Hierarchical pre-reordering model for patent machine translation

Renfen Hu, Kai Zhao, Hongzheng Li, Yun Zhu, Yaohong Jin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Patents constitute one of the most challenging domains for machine translation because patent sentences can be quite long with complex structures. This paper presents a hierarchical reordering method based on three-level parsing for Chinese-English patent MT. After integrating into a Phrase based SMT system, our method improves the BLEU score by 1.92. There are also improvements in NIST and METEOR scores. Besides, we investigate the precision and recall of the reordering rule set by conducting manual evaluations.

Original languageEnglish
Title of host publicationProceedings of the 2016 International Conference on Asian Language Processing, IALP 2016
EditorsMinghui Dong, Chung-Hsien Wu, Yanfeng Lu, Haizhou Li, Yuen-Hsien Tseng, Liang-Chih Yu, Lung-Hao Lee
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages232-235
Number of pages4
ISBN (Electronic)9781509009213
DOIs
Publication statusPublished - 10 Mar 2017
Externally publishedYes
Event20th International Conference on Asian Language Processing, IALP 2016 - Tainan, Taiwan, Province of China
Duration: 21 Nov 201623 Nov 2016

Publication series

NameProceedings of the 2016 International Conference on Asian Language Processing, IALP 2016

Conference

Conference20th International Conference on Asian Language Processing, IALP 2016
Country/TerritoryTaiwan, Province of China
CityTainan
Period21/11/1623/11/16

Keywords

  • hierarchical model
  • machine translation
  • patent
  • reordering

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