RESEARCH TOPICS
I am interested in the complex interplay of meaning and form and how it can be modeled and explained.
NLG
Natural Language Generation (NLG) is the branch of Computational Linguistics that deals with the automatic generation of texts from non-linguistic data. These texts must be tailored to the commmunicative skills and specific information needs of the intended user, which requires considering a variety of pragmatic conditions for content selection and grammatical realisation.
Dialogue
Actually, NLG is concerned with dialogical situations, since a NLG system should anticipate the user's needs and skills. Making the dialogical character of NLG explicit in, for example, question-answering systems, calls for various approaches to pragmatic modeling.
Current Projects
Propositional and Non-at-issue Content in Text Generation: Exploring the QUD Perspective (QUDGen). Funded by Deutsche Forschungsgemeinschaft (DFG); 2019-2022.
Former Projects
Bayesian Approaches to Preference-based Answer Generation in Dialogue (BAPAGiD). Funded by Deutsche Forschungsgemeinschaft (DFG); 2016-2018.