Paper: Role of Morpho-Syntactic Features in Estonian Proficiency Classification

ACL ID W13-1708
Title Role of Morpho-Syntactic Features in Estonian Proficiency Classification
Venue Innovative Use of NLP for Building Educational Applications
Session
Year 2013
Authors

We developed an approach to predict the pro- ficiency level of Estonian language learners based on the CEFR guidelines. We performed learner classification by studying morpho- syntactic variation and lexical richness in texts produced by learners of Estonian as a sec- ond language. We show that our features which exploit the rich morphology of Esto- nian by focusing on the nominal case and ver- bal mood are useful predictors for this task. We also show that re-formulating the classifi- cation problem as a multi-stage cascaded clas- sification improves the classification accuracy. Finally, we also studied the effect of training data size on classification accuracy and found that more training data is beneficial in only some of the cases.