Results 11 to 20 of about 2,197,203 (280)
Minimally-Augmented Grammatical Error Correction [PDF]
Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019), 2019 There has been an increased interest in low-resource approaches to automatic grammatical error correction. We introduce Minimally-Augmented Grammatical Error Correction (MAGEC) that does not require any error-labelled data.
Grundkiewicz, Roman +3 more
core +5 more sources
Mining Error Templates for Grammatical Error Correction
CoRR, 2022 Some grammatical error correction (GEC) systems incorporate hand-crafted rules and achieve positive results. However, manually defining rules is time-consuming and laborious.
Jiang, Haochen +5 more
core +4 more sources
Grammatical Error Correction in Low-Resource Scenarios [PDF]
Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019), 2019 Grammatical error correction in English is a long studied problem with many existing systems and datasets. However, there has been only a limited research on error correction of other languages.
Náplava, Jakub, Straka, Milan
core +6 more sources
Human Evaluation of Grammatical Error Correction Systems [PDF]
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015 The paper presents the results of the first large-scale human evaluation of automatic grammatical error correction (GEC) systems. Twelve participating systems and the unchanged input of the CoNLL-2014 shared task have been reassessed in a WMT-inspired ...
Junczys-Dowmunt, Marcin +5 more
core +7 more sources
Enhancing Grammatical Error Correction Systems with Explanations
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023 Grammatical error correction systems improve written communication by detecting and correcting language mistakes. To help language learners better understand why the GEC system makes a certain correction, the causes of errors (evidence words) and the ...
Fei, Yuejiao +5 more
core +4 more sources
Grammatical Error Correction with Dependency Distance [PDF]
Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021 Grammatical Error Correction (GEC) task is always considered as low resource machine translation task which translates a sentence in an ungrammatical language to a grammatical language. As the state-of-the-art approach to GEC task, transformer-based neural machine translation model takes input sentence as a token sequence without sentence's structure ...
Haowen Lin +3 more
+13 more sources
Adversarial Grammatical Error Correction [PDF]
Findings of the Association for Computational Linguistics: EMNLP 2020, 2020 Recent works in Grammatical Error Correction (GEC) have leveraged the progress in Neural Machine Translation (NMT), to learn rewrites from parallel corpora of grammatically incorrect and corrected sentences, achieving state-of-the-art results. At the same time, Generative Adversarial Networks (GANs) have been successful in generating realistic texts ...
Vipul Raheja, Dimitrios Alikaniotis
openaire +4 more sources
Reassessing the Goals of Grammatical Error Correction: Fluency Instead of Grammaticality [PDF]
Transactions of the Association for Computational Linguistics, 2021 The field of grammatical error correction (GEC) has grown substantially in recent years, with research directed at both evaluation metrics and improved system performance against those metrics. One unvisited assumption, however, is the reliance of GEC evaluation on error-coded corpora, which contain specific labeled corrections.
Keisuke Sakaguchi +3 more
doaj +3 more sources
An Automatic Error Detection Method for Machine Translation Results via Deep Learning
IEEE Access, 2023 Nowadays, the rapid development of natural language processing has brought great progress for the area of machine translation. Various deep neural network-based machine translation approaches have been more and more general.
Weihong Zhang
doaj +1 more source
Crowdsourcing for grammatical error correction [PDF]
Proceedings of the companion publication of the 17th ACM conference on Computer supported cooperative work & social computing, 2014 We discuss the problem of grammatical error correction, which has gained attention for its usefulness both in the development of tools for learners of foreign languages and as a component of statistical machine translation systems. We believe the task of suggesting grammar and style corrections in writing is well suited to a crowdsourcing solution but ...
Ellie Pavlick +2 more
openaire +1 more source