Verb Replacer: An English Verb Error Correction System

Yu-Hsuan Wu, Jhih-Jie Chen, Jason Chang


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.
Anthology ID:
I17-3013
Volume:
Proceedings of the IJCNLP 2017, System Demonstrations
Month:
November
Year:
2017
Address:
Tapei, Taiwan
Venue:
IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
49–52
Language:
URL:
https://www.aclweb.org/anthology/I17-3013
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/I17-3013.pdf