@inproceedings{wu-etal-2017-verb,
    title = "Verb Replacer: An {E}nglish Verb Error Correction System",
    author = "Wu, Yu-Hsuan  and
      Chen, Jhih-Jie  and
      Chang, Jason",
    editor = "Park, Seong-Bae  and
      Supnithi, Thepchai",
    booktitle = "Proceedings of the {IJCNLP} 2017, System Demonstrations",
    month = nov,
    year = "2017",
    address = "Tapei, Taiwan",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/I17-3013/",
    pages = "49--52",
    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."
}