Using Classifier Features for Studying the Effect of Native Language on the Choice of Written Second Language Words
Oren Tsur and Ari Rappoport
In: ACL 2007 Workshop on Cognitive Aspects of Computational Language Acquisition, 21 June - 30 June 2007, Prague, Czech Republic.
We apply modern statistical NLP techniques
to study language transfer, a major issue in
the theory of Second Language Acquisition
(SLA). Using an SVM for the problem of
native language classification, we show that
a careful analysis of the effects of various
features can lead to substantial scientific insights.
In particular, we demonstrate that
character bi-grams alone allow classification
levels of about 66% for a 5-class task even
when content and function word differences
are accounted for. We hypothesize that the
phonology of a native language has a strong
effect on the word choice of people writing
in a second language.
|EPrint Type:||Conference or Workshop Item (Paper)|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Subjects:||Natural Language Processing|
|Deposited By:||Oren Tsur|
|Deposited On:||11 February 2008|