Paper: Native Language Detection with Tree Substitution Grammars

ACL ID P12-2038
Title Native Language Detection with Tree Substitution Grammars
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2012
Authors

We investigate the potential of Tree Substitu- tion Grammars as a source of features for na- tive language detection, the task of inferring an author?s native language from text in a dif- ferent language. We compare two state of the art methods for Tree Substitution Grammar induction and show that features from both methods outperform previous state of the art results at native language detection. Further- more, we contrast these two induction algo- rithms and show that the Bayesian approach produces superior classification results with a smaller feature set.