Statistical learning and language acquisition

Statistical learning and language acquisition edited by Patrick Rebuschat, John N. Williams.

This volume brings together contributors from cognitive psychology, theoretical and applied linguistics, as well as computer science, in order to assess the progress and future directions of statistical learning research. The textcritically examines the role of statistical learning in language acqui...

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Bibliographic Details
Main Author: Williams, John N.
Corporate Author: ProQuest (Firm)
Other Authors: Rebuschat, Patrick, Williams, John, 1960-
Format: eBook
Language:English
Published: Boston : De Gruyter Mouton, c2012.
Series:Studies in second and foreign language education ; 1.
Subjects:
Linguistics > Statistical methods.
Psycholinguistics.
Theoretical linguistics.
Applied linguistics.
Language acquisition.
psycholinguistics.
applied linguistics.
LANGUAGE ARTS & DISCIPLINES > Linguistics > Psycholinguistics.
Psycholinguistics
Linguistics > Statistical methods
Applied linguistics
Language acquisition
Online Access:Click for online access
Table of Contents:
  • Preface; List of contributors; 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 acquisitionStatistical 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.

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