WS22/23: Cognitive Models of Human Language Understanding
In this seminar, we will take a look at how psycholinguistic theories can be formalized as computational models and how these models can help specify and improve those theories and generate predictions. The first two sessions will give participants an overview of the modeling frameworks – the cognitive modeling framework Adaptive Control of Thought – Rational (ACT-R) and Bayesian probabilistic models, including the Rational Speech Act (RSA) framework. Each participant will present a paper on a seminar-relevant topic, including but not limited to modeling the role of working memory and processing speed in language comprehension and production, eye movements and sentence comprehension, listener adaptation and rational overspecification.
The goal of the seminar is to take stock of the range of approaches used in computational cognitive modeling and the recent applications of cognitive modeling to psycholinguistic and pragmatic phenomena. At the end of the course, participants may choose between a more traditional term paper and a project modeling a psycholinguistic phenomenon of their choice in one of the frameworks discussed in the seminar, after consultation with the instructors.
|taught by:||Alexandra Mayn and Margarita Ryzhova|
|located in:||In C7.2, Seminar room 1.05|
We will use Microsoft Teams for communication.
|sign-up:||Please fill out this short form to be added to the seminar team. Please note that you will also need to register for the seminar on LSF.|
ATTENTION: The sign-up form does not replace the registration to examination on LSF.
The first two lectures will introduce students to the fundamentals of computational modeling, and each subsequent session will feature a student presentation and discussion.
Winter break: Mon, 26.12.2022 – Fri, 30.12.2022
|credits:||4 CP (presentation only), 7 CP (presentation + final paper/project)|
• 4 CP (presentation only): 70% Presentation, 30% homework and contribution to discussion
• 7 CP (presentation + term paper or project): 40% Presentation, 40% Final paper/project, 20% homework and contribution to discussion
|suited for:||B.Sc. in Computational Linguistics|
B.Sc. in Language Science and Technlogy
M.Sc. in Computational Linguistics
M.Sc. in Language Science and Technology
|more details:||In LSF|