A study of grammar transfer in a second order recurrent network

M. Negishi, S. J. Hanson

Research output: Contribution to conferencePaperpeer-review

Abstract

It has been known that people, after being exposed to sentences generated by an artificial grammar, acquire implicit grammatical knowledge and are able to transfer the knowledge to inputs that are generated by a similar grammar. In the current paper, the ability of a second order recurrent neural network to transfer grammatical knowledge from one language (generated by a Finite State Machine) to another language is investigated, where the latter language differs in the syntax from the former language but uses the same vocabulary. We sought the measure of syntactic differences that affects the amount of transfer. The result shows that the effect is sensitive to the frequency of subsequences of words in the both languages.

Original languageEnglish (US)
Pages326-330
Number of pages5
StatePublished - 2001
EventInternational Joint Conference on Neural Networks (IJCNN'01) - Washington, DC, United States
Duration: Jul 15 2001Jul 19 2001

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'01)
Country/TerritoryUnited States
CityWashington, DC
Period7/15/017/19/01

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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