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Bigrams and the Richness of the Stimulus
Author(s) -
Kam XuânNga Cao,
Stoyneshka Iglika,
Tornyova Lidiya,
Fodor Janet D.,
Sakas William G.
Publication year - 2008
Publication title -
cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
DOI - 10.1080/03640210802067053
Subject(s) - bigram , computer science , sentence , stimulus (psychology) , grammar , cognitive psychology , artificial intelligence , natural language processing , psychology , linguistics , trigram , philosophy
Recent challenges to Chomsky's poverty of the stimulus thesis for language acquisition suggest that children's primary data may carry “indirect evidence” about linguistic constructions despite containing no instances of them. Indirect evidence is claimed to suffice for grammar acquisition, without need for innate knowledge. This article reports experiments based on those of Reali and Christiansen (2005), who demonstrated that a simple bigram language model can induce the correct form of auxiliary inversion in certain complex questions. This article investigates the nature of the indirect evidence that supports this learning, and assesses how reliably it is available. Results confirm the original finding for one specific sentence type but show that the model's success is highly circumscribed. It performs poorly on inversion in related constructions in English and Dutch. Because other, more powerful statistical models have so far been shown to succeed only on the same limited subset of cases as the bigram model, it remains to be seen whether stimulus richness can be substantiated more generally.