Fragment Grammars: Exploring Computation and Reuse in Language

Title:	Fragment Grammars: Exploring Computation and Reuse in Language
Author:	Tenenbaum, Joshua B.; Goodman, Noah D.; O'Donnell, Timothy J.
Other Contributors:	Computational Cognitive Science
Advisor:	Joshua Tenenbaum
Issue Date:	2009-03-31
Abstract:	Language relies on a division of labor between stored units and structure building operations which combine the stored units into larger structures. This division of labor leads to a tradeoff: more structure-building means less need to store while more storage means less need to compute structure. We develop a hierarchical Bayesian model called fragment grammar to explore the optimum balance between structure-building and reuse. The model is developed in the context of stochastic functional programming (SFP) and in particular using a probabilistic variant of Lisp known as the Church programming language (Goodman, Mansinghka, Roy, Bonawitz, & Tenenbaum, 2008). We show how to formalize several probabilistic models of language structure using Church, and how fragment grammar generalizes one of them---adaptor grammars (Johnson, Griffiths, & Goldwater, 2007). We conclude with experimental data with adults and preliminary evaluations of the model on natural language corpus data.
URI:	http://hdl.handle.net/1721.1/44963
Series/Report no.:	MIT-CSAIL-TR-2009-013
Keywords:	Reuse, Language, Stochastic Memoization, Stochastic Functional Programming, Lexicon, Hierarchical Bayes

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