Results 11 to 20 of about 9,958 (247)
Comparison of the Evaluation Metrics for Neural Grammatical Error Correction With Overcorrection
IEEE Access, 2020 Grammar error correction (GEC) refers to the proper correction of grammatical errors in a given sentence. Important factors to consider in GEC are not only the grammatical correction of the sentence, but also the recognition of a correct sentence in ...
Chanjun Park +3 more
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Towards Harnessing the Most of ChatGPT for Korean Grammatical Error Correction
Applied SciencesIn this study, we conduct a pioneering and comprehensive examination of ChatGPT’s (GPT-3.5 Turbo) capabilities within the realm of Korean Grammatical Error Correction (K-GEC).
Chanjun Park +3 more
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A method for English paragraph grammar correction based on differential fusion of syntactic features. [PDF]
PLoS ONEThe new progress of deep learning and natural language processing technology has strongly promoted the development of English grammar error correction. However, the existing methods mostly rely on large-scale corpus, and often ignore the fine syntactic ...
Weiling Liu +7 more
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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
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Chinese Grammatical Error Correction Based on Grammatical Knowledge Enhancement [PDF]
Jisuanji gongcheng, 2023 The aim of grammatical error correction is to judge whether natural language texts contain grammatical errors, to correct them. In recent years, with the rapid development of pre-trained language models, methods based on such models have been widely used
Qian DENG, Shu CHEN, Junmin YE
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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
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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
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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
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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
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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. In view of this, we propose a method to mine error templates for GEC automatically. An error template is a regular expression aiming at identifying text errors.
Yue Zhang 0004 +5 more
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