Paper: A Feedback-Augmented Method For Detecting Errors In The Writing Of Learners Of English

ACL ID P06-1031
Title A Feedback-Augmented Method For Detecting Errors In The Writing Of Learners Of English
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2006
Authors

This paper proposes a method for detect- ing errors in article usage and singular plu- ral usage based on the mass count distinc- tion. First, it learns decision lists from training data generated automatically to distinguish mass and count nouns. Then, in order to improve its performance, it is augmented by feedback that is obtained from the writing of learners. Finally, it de- tects errors by applying rules to the mass count distinction. Experiments show that it achieves a recall of 0.71 and a preci- sion of 0.72 and outperforms other meth- ods used for comparison when augmented by feedback.