Modeling human sentence-processing can help us both better understand how the brain processes language, and also help improve user interfaces. For example, our systems could compare different (computer-generated) sentences and produce ones that are easiest to understand.

I will talk about my work on evaluating theories about syntactic processing difficulty on a large eye-tracking corpus, and present a model of sentence processing which uses an incremental, fully connected parsing strategy.

Speaker: Vera Demberg
Vera Demberg is a Ph.D. student in Computational Linguistics from the University of Edinburgh, Scotland. Her research focus is on building computational models of human sentence processing.

Vera obtained a Diplom (MSc) in Computational Linguistics from Stuttgart University, and a MSc in Artificial Intelligence from the University of Edinburgh. She has published papers in a number of top venues for language processing and psycholinguistic research, including ACL, EACL, CogSci and Cognition.

For her PhD research, she's been awarded the AMLaP Young Scientist Award for best platform presentation by a junior scientist. She was a finalist for the Google Europe Anita Borg Memorial Scholarship in 2007.