Language and Speech Technology
We research and develop computational methods for the comprehension and generation of text and speech. We evaluate these methods intrinsically, and test their utility in real-world applications (such as automatic speech recognition in realistic environments, and text mining in historical collections and social media). We also connect these computational models to models in theoretical and applied linguistics, psycholinguistics, and communication studies. The group works with ‘big data' and methods that learn computational models from data, while at the same time the proper development of information systems demands a hybridization of data-driven learning and ‘rich priors' from the domain or context.
- Beeksma et al. (2019). Predicting life expectancy with a long short-term memory recurrent neural network using electronic medical records.
- Merkx & Frank (2019). Learning semantic sentence representations from visually grounded language without lexical knowledge.
- Oostdijk et al. (2019). Fora fueling the finding of fortified dietary supplements. An exploratory study directed at monitoring the internet for contaminated food supplements based on the reported effects of their users.
The PIs of this research group are Martha Larson and Nelleke Oostdijk.
An overview of our members can be found by clicking the link below.