Deep audio effects for snare drum recording transformations

Cheshire, Matthew and Drysdale, Jake and Enderby, Sean and Tomczak, Maciej and Hockman, Jason (2022) Deep audio effects for snare drum recording transformations. Journal of the Audio Engineering Society, 70 (9). pp. 742-752. ISSN 1549-4950

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The ability to perceptually modify drum recording parameters in a post-recording process would be of great benefit to engineers limited by time or equipment. In this work, a datadriven approach to post-recording modification of the dampening and microphone positioning parameters commonly associated with snare drum capture is proposed. The system consists of a deep encoder that analyzes audio input and predicts optimal parameters of one or more third-party audio effects, which are then used to process the audio and produce the desired transformed output audio. Furthermore, two novel audio effects are specifically developed to take advantage of the multiple parameter learning abilities of the system. Perceptual quality of transformations is assessed through a subjective listening test, and an object evaluation is used to measure system performance. Results demonstrate a capacity to emulate snare dampening; however, attempts were not successful for emulating microphone position changes.

Item Type: Article
Identification Number:
1 August 2022Accepted
12 September 2022Published Online
Subjects: CAH11 - computing > CAH11-01 - computing > CAH11-01-04 - software engineering
CAH11 - computing > CAH11-01 - computing > CAH11-01-05 - artificial intelligence
CAH25 - design, and creative and performing arts > CAH25-02 - performing arts > CAH25-02-02 - music
Divisions: Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Depositing User: Jason Hockman
Date Deposited: 06 Dec 2022 16:51
Last Modified: 22 Mar 2023 12:00

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