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Grammatical error correction in low error density domains: a new benchmark and analyses
File(s)
2020.emnlp-main.680.pdf (350.07 KB)
Published version
OA Location
Author(s)
Flachs, Simon
Lacroix, Ophélie
Yannakoudakis, Helen
Rei, Marek
Søgaard, Anders
Type
Conference Paper
Abstract
Evaluation of grammatical error correction (GEC) systems has primarily focused on essays written by non-native learners of English, which however is only part of the full spectrum of GEC applications. We aim to broaden the target domain of GEC and release CWEB, a new benchmark for GEC consisting of website text generated by English speakers of varying levels of proficiency. Website data is a common and important domain that contains far fewer grammatical errors than learner essays, which we show presents a challenge to state-of-the-art GEC systems. We demonstrate that a factor behind this is the inability of systems to rely on a strong internal language model in low error density domains. We hope this work shall facilitate the development of open-domain GEC models that generalize to different topics and genres.
Date Issued
2020-11
Date Acceptance
2020-11-01
Citation
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.8467-8478
URI
URL
DOI
Publisher
Association for Computational Linguistics
Start Page
8467
End Page
8478
Journal / Book Title
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Volume
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Copyright Statement
© 2020 Association for Computational Linguistics. Materials published in or after 2016 are licensed on a Creative Commons Attribution 4.0 International License.
License URL
Identifier
https://www.aclweb.org/anthology/2020.emnlp-main.680/
Source
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Publication Status
Published
Start Date
2020-11-16
Finish Date
2020-11-20
Date Publish Online
2020-11-16