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This paper presents a fully Object-Based Audio production workflow for live sports from point of capture to audience playback. The presented chain demonstrates how an efficient workflow can be built with minimal changes for the production staff. As an exemplar, the authors applied this approach to a Premier League football match. Broadcast microphones were recorded at a live event, along with additional streams for the provision of different crowd presentations (home and away etc.) to facilitate an immersive and personalised mix for audiences. To manage the additional channels efficiently, AI-based mixing software was used to ensure an object-based approach from the outset. This was achieved by integrating MPEG-H authoring features providing Next Generation Audio from the point of production, streamlining the workflow thus removing the need for additional authoring later in the chain.
Author (s): Moulson, Aimée; Walley, Max; Grewe, Yannik; Oldfield, Rob; Shirley, Ben; Scuda, Ulli
Affiliation:
Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany; Salsa Sound Ltd., Manchester, United Kingdom; Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany; Salsa Sound Ltd., Manchester, United Kingdom; Salsa Sound Ltd., Manchester, United Kingdom; Acoustic Research Center, University of Salford, Salford, United Kingdom, Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany
(See document for exact affiliation information.)
Publication Date:
2023-08-06
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Permalink: https://aes2.org/publications/elibrary-page/?id=22187
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Moulson, Aimée; Walley, Max; Grewe, Yannik; Oldfield, Rob; Shirley, Ben; Scuda, Ulli; 2023; Object-Based Workflows in Live Sports Broadcasting Using AI-Based Mixing [PDF]; Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany; Salsa Sound Ltd., Manchester, United Kingdom; Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany; Salsa Sound Ltd., Manchester, United Kingdom; Salsa Sound Ltd., Manchester, United Kingdom; Acoustic Research Center, University of Salford, Salford, United Kingdom, Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany; Paper 31; Available from: https://aes2.org/publications/elibrary-page/?id=22187
Moulson, Aimée; Walley, Max; Grewe, Yannik; Oldfield, Rob; Shirley, Ben; Scuda, Ulli; Object-Based Workflows in Live Sports Broadcasting Using AI-Based Mixing [PDF]; Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany; Salsa Sound Ltd., Manchester, United Kingdom; Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany; Salsa Sound Ltd., Manchester, United Kingdom; Salsa Sound Ltd., Manchester, United Kingdom; Acoustic Research Center, University of Salford, Salford, United Kingdom, Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany; Paper 31; 2023 Available: https://aes2.org/publications/elibrary-page/?id=22187
@article{moulson2023object-based,
author={moulson aimée and walley max and grewe yannik and oldfield rob and shirley ben and scuda ulli},
journal={journal of the audio engineering society},
title={object-based workflows in live sports broadcasting using ai-based mixing},
year={2023},
number={31},
month={august},}