- Sharing good practices, state of the art and catalogue of AME tools (2021)
- Development ML/DL models for target audience identification (Q1 2021)
- Development of a POC for authorship identification (Q4 2020)
- Development of a POC for fake news detection(Q4 2020)
- Sharing good practices, state of the art and catalogue of AME tools (2020)
The EBU AME group is part of the EBU "Metadata and Artificial Intelligence" activities. Its main goal is to help Members adopt and develop AI-based automatic information extraction tools, such as:
- content tagging for writings, audios and videos,
- speech-to-text and subtitling,
- face/voice recognition,
- location, event and object detection and identification in videos
- actions detection and identification in videos
Related EBU work
The EBU AI Benchmarking project develops tools to evaluate speech-to-text transcription.
The EBU "AI Data Pool" pre-study, which proposes a framework to share resources for training and assessing AI tools.