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Integrating IP broadcasting with audio tags: Workflow and challenges
Conference paper   Open access

Integrating IP broadcasting with audio tags: Workflow and challenges

Rhys Burchett-Vass, Arshdeep Singh, Gabriel Bibbó and Mark D. Plumbley
Audio Engineering Society Conference on AI and Machine Learning for Audio (AES AIMLA)
Audio Engineering Society (AES)
1st Audio Engineering Society Conference on AI and Machine Learning for Audio (AES AIMLA), London (London, UK, 08/09/2025–10/09/2025)
04/06/2025

Abstract

The broadcasting industry has adopted IP technologies, revolutionising both live and pre-recorded content production, from news gathering to live music events. IP broadcasting allows for the transport of audio and video signals in an easily configurable way, aligning with modern networking techniques. This shift towards an IP workflow allows for much greater flexibility, not only in routing signals but with the integration of tools using standard web development techniques. One possible tool could include the use of live audio tagging, which has a number of uses in the production of content. These could include adding sound effects to automated closed captioning or identifying unwanted sound events within a scene. In this paper, we describe the process of containerising an audio tagging model into a microservice, a small segregated code module that can be integrated into a multitude of different network setups. The goal is to develop a modular, accessible, and flexible tool capable of seamless deployment into broadcasting workflows of all sizes, from small productions to large corporations. Challenges surrounding latency of the selected audio tagging model and its effect on the usefulness of the end product are discussed.
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BurchettVassSinghBibboP25-aes-aimla_aam207.46 kBDownloadView
Author's Accepted Manuscript Open Access CC BY V4.0
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https://aes2.org/events-calendar/2025-aes-international-conference-on-artificial-intelligence-and-machine-learning-for-audio/View
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