Paper: Generating artificial errors for grammatical error correction

ACL ID E14-3013
Title Generating artificial errors for grammatical error correction
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

This paper explores the generation of ar- tificial errors for correcting grammatical mistakes made by learners of English as a second language. Artificial errors are in- jected into a set of error-free sentences in a probabilistic manner using statistics from a corpus. Unlike previous approaches, we use linguistic information to derive error generation probabilities and build corpora to correct several error types, including open-class errors. In addition, we also analyse the variables involved in the selec- tion of candidate sentences. Experiments using the NUCLE corpus from the CoNLL 2013 shared task reveal that: 1) training on artificially created errors improves pre- cision at the expense of recall and 2) dif- ferent types of linguistic information are better suited for correcting diff...