Elicitation of expert knowledge to inform object-based audio rendering to different systems

Woodcock, JS ORCID: https://orcid.org/0000-0001-5654-5374, Davies, WJ ORCID: https://orcid.org/0000-0002-5835-7489, Melchior, F and Cox, TJ ORCID: https://orcid.org/0000-0002-4075-7564 2018, 'Elicitation of expert knowledge to inform object-based audio rendering to different systems' , Journal of the Audio Engineering Society, 66 (1/2) , pp. 44-59.

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Object-based audio presents the opportunity to optimise audio reproduction for different listening scenarios. Vector base amplitude panning (VBAP) is typically used to render object-based scenes. Optimizing this process based on knowledge of the perception and practices of experts could result in significant improvements to the end user's listening experience. An experiment was conducted to investigate how content creators perceive changes in the perceptual attributes of the same content rendered to systems with different numbers of channels, and to determine what they would do differently to standard VBAP and matrix based downmixes to minimize these changes. Text mining and clustering of the content creators' responses revealed 6 general mix processes: the spatial spread of individual objects, EQ and processing, reverberation, position, bass, and level. Logistic regression models show the relationships between the mix processes, perceived changes in perceptual attributes, and the rendering method/speaker layout. The relative frequency of use for the different mix processes was found to differ between categories of audio object suggesting that any downmix rules should be object category specific. These results give insight into how object-based audio can be used to improve listener experience and provide the first template for doing this across different reproduction systems.

Item Type: Article
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Journal or Publication Title: Journal of the Audio Engineering Society
Publisher: Audio Engineering Society (AES)
ISSN: 1549-4950
Related URLs:
Funders: Engineering and Physical Sciences Research Council (EPSRC)
Depositing User: USIR Admin
Date Deposited: 05 Jan 2018 09:02
Last Modified: 15 Feb 2022 22:48
URI: https://usir.salford.ac.uk/id/eprint/44895

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