Probabilistic Language Understanding

Course Description

The present course provides a practical introduction to the Bayesian Rational Speech Act modeling framework. Much work in formal, compositional semantics follows the tradition of positing systematic but inflexible theories of meaning. However, in practice, the meanings we derive from language are heavily dependent on nearly all aspects of context. To formally explain these nuanced aspects of meaning and better understand the compositional mechanism that delivers them, recent work in formal pragmatics recognizes semantics not as one of the final steps in meaning calculation, but rather as one of the first. Within the Rational Speech Act modeling framework, speakers and listeners reason about each other’s reasoning about the literal interpretation of utterances. The resulting interpretation necessarily depends on the literal interpretation of an utterance (i.e., on the semantics), but is not necessarily wholly determined by it. Rather than describing a pragmatic reasoning process, these models articulate and implement one, deriving both qualitative and quantitative predictions of human behavior. This course will introduce students to the basics of the modeling framework via hands-on practice. Students should expect to leave the course having gained the ability to 1) digest the primary modeling literature and 2) independently construct models of their own.

Area Tags: Pragmatics, Semantics, Computational Linguistics, Cognitive Science

Instructor: Gregory Scontras