Results 21 to 30 of about 3,453,209 (234)

EXPLORING EFL LEARNERS’ GRAMMATICAL ERROR IN PARAGRAPH WRITING [PDF]

, 2020
Writing is the most difficult skill in English, so most English as a foreign language (EFL) learners tend to make errors in writing. In assisting the learners to sucessfully acquire writing skill, the analysis of errors and the understanding of their ...
Cahyani, Dian Anik, Rizaldi, Aditya
core   +1 more source

A Hybrid System for Chinese Grammatical Error Diagnosis and Correction [PDF]

Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications, 2018
This paper introduces the DM_NLP team’s system for NLPTEA 2018 shared task of Chinese Grammatical Error Diagnosis (CGED), which can be used to detect and correct grammatical errors in texts written by Chinese as a Foreign Language (CFL) learners.
Chen Li, Junpei Zhou, Zuyi Bao, Hengyou Liu, Guangwei Xu, Linlin Li 0001   +5 more
openaire   +1 more source

Nonlinear Error Correction Models [PDF]

, 2002
The relationship between cointegration and error correction (EC) models is well characterized in a linear context, but the extension to the nonlinear context is still a challenge.
Escribano, Álvaro, Mira, Santiago
core   +1 more source

Revisiting the Evaluation for Chinese Grammatical Error Correction

Journal of Advanced Computational Intelligence and Intelligent Informatics
English grammar error correction (GEC) has been a popular topic over the past decade. The appropriateness of automatic evaluations, e.g., the combination of metrics and reference types, has been thoroughly studied for English GEC. Yet, such systematic investigations on the Chinese GEC are still insufficient.
Hongfei Wang, Zhousi Chen, Zizheng Zhang, Zhidong Ling, Xiaomeng Pan, Wenjie Duan, Masato Mita, Mamoru Komachi   +7 more
openaire   +4 more sources

Non-linear error correction, asymmetric adjustment and cointegration [PDF]

, 1998
This article links the intertemporal choice model with the non-linear error correction (NEC) model. It has three main components. First, it outlines a model of non-linear error correction, in which the linear error correction term ?Xt (the vector time ...
Pfann, Gerard, Escribano, Álvaro
core   +1 more source

GenERRate: generating errors for use in grammatical error detection [PDF]

, 2009
This paper explores the issue of automatically generated ungrammatical data and its use in error detection, with a focus on the task of classifying a sentence as grammatical or ungrammatical.
Foster, Jennifer, Andersen, Øistein E.
core   +2 more sources

A new evaluation method: evaluation data and metrics for Chinese grammatical error correction

Language Resources and Evaluation, 2022
Abstract As a fundamental task in natural language processing (NLP), Chinese Grammatical Error Correction (CGEC) [1–3] has gradually received widespread attention and become a research hotspot. However, one obvious deficiency of the existing CGEC evaluation systems is that the evaluation values of the same error correction models are signif ...
Nankai Lin, Yingwen Fu, Xiaotian Lin, Ziyu Yang, Shengyi Jiang   +4 more
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“Is Whole Word Masking Always Better for Chinese BERT?”: Probing on Chinese Grammatical Error Correction

Findings of the Association for Computational Linguistics: ACL 2022, 2022
Whole word masking (WWM), which masks all subwords corresponding to a word at once, makes a better English BERT model. For the Chinese language, however, there is no subword because each token is an atomic character. The meaning of a word in Chinese is different in that a word is a compositional unit consisting of multiple characters.
Yong Dai 0001, Linyang Li, Cong Zhou, Zhangyin Feng, Enbo Zhao, Xipeng Qiu, Piji Li, Duyu Tang   +7 more
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FlaCGEC: A Chinese Grammatical Error Correction Dataset with Fine-grained Linguistic Annotation

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
Chinese Grammatical Error Correction (CGEC) has been attracting growing attention from researchers recently. In spite of the fact that multiple CGEC datasets have been developed to support the research, these datasets lack the ability to provide a deep linguistic topology of grammar errors, which is critical for interpreting and diagnosing CGEC ...
Hanyue Du, Yike Zhao, Qingyuan Tian, Jiani Wang, Lei Wang 0185, Yunshi Lan, Xuesong Lu   +6 more
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Linguistic Rules-Based Corpus Generation for Native Chinese Grammatical Error Correction

Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
Long paper, accepted at the Findings of EMNLP ...
Shirong Ma, Yinghui Li, Rongyi Sun, Qingyu Zhou, Shulin Huang, Ding Zhang, Yangning Li, Ruiyang Liu, Zhongli Li, Yunbo Cao, Haitao Zheng 0002, Ying Shen 0001   +11 more
openaire   +2 more sources