Hierarchical pre-reordering model for patent machine translation

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

doi:10.1109/IALP.2016.7875975

Hierarchical pre-reordering model for patent machine translation

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

Beijing Normal University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016
Editors	Minghui Dong, Chung-Hsien Wu, Yanfeng Lu, Haizhou Li, Yuen-Hsien Tseng, Liang-Chih Yu, Lung-Hao Lee
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	232-235
Number of pages	4
ISBN (Electronic)	9781509009213
DOIs	https://doi.org/10.1109/IALP.2016.7875975
Publication status	Published - 10 Mar 2017
Externally published	Yes
Event	20th International Conference on Asian Language Processing, IALP 2016 - Tainan, Taiwan, Province of China Duration: 21 Nov 2016 → 23 Nov 2016

Publication series

Name	Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016

Conference

Conference	20th International Conference on Asian Language Processing, IALP 2016
Country/Territory	Taiwan, Province of China
City	Tainan
Period	21/11/16 → 23/11/16

Keywords

hierarchical model
machine translation
patent
reordering

Access to Document

10.1109/IALP.2016.7875975

Cite this

Hu, R., Zhao, K., Li, H., Zhu, Y., & Jin, Y. (2017). Hierarchical pre-reordering model for patent machine translation. In M. Dong, C.-H. Wu, Y. Lu, H. Li, Y.-H. Tseng, L.-C. Yu, & L.-H. Lee (Eds.), Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016 (pp. 232-235). Article 7875975 (Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IALP.2016.7875975

Hu, Renfen ; Zhao, Kai ; Li, Hongzheng et al. / Hierarchical pre-reordering model for patent machine translation. Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016. editor / Minghui Dong ; Chung-Hsien Wu ; Yanfeng Lu ; Haizhou Li ; Yuen-Hsien Tseng ; Liang-Chih Yu ; Lung-Hao Lee. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 232-235 (Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016).

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title = "Hierarchical pre-reordering model for patent machine translation",

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.",

keywords = "hierarchical model, machine translation, patent, reordering",

author = "Renfen Hu and Kai Zhao and Hongzheng Li and Yun Zhu and Yaohong Jin",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 20th International Conference on Asian Language Processing, IALP 2016 ; Conference date: 21-11-2016 Through 23-11-2016",

year = "2017",

month = mar,

day = "10",

doi = "10.1109/IALP.2016.7875975",

language = "English",

series = "Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "232--235",

editor = "Minghui Dong and Chung-Hsien Wu and Yanfeng Lu and Haizhou Li and Yuen-Hsien Tseng and Liang-Chih Yu and Lung-Hao Lee",

booktitle = "Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016",

address = "United States",

}

Hu, R, Zhao, K, Li, H, Zhu, Y & Jin, Y 2017, Hierarchical pre-reordering model for patent machine translation. in M Dong, C-H Wu, Y Lu, H Li, Y-H Tseng, L-C Yu & L-H Lee (eds), Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016., 7875975, Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016, Institute of Electrical and Electronics Engineers Inc., pp. 232-235, 20th International Conference on Asian Language Processing, IALP 2016, Tainan, Taiwan, Province of China, 21/11/16. https://doi.org/10.1109/IALP.2016.7875975

Hierarchical pre-reordering model for patent machine translation. / Hu, Renfen; Zhao, Kai; Li, Hongzheng et al.
Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016. ed. / Minghui Dong; Chung-Hsien Wu; Yanfeng Lu; Haizhou Li; Yuen-Hsien Tseng; Liang-Chih Yu; Lung-Hao Lee. Institute of Electrical and Electronics Engineers Inc., 2017. p. 232-235 7875975 (Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Hierarchical pre-reordering model for patent machine translation

AU - Hu, Renfen

AU - Zhao, Kai

AU - Li, Hongzheng

AU - Zhu, Yun

AU - Jin, Yaohong

PY - 2017/3/10

Y1 - 2017/3/10

N2 - 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.

AB - 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.

KW - hierarchical model

KW - machine translation

KW - patent

KW - reordering

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U2 - 10.1109/IALP.2016.7875975

DO - 10.1109/IALP.2016.7875975

M3 - Conference contribution

AN - SCOPUS:85017275828

T3 - Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016

SP - 232

EP - 235

BT - Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016

A2 - Dong, Minghui

A2 - Wu, Chung-Hsien

A2 - Lu, Yanfeng

A2 - Li, Haizhou

A2 - Tseng, Yuen-Hsien

A2 - Yu, Liang-Chih

A2 - Lee, Lung-Hao

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 20th International Conference on Asian Language Processing, IALP 2016

Y2 - 21 November 2016 through 23 November 2016

ER -

Hu R, Zhao K, Li H, Zhu Y, Jin Y. Hierarchical pre-reordering model for patent machine translation. In Dong M, Wu CH, Lu Y, Li H, Tseng YH, Yu LC, Lee LH, editors, Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 232-235. 7875975. (Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016). doi: 10.1109/IALP.2016.7875975

Hierarchical pre-reordering model for patent machine translation

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