Course details


Computational Pragmatics

WS 2019 Prof. Dr. Michael Franke
B.Sc modules:
CS-BWP-CL - (Computational) Linguistics
CS-BWP-CNP - Cognitive (Neuro-)Psychology
KOGW-WPM-CL - Computational Linguistics
KOGW-WPM-KNP - Cognitive (Neuro-)Psychology
M.Sc modules:
CC-MWP-CL - Computational Linguistics
CS-MWP-CL - (Computational) Linguistics
CS-MWP-CNP - Cognitive (Neuro-)Psychology
KOGW-MWPM-CL - Major subject Linguistics and Computational Linguistics
KOGW-MWPM-KNP - Major subject Cognitive (Neuro-)Psychology

Doctorate program

Pragmatic reasoning is reasoning about what a speaker may have meant by an utterance at a given occasion. Pragmatic reasoning requires listeners to draw on different sources of possibly uncertain information from context and world-knowledge. Likewise, listeners need to reason about the speaker’s state of mind, her beliefs and goals, and possibly even about the speaker’s idiosyncratic use of language. To combine these sources of information about what the speaker has likely meant, we turn towards probabilistic modelling. This course will cover a sequence of increasingly complex models of listeners’ probabilistic inferences about speaker meaning, including applications to referential communication, scalar implicatures, vagueness, generics, politeness and tropes. To harness the complexity of pragmatic reasoning we will formulate models in a probabilistic programming language called WebPPL, which the course will introduce and which will help us understand the models and calculate their (quantitative) predictions. We will exercise with model code by going through selected chapters of the web-book ''. Preliminary dates & times: March 11 - 13 2020 March 19 - 20 2020 9am - 15pm each day