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        <title>Verb Replacer: An English Verb Error Correction System</title>
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    <name type="personal">
        <namePart type="given">Yu-Hsuan</namePart>
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        <namePart type="given">Jhih-Jie</namePart>
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            <title>Proceedings of the IJCNLP 2017, System Demonstrations</title>
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            <namePart type="given">Seong-Bae</namePart>
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            <namePart type="family">Supnithi</namePart>
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    <abstract>According to the analysis of Cambridge Learner Corpus, using a wrong verb is the most common type of grammatical errors. This paper describes Verb Replacer, a system for detecting and correcting potential verb errors in a given sentence. In our approach, alternative verbs are considered to replace the verb based on an error-annotated corpus and verb-object collocations. The method involves applying regression on channel models, parsing the sentence, identifying the verbs, retrieving a small set of alternative verbs, and evaluating each alternative. Our method combines and improves channel and language models, resulting in high recall of detecting and correcting verb misuse.</abstract>
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%0 Conference Proceedings
%T Verb Replacer: An English Verb Error Correction System
%A Wu, Yu-Hsuan
%A Chen, Jhih-Jie
%A Chang, Jason
%Y Park, Seong-Bae
%Y Supnithi, Thepchai
%S Proceedings of the IJCNLP 2017, System Demonstrations
%D 2017
%8 November
%I Association for Computational Linguistics
%C Tapei, Taiwan
%F wu-etal-2017-verb
%X According to the analysis of Cambridge Learner Corpus, using a wrong verb is the most common type of grammatical errors. This paper describes Verb Replacer, a system for detecting and correcting potential verb errors in a given sentence. In our approach, alternative verbs are considered to replace the verb based on an error-annotated corpus and verb-object collocations. The method involves applying regression on channel models, parsing the sentence, identifying the verbs, retrieving a small set of alternative verbs, and evaluating each alternative. Our method combines and improves channel and language models, resulting in high recall of detecting and correcting verb misuse.
%U https://aclanthology.org/I17-3013
%P 49-52

Markdown (Informal)

[Verb Replacer: An English Verb Error Correction System](https://aclanthology.org/I17-3013) (Wu et al., IJCNLP 2017)

• Verb Replacer: An English Verb Error Correction System (Wu et al., IJCNLP 2017)

ACL

• Yu-Hsuan Wu, Jhih-Jie Chen, and Jason Chang. 2017. Verb Replacer: An English Verb Error Correction System. In Proceedings of the IJCNLP 2017, System Demonstrations, pages 49–52, Tapei, Taiwan. Association for Computational Linguistics.