We are also involved in national and international standardisation activities around language and knowledge technologies as well as artificial intelligence at large. Other areas of work are the development and use of language technology platforms and the integration of our research work in an emerging strategic agenda for technology-enabled multilingualism and digital language equality in Europe. Among others, we use rule-based, data-driven neural and knowledge-based methods that combine their respective advantages by bridging between the symbolic and sub-symbolic levels. Within the topic field Language, Data and Knowledge Technologies we apply a holistic approach and actively work on all involved levels of technological components that are necessary to address a certain use case with a prototypical language technology demonstrator or with a deployed system ready for production use, especially with regard to applications in the professional context of digital content curation (curation technologies). Language, Data and Knowledge Technologies Applications of its technologies are in the fields of medicine, mobility, law, as well as machine translation. A main strength of SLT is its use of crowdsourcing for data generation, the creation of hybrid human-machine intelligence processes, as well as its focus on evaluation methodologies to which SLT constantly contributes with scientific publications as well as with international standards. Regarding chatbots, SLT concentrates on the quick bootstrapping of chatbots from knowledge graphs, also for industrial applications, as well as on the simulation of interaction behaviour. Regarding knowledge management, SLT brings together large multilingual resources in the European Language Grid and other European as well as national projects, focussing on data curation as well as research data management techniques. We know technology as the name technological know-how. ![]() Regarding information extraction, the main contributions are in the field of training on sparse data (addressed through sequential transfer learning (e.g., by Alt, 2020) or by multitask-learning (e.g., by Mittag, 2021), as well as on explainable AI (e.g., by Schwarzenberg, 2021). Speech for Students Speech on Technology for Students and Children 3 Minutes Speech on Technology We live in the 21st century, where we do all over work with the help of technology. ![]() Its focus is on information extraction from written text and from spoken language, on knowledge technologies, and on interactive chatbots. DFKI’s Speech and Language Technology Department (SLT) addresses the use of AI for analysing, generating and interacting through spoken and written language.
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