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English Grammar Error Detection Using Recurrent Neural Networks

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成果类型:
期刊论文
作者:
He, Zhenhui
作者机构:
[He, Zhenhui] Hunan Univ Changsha, Foreign Languages Dept, Changsha 410082, Hunan, Peoples R China.
[He, Zhenhui] Hunan Agr Univ Changsha, Foreign Languages Dept, Changsha 410128, Hunan, Peoples R China.
语种:
英文
期刊:
Scientific Programming
ISSN:
1058-9244
年:
2021
卷:
2021
基金类别:
Education and Science Planning Project of Hunan Province, China [XJK18QGD010]; Foreign Language Association Project of Social and Scientific Funding of Hunan Province, China [18WLH18]; Foreign Language Research Institute, Shanghai, China [2018HN0063B]; Excellent Youth Project of Education Department of Hunan Province, China [20B287, HNJG-2020-0038]
机构署名:
本校为其他机构
摘要:
Automatic marking of English compositions is a rapidly developing field in recent years. It has gradually replaced teachers' manual reading and become an important tool to relieve the teaching burden. The existing literature shows that the error of verb consistency and the error of verb tense are the two types of grammatical errors with the highest error rate in English composition. Hence, the detection results of verb errors can reflect the practicability and effectiveness of an automatic reading system. This paper proposes an English verb's grammar error detection algorithm based on the cycl...

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