The scientific and technological objectives of QALL-ME pursued three crucial directions: multilingual open domain QA, user-driven and context-aware QA, and learning technologies for QA. The specific research objectives of the project included state-of-art advancements in the complexity of the questions handled by the system(e.g. how questions); the development of a web-based architecture for cross-language QA (i.e. question in one language, answer in a different language); the realization of real-time QA systems for concrete applications; the integration of the temporal and spatial context both for question interpretation and for answer extraction; the development of a robust framework for applying minimally supervised machine learning algorithms to QA tasks; and the integration of mature technologies for automatic speech recognition within the open domain question answering framework.
The AI4Culture Platform is here!
Thrilled to officially launch the @AI4Culture platform: an exciting opportunity to empower #CulturalHeritage with #AI tools & resources.
Read more on @Europeanaeu & discover it now:
https://shorturl.at/8ZQbg
I’m honestly impressed by the quantity and quality of PhD students at @FBK_research working on #NLProc related topics… we have a very promising new generation of young researchers ready to take the stage #LT2024FBK
#LT2024FBK day. Some pictures of our students from LanD presenting their work. Well done folks!
3What a day! We've had a great line-up of speakers today, starting from @barbara_plank's keynote speech to all the presenters at the Language Technology day in @FBK_research #LT2024FBK