Computational Methods for Linguistic and Behavioral Research
Language is a core human cognitive ability and a shared cognitive technology that allows us to represent, store, and transmit information across space and time. Researchers investigating how individuals process, produce, and understand language, and how language functions in groups, rely on accurate measures on how language is used and on methods that allow them to collect and analyze experimental and naturally occurring language data.
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dr. Emmanuel Keuleers
Principal Investigator
In our lab, we develop methods and resources that facilitate experimental and applied linguistic and behavioral research. Some of our focus areas are:
- Collection and validation of lexical statistics, e.g., how often words occur, how often they are used, how well they are known, etc.
- Development and validation of proxy measures for word meaning, such as word embeddings derived from computational language models.
- Methods for collecting large amounts of behavioral measures of language processing (megastudies and crowdsourcing).
- Methods for stimulus presentation, optimal data collection, and data analysis.
- Computational methods to generate imaginary words and characters.
- Unsupervised methods for hierarchical language segmentation.
Our theoretical focus is on modeling language as a complex cognitive technology, with written language a the primary focus of investigation. Some of our current research interests are how different scripts shape different semantic representations, how network dynamics can both influence language change and lead to language homogenization, and the effect of artificial language users on individual and group language development.
Partners
- JADS
- TU/e
- Ghent University
- South China Normal University
- KPN Responsible AI Lab (ICAI)
- Masterminds Lab (ICAI)
- Uitgeverij Zwijsen