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Kolodny, Oren; Lotem, Arnon; Edelman, Shimon – Cognitive Science, 2015
We introduce a set of biologically and computationally motivated design choices for modeling the learning of language, or of other types of sequential, hierarchically structured experience and behavior, and describe an implemented system that conforms to these choices and is capable of unsupervised learning from raw natural-language corpora. Given…
Descriptors: Grammar, Natural Language Processing, Computer Mediated Communication, Graphs
Ambridge, Ben; Rowland, Caroline F.; Pine, Julian M. – Cognitive Science, 2008
According to Crain and Nakayama (1987), when forming complex yes/no questions, children do not make errors such as "Is the boy who smoking is crazy?" because they have innate knowledge of "structure dependence" and so will not move the auxiliary from the relative clause. However, simple recurrent networks are also able to avoid…
Descriptors: Children, Language Processing, Language Patterns, Linguistic Input