Paper: Detecting Learner Errors in the Choice of Content Words Using Compositional Distributional Semantics

ACL ID C14-1164
Title Detecting Learner Errors in the Choice of Content Words Using Compositional Distributional Semantics
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

We describe a novel approach to error detection in adjective?noun combinations. We present and release a new dataset of annotated errors where the examples are extracted from learner texts and annotated with error types. We show how compositional distributional semantic approaches can be applied to discriminate between correct and incorrect word combinations from learner data. Finally, we show how the output of the compositional distributional semantic models can be used as features in a classifier yielding good precision and accuracy.