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SUMMARY:Towards a model of morphological processing grounded in principles
  of discriminative learning - Harald Baayen\, Eberhard Karls University\, 
 Tuebing and University of Alberta
DTSTART:20140206T170000Z
DTEND:20140206T183000Z
UID:TALK47976@talks.cam.ac.uk
CONTACT:Alison Biggs
DESCRIPTION:Most research on morphological processing takes for granted th
 at morphemes (or exponents) exist\, and that they mediate lexical access i
 n speech production and language comprehension. It is only in subsymbolic 
 connectionist approaches that the theoretical concept of\nmorphemes (or ex
 ponents) plays no role. However\, after a series of promising studies prom
 oting the triangle model around the beginning of the present century\, rep
 orts of advances in this area have not been\nforthcoming.  As a consequenc
 e\, the scholarly discourse has drifted towards a view of morphological pr
 ocessing in which units such as morphemes (or exponents) are part and parc
 el of interactive activation networks.   \n\nIn this presentation\, I will
  present a new computational\nmodel for lexical processing that takes insp
 iration on the one hand from word and paradigm morphology\, and on the oth
 er hand from learning theory in psychology.  This new model is strictly a-
 morphous\, in the sense\nthat there are no units representing stems\, morp
 hemes\, or exponents. This does not mean that the model would be committed
  to subsymbolic representations.  To the contrary\, it's elementary units 
 are symbolic\, and range from units for melodies in articulatory scores to
  orthographic n-grams (typically letter bigrams or trigrams)\, and from le
 xeme nodes (nodes mediating between form and meaning for both  content wor
 ds and grammatical features such as plurality or tense) to units represent
 ing snippets of acoustic information (operationalized with diphones or dem
 i-syllables). These different sets of units participate in a range of netw
 orks\, the weights of which are estimated with the Rescorla-Wagner equatio
 ns from learning theory in psychology. Complementing networks that learn t
 he mapping from form to lexemes during listening and reading are are netwo
 rks learning the linear order of form units (n-graphs or n-phones) for com
 binations of lexemes. How this model works will be illustrated by taking a
  closer look at how it deals with inflectional morphology.  Examples from 
 Dutch and English will be discussed\, as well as examples from fusional an
 d agglutinative inflectional paradigms.
LOCATION:GR06/7 English Faculty\, Sidgwick Site
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