Results 11 to 20 of about 284,138 (314)

Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction [PDF]

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2017
Until now, error type performance for Grammatical Error Correction (GEC) systems could only be measured in terms of recall because system output is not annotated. To overcome this problem, we introduce ERRANT, a grammatical ERRor ANnotation Toolkit designed to automatically extract edits from parallel original and corrected sentences and classify them ...
Bryant, CJ, Felice, M, Briscoe, E
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Chinese Grammatical Error Correction: A Survey

arXiv.org
Chinese Grammatical Error Correction (CGEC) is a critical task in Natural Language Processing, addressing the growing demand for automated writing assistance in both second-language (L2) and native (L1) Chinese writing. While L2 learners struggle with mastering complex grammatical structures, L1 users also benefit from CGEC in academic, professional ...
Qiu, Mengyang, Gao, Qingyu, Yang, Linxuan, Gu, Yang, Nguyen, Tran Minh, Huang, Zihao, Park, Jungyeul   +6 more
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A Small-Scale Evaluation of Large Language Models Used for Grammatical Error Correction in a German Children’s Literature Corpus: A Comparative Study

Applied Sciences
Grammatical error correction (GEC) has become increasingly important for enhancing the quality of OCR-scanned texts. This small-scale study explores the application of Large Language Models (LLMs) for GEC in German children’s literature, a genre with ...
Phuong Thao Nguyen, Bernd Nuss, Roswita Dressler, Katie Ovens   +3 more
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Towards Harnessing the Most of ChatGPT for Korean Grammatical Error Correction

Applied Sciences
In 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, Seonmin Koo, Gyeongmin Kim, Heuiseok Lim   +3 more
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Research on grammatical error correction algorithm in English translation via deep learning

Journal of Intelligent Systems
This study provides a concise overview of a grammatical error correction algorithm that is based on an encoder-decoder machine translation structure.
Cai Lihua
doaj   +2 more sources

End-to-End Spoken Grammatical Error Correction

arXiv.org
Grammatical Error Correction (GEC) and feedback play a vital role in supporting second language (L2) learners, educators, and examiners. While written GEC is well-established, spoken GEC (SGEC), aiming to provide feedback based on learners' speech, poses additional challenges due to disfluencies, transcription errors, and the lack of structured input ...
Qian, Mengjie, Ma, Rao, Bannò, Stefano, Gales, Mark J. F., Knill, Kate M.   +4 more
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GPT-3.5 for Grammatical Error Correction

International Conference on Language Resources and Evaluation
This paper investigates the application of GPT-3.5 for Grammatical Error Correction (GEC) in multiple languages in several settings: zero-shot GEC, fine-tuning for GEC, and using GPT-3.5 to re-rank correction hypotheses generated by other GEC models. In the zero-shot setting, we conduct automatic evaluations of the corrections proposed by GPT-3.5 using
Katinskaia Anisia, Yangarber Roman
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Grammatical error correction for low-resource languages: a review of challenges, strategies, computational and future directions. [PDF]

PeerJ Comput Sci
Grammatical error correction (GEC) is crucial for enhancing the readability and comprehension of texts, particularly in improving text quality in low-resource languages.
Marier SM, Chen X, Zhu L, Kong X.
europepmc   +2 more sources

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. Our unsupervised approach is based on a simple but effective synthetic error generation method based on confusion sets from ...
Roman Grundkiewicz, Marcin Junczys-Dowmunt   +1 more
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Neural Quality Estimation Based on Multiple Hypotheses Interaction and Self-Attention for Grammatical Error Correction

IEEE Access, 2023
The English grammatical error correction system is suitable for the English learning environment, with the goal of accurately correcting errors in learners’ writing.
Chen Zhang, Tongjie Xu, Guangli Wu
doaj   +1 more source