Special 1-day MIT Workshop: Where Does Syntax Come From? Have We All Been Wrong

[pcomp at hunter.cuny.edu]

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Call for Participation

Special 1-day MIT Workshop:

Where Does Syntax Come From? Have We All Been Wrong?

Cambridge, MA, October 19th, 2007

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When:

Friday, October 19th,  2007,  9 am - 5:30 pm
(refreshments  9-9:30; lunch 12:30-1:30; afternoon refreshments)

Where:

Massachusetts Institute of Technology
Room 34-401  (Grier Room), Cambridge, MA
http://whereis.mit.edu/map-jpg?mapterms=34-401&mapsearch=go

Who:

Noam Chomsky, MIT, 
  Remarks and Reflections
Sandiway Fong, University of Arizona,
  Statistical Natural Language Parsing: Reliable  
  Models of Language?
Lila Gleitman, University of Pennsylvania,
  Human Simulations of Language Learning
Howard Lasnik and Juan Uriagereka, University of Maryland,
  Structure Dependence, the Rational Learner, and  
  Putnam's 'Sane Person' 
Chris Manning, Stanford University, 
  Title TBA
Parta Niyogi, University of Chicago,
  The Computational Nature of Language Learning
William Gregory Sakas & Janet Dean Fodor, CUNY,
  'Ideal' Language Learning and The Psychological  
  Resource Problem
Josh Tennenbaum, Amy Perfors, MIT, & Terry Regier, University of Chicago,
  Explorations in Language Learnability Using  
  Probabilistic Grammars and Child-directed Speech

Registration:

No advance registration required, no fee - open to all.
Open roundtable discussion at the end of the day.

Organizers:

Robert C. Berwick, MIT, berwick at csail.mit.edu
Michael Coen, University of Wisconsin-Madison,
mhcoen at cs.wisc.edu

What:

The impetus for this workshop, borrowing from a recent review by
Yang in TICS (2004), is that "Recent demonstrations of statistical
learning in infants have reinvigorated the innateness versus learning
debate in language acquisition," particularly regarding syntax.
We aim to reexamine this issue in a single forum from the
computational, cognitive, and formal linguistics perspectives. Our
intent is to examine recent applications of statistical learning
theory to language acquisition.

That machine learning has something to offer in understanding
language acquisition is not in doubt.  However, we would like to
examine the basic premise that computational approaches should be
linguistically informed.  The hypothesis put forth is that statistical
approaches should work within the framework of classical linguistics
rather than supplant it.

The goal of this workshop is to examine this hypothesis critically,
be it wrong or right, and for each speaker to present evidence as
they see fit.