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We try to understand the computational principles underlying natural language understanding by humans and machines, the neural implementation of these principles, their evolutionary origins and their usefulness in language technology.
We carry out research at the interface of computational linguistics, cognitive science and AI to study language in interaction. Topics include: semantics & pragmatics, visually grounded language, conversational agents, language variation & change.
We investigate language and communication in autistic individuals. This includes developing new (experimental) methods to adequately investigate the diverse autistic population across the life-span.
We develop machine learning methods for natural language processing, especially for semantic tasks such as question answering, information extraction, and semantic parsing. We also work on interpretability and controlability of deep learning models.
People often reason contrary to the prescriptions of classical logic. We study such cases and hypothesise that they are a consequence of a tendency in human cognition to neglect empty representations.
Our research focus lies in computationally modelling the production, comprehension, acquisition and diachronic development of phonology and phonetics, and in supply experimental evidence for those.
Our research concentrates on statistical models for structured language processing with application to machine translation, paraphrasing, semantic and morpho-syntactic parsing, and statistical learning for NLP.
The Visualisation Lab provides access to facilities and resources for students and researchers who want to work on interactive visual systems. The lab specialises on scientific visualisation, high-performance interactive graphics and XR/MR/VR/AR.