A. Moulson, M. Walley, Y. Grewe, R. Oldfield, B. Shirley, and U. Scuda, “Object-Based Workflows in Live Sports Broadcasting Using AI-Based Mixing,” in Proc. AES Conference: AES 2023 International Conference on Spatial and Immersive Audio, Aug. 2023, Paper 31. [Online]. Available: https://aes.org/publications/elibrary-page/?id=22187
Moulson A, Walley M, Grewe Y, Oldfield R, Shirley B, Scuda U. Object-Based Workflows in Live Sports Broadcasting Using AI-Based Mixing. In: AES Conference: AES 2023 International Conference on Spatial and Immersive Audio. Audio Engineering Society; 2023. Paper 31. Available from: https://aes.org/publications/elibrary-page/?id=22187
@inproceedings{Moulson2023_22187,
author = {Moulson, Aimée and Walley, Max and Grewe, Yannik and Oldfield, Rob and Shirley, Ben and Scuda, Ulli},
title = {{Object-Based Workflows in Live Sports Broadcasting Using AI-Based Mixing}},
booktitle = {AES Conference: AES 2023 International Conference on Spatial and Immersive Audio},
note = {Paper 31},
year = {2023},
month = aug,
publisher = {Audio Engineering Society},
url = {https://aes.org/publications/elibrary-page/?id=22187}
}
TY - CPAPER
TI - Object-Based Workflows in Live Sports Broadcasting Using AI-Based Mixing
AU - Moulson, Aimée
AU - Walley, Max
AU - Grewe, Yannik
AU - Oldfield, Rob
AU - Shirley, Ben
AU - Scuda, Ulli
T2 - AES Conference: AES 2023 International Conference on Spatial and Immersive Audio
M1 - Paper 31
PY - 2023
DA - 2023/08/06
UR - https://aes.org/publications/elibrary-page/?id=22187
PB - Audio Engineering Society
LA - en
AB - 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.
ER -