Title
Using first and second language models to correct preposition errors in second language authoring
Abstract
In this paper, we investigate a novel approach to correcting grammatical and lexical errors in texts written by second language authors. Contrary to previous approaches which tend to use unilingual models of the user's second language (L2), this new approach uses a simple roundtrip Machine Translation method which leverages information about both the author's first (L1) and second languages. We compare the repair rate of this roundtrip translation approach to that of an existing approach based on a unilingual L2 model with shallow syntactic pruning, on a series of preposition choice errors. We find no statistically significant difference between the two approaches, but find that a hybrid combination of both does perform significantly better than either one in isolation. Finally, we illustrate how the translation approach has the potential of repairing very complex errors which would be hard to treat without leveraging knowledge of the author's L1.
Year
Venue
Keywords
2009
BEA@NAACL
language authoring,l2 model,new approach,roundtrip translation approach,translation approach,unilingual model,novel approach,preposition error,language model,existing approach,language author,previous approach,simple roundtrip machine translation,machine translation
Field
DocType
Citations 
Computer science,Second language,Machine translation,Speech recognition,Repair rate,Natural language processing,Transfer-based machine translation,Artificial intelligence,Syntax
Conference
12
PageRank 
References 
Authors
0.68
9
2
Name
Order
Citations
PageRank
Matthieu Hermet1241.94
Alain Désilets213615.99