Deep learning for spoken language identification
Imagine that a tourist calls an emergency service speaking a foreign language. How to find a person that speaks the right language? Or you have tons of multilingual television broadcasts…
Read more
Audiovisual media content is an essential resource of modern history. It’s our way to communicate and to entertain. To fully benefit from multilingual audiovisual content, we need efficient tools to make visual content accessible in words.
What is MeMAD providing?
We provide new methods that help to translate moving images and sounds into words. MeMAD methods will help us to manage large amounts of audiovisual data cost efficiently.
Who will benefit from MeMAD?
Anyone using audiovisual content will benefit from MeMAD. Professionals who work in the Creative Industries will receive new methods for video management and digital storytelling. Visually and hearing impaired, among others, will have better access to video content.
MeMAD is an EU funded H2020 research project (2018-2020). MeMAD will develop methods for an efficient re-use and re-purpose of multilingual audiovisual content targeting to revolutionize video management and digital storytelling in broadcasting and media production.
“We go far beyond the state-of-the-art automatic video description methods by making the machine learn from the human. The resulting description is thus not only a time-aligned semantic extraction of objects but makes use of the audio and recognizes action sequences.”
MeMAD’s main results are detailed, rich descriptions of the moving images, speech, and audio. We integrate the latest research achievements in deep neural network techniques in computer vision with knowledge bases, human and machine translation in a continuously improving machine learning framework.
Project partners
Latest from the blog
Putting it all together: towards multimodal solutions and their evaluation
INA hosted our 6th in plenary meeting in Paris in the beginning of February. Together, we hashed out the final stages of development of our multimodal solutions and the final…
Automatically generated metadata in video editing and searching
At the end of the second year of the MeMAD project, different aspects of the prototype were chosen for evaluation, based on product maturity. There were four tracks of evaluation:…
Into the lion’s den? Pilot testing machine translated subtitles with professional subtitlers
One important part of the MeMAD project is working with potential users of the tools developed, as well as presenting the research and development work to professional communities and wider…
Who spoke and when? – Speaker diarization without speech recognition
Imagine that someone has recorded a series of hundreds of meetings and your task is to find out who spoke where and when. Sounds like a lot of transcription work,…
Automatic metadata high up in the mountains
The European Broadcasting Union EBU’s annual Metadata Network MDN Workshop 2019 was organised in June 2019 in Geneva. It gathered 88 experts from different media companies, research institutes and vendor…
More from the blog