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Exploiting Multiple Sources of Information in Learning an Artificial Language: Human Data and Modeling
Cognitive Science 34 (2):255-285 (2010)
Abstract
This article has no associated abstract. (fix it)DOI
10.1111/j.1551-6709.2009.01074.x
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Citations of this work
Zipfian frequency distributions facilitate word segmentation in context.Chigusa Kurumada, Stephan C. Meylan & Michael C. Frank - 2013 - Cognition 127 (3):439-453.
What Mechanisms Underlie Implicit Statistical Learning? Transitional Probabilities Versus Chunks in Language Learning.Pierre Perruchet - 2019 - Topics in Cognitive Science 11 (3):520-535.
Pre-linguistic segmentation of speech into syllable-like units.Okko Räsänen, Gabriel Doyle & Michael C. Frank - 2018 - Cognition 171 (C):130-150.
iMinerva: A Mathematical Model of Distributional Statistical Learning.Erik D. Thiessen & Philip I. Pavlik - 2013 - Cognitive Science 37 (2):310-343.
How Many Mechanisms Are Needed to Analyze Speech? A Connectionist Simulation of Structural Rule Learning in Artificial Language Acquisition.Aarre Laakso & Paco Calvo - 2011 - Cognitive Science 35 (7):1243-1281.
References found in this work
"Schema abstraction" in a multiple-trace memory model.Douglas L. Hintzman - 1986 - Psychological Review 93 (4):411-428.
Implicit learning and statistical learning: One phenomenon, two approaches.Pierre Perruchet & Sebastien Pacton - 2006 - Trends in Cognitive Sciences 10 (5):233-238.
Infants rapidly learn word-referent mappings via cross-situational statistics.Linda Smith & Chen Yu - 2008 - Cognition 106 (3):1558-1568.
Simplicity: A unifying principle in cognitive science?Nick Chater & Paul Vitányi - 2003 - Trends in Cognitive Sciences 7 (1):19-22.
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