Statistical Learning and Language Acquisition / / ed. by John N. Williams, Patrick Rebuschat.

Open publication This volume brings together contributors from cognitive psychology, theoretical and applied linguistics, as well as computer science, in order to assess the progress made in statistical learning research and to determine future directions. An important objective is to critically exa...

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Bibliographic Details
Superior document:Title is part of eBook package: De Gruyter DGBA Backlist Complete English Language 2000-2014 PART1
MitwirkendeR:
HerausgeberIn:
Place / Publishing House:Berlin ;, Boston : : De Gruyter Mouton, , [2012]
©2011
Year of Publication:2012
Language:English
Series:Studies in Second and Foreign Language Education [SSFLE] , 1
Online Access:
Physical Description:1 online resource (511 p.)
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Table of Contents:
  • Frontmatter
  • Preface
  • List of contributors
  • Table of contents
  • Introduction: Statistical learning and language acquisition
  • Statistical-sequential learning in development
  • Bootstrapping language: Are infant statisticians up to the job?
  • Sensitivity to statistical information begets learning in early language development
  • Word segmentation: Trading the (new, but poor) concept of statistical computation for the (old, but richer) associative approach
  • The road to word class acquisition is paved with distributional and sound cues
  • Linguistic constraints on statistical learning in early language acquisition
  • The potential contribution of statistical learning to second language acquisition
  • Statistical learning and syntax: What can be learned, and what difference does meaning make?
  • Statistical construction learning: Does a Zipfian problem space ensure robust language learning?
  • Can we enhance domain-general learning abilities to improve language function?
  • Conscious versus unconscious learning of structure
  • How implicit is statistical learning?
  • What Bayesian modelling can tell us about statistical learning: What it requires and why it works
  • Evolutionary perspectives on statistical learning
  • Statistical learning: What can music tell us?
  • ‘‘I let the music speak’’: Cross-domain application of a cognitive model of musical learning
  • Index