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A Bayesian Account of Conversational Inferences

Date and Time: 
Thursday, February 12, 2015. 04:00 PM - 05:30 PM
Meeting Location: 
Building 460, Room 126
Meeting Description: 
About the speaker:
Dan Grodner is an Associate Professor of Psychology at Swarthmore College.
 
Meeting description:
Much if not most of the meaning that speakers convey with their words is implicit. The standard account of how perceivers recover implicit content is via a process of rational psychosocial inference: Perceivers appeal to a set of maxims to formulate a generative model of a cooperative speaker (Grice, 1975).  This view requires that perceivers reason about the communicative intention of the speaker's speech act (the whole utterance).  Over the past 10-15 years, a number of researchers have argued that the standard account is inadequate because it cannot account for the existence of so-called local implicatures.  These are cases where an inference appears to be generated within an embedded constituent within an utterance (e.g., Chierchia, Fox & Spector, 2012; Chemla & Spector 2011, Gajewsky & Sharvit, 2012).   I will describe a probabilistic model that follows from the assumptions of the standard Gricean account (Russell 2012) and provide experimental evidence that supports it.  I will show how this model can explain seemingly local implicatures without appealing to special grammatical operators. In addition to providing a formalization of Gricean reasoning, this approach allows us to preserve the traditional division of labor between semantics and pragmatics.  The present approach is similar in spirit to other recent probabilistic approaches (e.g., Goodman & Stuhlmueller 2013) but covers different empirical territory and differs in its mechanics.
 
 (Joint work with Ben Russell)

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