A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Neural Quality Estimation of Grammatical Error Correction
2018
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Grammatical error correction (GEC) systems deployed in language learning environments are expected to accurately correct errors in learners' writing. However, in practice, they often produce spurious corrections and fail to correct many errors, thereby misleading learners. This necessitates the estimation of the quality of output sentences produced by GEC systems so that instructors can selectively intervene and re-correct the sentences which are poorly corrected by the system and ensure that
doi:10.18653/v1/d18-1274
dblp:conf/emnlp/ChollampattN18
fatcat:3qblkfwdjnd7lnjjtjumpvsir4