In this course you will learn:|
- what the basic concepts, results and debates are in the field of computational psycholinguistics
- to identify the core properties, strengths and weaknesses of different modelling approaches
- to critically assess computational models and the claims arising from them
- how to develop and/or evaluate a computational psycholinguistic model
Computational psycholinguists develop computational models that simulate aspects of the human language system, for example: learning word meaning from large amounts of language input, assigning syntactic structures to sentences, or generating sentences given the intended meaning. A successful model can explain findings from human experiments and thereby increases our understanding of the human cognitive system. In this course, we will discuss the properties of different model types, look into the details of some of the most important models proposed in the literature, and gain hands-on experience with the development and/or evaluation of a computational psycholinguistic model.|
Basic knowledge of Python programming is required for the practical assignments. If you have experience with another programming language, you should be able to quickly learn enough Python by self study.