Reports

Tech Papers 2021: This paper shows how super resolution can upscale SD/HD to UHD, as tested by France TV at the French Open, delivering sharper 4K quality.

Tech Paper 2021: This paper explores the BBC’s Public Service Data Ecosystem (PSDE), demonstrating how trusted data management can enhance media recommendations while addressing legal, privacy, security, and design challenges.

Tech Papers 2021: This paper proposes a TV-watching companion robot that generates questions from program content to stimulate conversation, with experiments showing it enhances communication and creates a more engaging viewing experience.

Tech Paper 2021: This paper presents the Itinerant Orchestra use case, where 5G networks enable real-time mixing of street and concert hall musicians in Turin, Italy, detailing the technical setup, network architecture, and performance metrics.

Tech Paper 2021: This paper presents a way to use an individual’s entire media streaming history from all their providers to inform recommendations without any of the contributing services needing to process or hold the data.

Tech Papers 2021: This paper presents a cloud-based architecture for networked radio stations, enabling direct interconnection and media sharing without external devices.

Tech Papers 2021: This paper presents a technical report on building secure, globally scalable hybrid cloud/on-premise production workflows using the JT-NM Reference Architecture, enabling frame-level media access with strong authentication and auditing.

Tech Paper 2021: This paper presents TV 2 Norway’s cloud-native mobile news service, TV 2 Nyhetene, which streamlines content creation and distribution for timely, multi-platform news delivery.

Tech Paper 2021: This paper presents Dialog+, a deep-learning solution that enhances speech intelligibility in broadcast content, allowing user-adjustable dialogue levels even for traditional audio, and reports on large-scale field tests showing strong audience approval.

Tech Papers 2021: This paper presents a cloud-based machine learning approach for automatic audio recognition and mixing in the 5G Edge-XR project, enabling real-time, personalized, immersive audio experiences for live events like boxing and in-stadium broadcasts.