NLive will focus on the engagement and incentivisation through using a P2P Learning support platform, which will use Natural Language Processing (NLP) in order to provide improved quality assurance of the live capture of the lectures and for HEIs to manage digital rights (DRM). The aim of the project is to improve the engagement of students with the lecture material generated withing the HEI.
This will be achieved through:
Use of NLP to create automated quality control of human collaboratively edited closed-captioning and live translation.
Provision of multi-DRM (digital rights management) and watermarking to protect HEI IP on live-streaming and video-ondemand across different platforms and devices. NLive will support major DRM schemes including Playready (over Smooth Stream and Dash CENC), Widevine (Classic and Modular over Dash CENC) and Apple Fairplay and tightly integrated with NLive’s recording-packaging features.
Use of AI and noise-cancellation algorithms to enhance audio quality, especially in home environments based on NTE’s 60,000 hours of sampling audio.
Providing accessibility at the core of the implementation to cater for different learning styles.
Integrating those innovations into our NLive and optimising the algorithms to minimise the impact on latency and memory consumption.