Constructing grammar: A computational model of the emergence of early constructions
Nancy Chih-Lin Chang
EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2009-24
February 5, 2009
http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-24.pdf
Abstract Constructing grammar: A computational model of the emergence of early constructions by Nancy Chih-lin Chang Doctor of Philosophy in Computer Science University of California, Berkeley Professor Jerome A. Feldman, Chair In this thesis I explore and formalize the view that grammar learning is driven by meaningful language use in context. On this view, the goal of a first language learner is to become a better language user—in particular, by acquiring linguistic constructions (structured mappings between form and meaning) that facilitate successful communication. I present a computational model in which all aspects of the language learning problem are reformulated in line with these assumptions. The representational basis of the model is a construction grammar formalism that captures constituent structure and relational constraints, both within and across the domains of form and meaning. This formalism plays a central role in two processes: language understanding, which uses constuctions to interpret utterances in context; and language learning, which seeks to improve comprehension by making judicious changes to the current set of constructions. The resulting integrated model of language structure, use and acquisition provides a cognitively motivated and computationally precise account of how children acquire their earliest multiword constructions. I define a set of operations for proposing new constructions, either to capture contextually available mappings not predicted by the current grammar, or to reorganize existing constructions. Candidate constructions are evaluated using a minimum description length criterion that balances a structural bias toward simpler grammars against a data-driven bias toward more specific grammars. When trained with a corpus of child-directed utterances annotated with situation descriptions, the model gradually acquires the concrete word combinations and item-based constructions that constitute the first steps toward adult language.
Advisor: Jerome A. Feldman
BibTeX citation:
@phdthesis{Chang:EECS-2009-24,
Author = {Chang, Nancy Chih-Lin},
Title = {Constructing grammar: A computational model of the emergence of early constructions},
School = {EECS Department, University of California, Berkeley},
Year = {2009},
Month = {Feb},
URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-24.html},
Number = {UCB/EECS-2009-24},
Abstract = {Abstract
Constructing grammar: A computational model of the emergence of early constructions
by
Nancy Chih-lin Chang
Doctor of Philosophy in Computer Science
University of California, Berkeley
Professor Jerome A. Feldman, Chair
In this thesis I explore and formalize the view that grammar learning is driven by meaningful language
use in context. On this view, the goal of a first language learner is to become a better language
user—in particular, by acquiring linguistic constructions (structured mappings between form and
meaning) that facilitate successful communication. I present a computational model in which all
aspects of the language learning problem are reformulated in line with these assumptions. The
representational basis of the model is a construction grammar formalism that captures constituent
structure and relational constraints, both within and across the domains of form and meaning. This
formalism plays a central role in two processes: language understanding, which uses constuctions
to interpret utterances in context; and language learning, which seeks to improve comprehension
by making judicious changes to the current set of constructions.
The resulting integrated model of language structure, use and acquisition provides a cognitively
motivated and computationally precise account of how children acquire their earliest multiword
constructions. I define a set of operations for proposing new constructions, either to capture
contextually available mappings not predicted by the current grammar, or to reorganize existing
constructions. Candidate constructions are evaluated using a minimum description length criterion
that balances a structural bias toward simpler grammars against a data-driven bias toward more
specific grammars. When trained with a corpus of child-directed utterances annotated with situation
descriptions, the model gradually acquires the concrete word combinations and item-based
constructions that constitute the first steps toward adult language.}
}
EndNote citation:
%0 Thesis %A Chang, Nancy Chih-Lin %T Constructing grammar: A computational model of the emergence of early constructions %I EECS Department, University of California, Berkeley %D 2009 %8 February 5 %@ UCB/EECS-2009-24 %U http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-24.html %F Chang:EECS-2009-24