PsychoCompLA-2007 (previous meetings: PsychoCompLA-2004, PsychoCompLA-2005)

Organized by the CUNY-CoLAG research group

August 1st at CogSci 2007 - Nashville, Tennessee

Workshop Topic The workshop is devoted to psychologically-motivated computational models of language acquisition. That is, models that are compatible with research in psycholinguistics, developmental psychology and linguistics.

Workshop Program Proceedings (PDF)

Invited Presentations:

Statistical language learning: Computational and maturational constraints

Elissa Newport, University of Rochester

The next challenges in unsupervised language acquisition: dependencies and complex sentences

Shimon Edelman, Cornell University

Indirect evidence and the poverty of the stimulus

Amy Prefors, MIT

Terry Regier, University of Chicago

Josh Tenenbaum, MIT

Lexical learning and lexical diffusion

Charles D. Yang, University of Pennsylvania

Learnable representations of languages: something old and something new

Alex Clark, Royal Holloway University College London

Transformational Networks

Bob Frank, John Hopkins University

The Great (Penn Treebank) Robbery: When statistics is not enough

Robert C. Berwick, MIT

Michael Coen, University of Wisconsin

Sandiway Fong, University of Arizona

Partha Niyogi, University of Chicago

Workshop History This is the third meeting of the Psychocomputational Models of Human Language Acquisition workshop following PsychoCompLA-2004, held in Geneva, Switzerland as part of the 20th International Conference on Computational Linguistics (COLING 2004) and PsychoCompLA-2005 as part of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL-2005) held in Ann Arbor, Michigan where the workshop shared a joint session with the Ninth Conference on Computational Natural Language Learning (CoNLL-2005).

Workshop Description This workshop will present research and foster discussion centered around psychologically-motivated computational models of language acquisition, with an emphasis on the acquisition of syntax. In recent decades there has been a thriving research agenda that applies computational learning techniques to emerging natural language technologies and many meetings, conferences and workshops in which to present such research. However, there have been only a few (but growing number of) venues in which psychocomputational models of how humans acquire their native language(s) are the primary focus. By psychocomputational models we mean models that are compatible with, or might inform research in psycholinguistics, developmental psychology or linguistics.

Psychocomputational models of language acquisition are of particular interest in light of recent results in developmental psychology that suggest that very young infants are adept at detecting statistical patterns in an audible input stream. Though, how children might plausibly apply statistical 'machinery' to the task of grammar acquisition, with or without an innate language component, remains an open and important question. One effective line of investigation is to computationally model the acquisition process and determine interrelationships between a model and linguistic or psycholinguistic theory, and/or correlations between a model's performance and data from linguistic environments that children are exposed to.

Although there has been a significant amount of presented research targeted at modeling the acquisition of word categories, morphology and phonology, research aimed at modeling syntax acquisition has just begun to emerge.

Workshop Organizer: William Gregory Sakas, City University of New York (sakas at hunter.cuny.edu)
Workshop Co-organizer: David Guy Brizan, City University of New York (dbrizan at gc.cuny.edu)

Submission details Authors are invited to submit abstracts of 1 page plus 1 page for data and other supplementary materials. Abstracts should be anonymous, clearly titled and no more than 500 words in length. Text of the abstract should fit on one page, with a second page for examples, table, figures, references, etc. The following formats are accepted: PDF, PS, and MS Word. Please include a cover sheet (as a separate attachment) containing the title of your submission, your name, contact details and affiliation. Please send your submission electronically to Psycho.Comp@hunter.cuny.edu. The accepted abstracts will appear in the online workshop proceedings. Full papers will be considered for a submission for a special issue of a Cognitive Science Society Journal in the fall.

Submission deadline (PAST) May 22, 2007

Topics and Goals Abstracts that present research on (but not necessarily limited to) the following topics are welcome:

· Models that address the acquisition of word-order;

· Models that combine parsing and learning;

· Formal learning-theoretic and grammar induction models that incorporate psychologically plausible constraints;

· Comparative surveys that critique previously reported studies;

· Models that have a cross-linguistic or bilingual perspective;

· Models that address learning bias in terms of innate linguistic knowledge versus statistical regularity in the input;

· Models that employ language modeling techniques from corpus linguistics;

· Models that employ techniques from machine learning;

· Models of language change and its effect on language acquisition or vice versa.

· Models that employ statistical/probabilistic grammars;

· Computational models that can be used to evaluate existing linguistic or developmental theories (e.g., principles & parameters, optimality theory, construction grammar, etc.)

· Empirical models that make use of child-directed corpora such as CHILDES.

This workshop intends to bring together researchers from cognitive psychology, computational linguistics, other computer/mathematical sciences, linguistics and psycholinguistics working on all areas of language acquisition. Diversity and cross-fertilization of ideas is the central goal.

Contact: Psycho.Comp@hunter.cuny.edu

FYI, Related 2007 Meetings

Machine Learning and Cognitive Science of Language Acquisition 21-22 June, 2007

Cognitive Aspects of Computational Language Acquisition 29 June, 2007

Exemplar-Based Models of Language Acquisition and Use 6-17 August, 2007