Cloud-based AI for automatic audio production for personalized immersive XR experiences

Oldfield, RG, Walley, MSS, Shirley, BG ORCID: https://orcid.org/0000-0001-9634-4489 and Williams, DL 2022, 'Cloud-based AI for automatic audio production for personalized immersive XR experiences' , SMPTE Motion Imaging Journal, 131 (7) , pp. 6-16.

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Abstract

In this article, we focus on the machine-learning approach developed for automatic audio source recognition and mixing for the U.K. Government Department of Culture Media and Sport (DCMS) funded collaborative project called 5G Edge-XR. Leveraging graphics processing unit (GPU) acceleration, we deployed innovative algorithms in the cloud so that content can be automatically mixed on-the-fly for a personalized, immersive, and interactive experience for audiences. We describe the algorithms involved, the system architecture, how it has been implemented for immersive live boxing, and also how we are using it to enhance a live in-stadium experience.

Item Type: Article
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Journal or Publication Title: SMPTE Motion Imaging Journal
Publisher: IEEE
ISSN: 1545-0279
Funders: Department of Culture Media and Sport
Depositing User: Dr Ben Shirley
Date Deposited: 28 Sep 2022 09:35
Last Modified: 28 Sep 2022 09:35
URI: https://usir.salford.ac.uk/id/eprint/64546

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