Discriminative reranking for grammatical error correction with statistical machine translation

Tomoya Mizumoto, Yuji Matsumoto

研究成果: Conference contribution

12 被引用数 (Scopus)

抄録

Research on grammatical error correction has received considerable attention. For dealing with all types of errors, grammatical error correction methods that employ statistical machine translation (SMT) have been proposed in recent years. An SMT system generates candidates with scores for all candidates and selects the sentence with the highest score as the correction result. However, the 1-best result of an SMT system is not always the best result. Thus, we propose a reranking approach for grammatical error correction. The reranking approach is used to re-score N-best results of the SMT and reorder the results. Our experiments show that our reranking system using parts of speech and syntactic features improves performance and achieves state-of-the-art quality, with an F0.5 score of 40.0.

本文言語English
ホスト出版物のタイトル2016 Conference of the North American Chapter of the Association for Computational Linguistics
ホスト出版物のサブタイトルHuman Language Technologies, NAACL HLT 2016 - Proceedings of the Conference
出版社Association for Computational Linguistics (ACL)
ページ1133-1138
ページ数6
ISBN(電子版)9781941643914
DOI
出版ステータスPublished - 2016
イベント15th Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016 - San Diego, United States
継続期間: 2016 6 122016 6 17

出版物シリーズ

名前2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016 - Proceedings of the Conference

Other

Other15th Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016
CountryUnited States
CitySan Diego
Period16/6/1216/6/17

ASJC Scopus subject areas

  • Computer Science Applications
  • Linguistics and Language
  • Language and Linguistics

フィンガープリント 「Discriminative reranking for grammatical error correction with statistical machine translation」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル