildford GU2 7XH, UK

Funding

Horizon 2020 Framework Programme

References (14)

Show source-provided references
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