thesis available: Division of labor in visual word recognition

[Mike Harm]

Hi.

My Ph.D. thesis is now publicly available.  



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          DIVISION OF LABOR IN A COMPUTATIONAL MODEL OF 
                   VISUAL WORD RECOGNITION


                       Michael W. Harm
               University of Southern California
                Department of Computer Science
                        August, 1998


Abstract:

How do we compute the meanings of written words?  For decades, the
basic mechanisms underlying visual word recognition have remained
controversial.  The intuitions of educators and policy makers, and the
existing empirical evidence have resulted in contradictory
conclusions, particularly about the role of the sound structure of
language (phonology) in word recognition.  To explore the relative
contributions of phonological and direct information in word
recognition, a large scale connectionist model of visual word
recognition was created containing orthographic, semantic and
phonological representations. The behavior of the model is analyzed
and explained in terms of redundant representations, the development
of dynamic attractors in representational space, the time course of
activation and processing within such networks, and demands of the
reading task itself.  The different patterns of results that have been
obtained in previous behavioral studies are explained by appeal to
stimulus composition and properties of a common experimental paradigm.
A unified explanation of a wide range of empirical phenomena is
presented.

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PDF version (you may need acrobat 3.0):

    ftp://siva.usc.edu/pub/coglab/mharm/thesis.pdf  (631 kb)

Compressed postscript version:

    ftp://siva.usc.edu/pub/coglab/mharm/thesis.ps.Z  (381 kb)


It's about 120 pages.


Cheers,

Mike Harm
mharm at cnbc.cmu.edu
Center for the Neural Basis of Cognition
Carnegie Mellon University
http://www.cnbc.cmu.edu/~mharm/
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    At midnight, all the agents,
    And the superhuman crew,
    Come out and round up everyone,
    That knows more than they do.

                  Bob Dylan,  "Desolation Row"