Grammar Transfer in a Second Order Recurrent Neural Network
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 modified grammar. We show that a second order recurrent neural network is able to transfer grammatical knowledge from one language (generated by a Finite State Machine) to another language which differ both in vocabularies and syntax. Representa(cid:173) tion of the grammatical knowledge in the network is analyzed using linear discriminant analysis.
Cite
Text
Negishi and Hanson. "Grammar Transfer in a Second Order Recurrent Neural Network." Neural Information Processing Systems, 2001.Markdown
[Negishi and Hanson. "Grammar Transfer in a Second Order Recurrent Neural Network." Neural Information Processing Systems, 2001.](https://mlanthology.org/neurips/2001/negishi2001neurips-grammar/)BibTeX
@inproceedings{negishi2001neurips-grammar,
title = {{Grammar Transfer in a Second Order Recurrent Neural Network}},
author = {Negishi, Michiro and Hanson, Stephen J.},
booktitle = {Neural Information Processing Systems},
year = {2001},
pages = {67-73},
url = {https://mlanthology.org/neurips/2001/negishi2001neurips-grammar/}
}