A study of translation rule classification for syntax-based statistical machine translation

Hongfei Jiang; Sheng Li; Muyun Yang; Tiejun Zhao

doi:10.3115/1626344.1626350

A study of translation rule classification for syntax-based statistical machine translation

Hongfei Jiang
, Sheng Li
, Muyun Yang
, Tiejun Zhao

School of Computer Science and Technology, Harbin Institute of Technology

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

Abstract

Recently, numerous statistical machine translation models which can utilize various kinds of translation rules are proposed. In these models, not only the conventional syntactic rules but also the non-syntactic rules can be applied. Even the pure phrase rules are includes in some of these models. Although the better performances are reported over the conventional phrase model and syntax model, the mixture of diversified rules still leaves much room for study. In this paper, we present a refined rule classification system. Based on this classification system, the rules are classified according to different standards, such as lexicalization level and generalization. Especially, we refresh the concepts of the structure reordering rules and the discontiguous phrase rules. This novel classification system may supports the SMT research community with some helpful references.

Original language	English
Title of host publication	Proceedings of SSST 2009
Subtitle of host publication	3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009
Editors	Dekai Wu, David Chiang
Publisher	Association for Computational Linguistics (ACL)
Pages	45-50
Number of pages	6
ISBN (Electronic)	9781932432398
DOIs	https://doi.org/10.3115/1626344.1626350
State	Published - 2009
Externally published	Yes
Event	3rd Workshop on Syntax and Structure in Statistical Translation, SSST 2009 at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009 - Boulder, United States Duration: 5 Jun 2009 → …

Publication series

Name	Proceedings of SSST 2009: 3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009

Conference

Conference	3rd Workshop on Syntax and Structure in Statistical Translation, SSST 2009 at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009
Country/Territory	United States
City	Boulder
Period	5/06/09 → …

Access to Document

10.3115/1626344.1626350

Cite this

Jiang, H., Li, S., Yang, M., & Zhao, T. (2009). A study of translation rule classification for syntax-based statistical machine translation. In D. Wu, & D. Chiang (Eds.), Proceedings of SSST 2009: 3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009 (pp. 45-50). (Proceedings of SSST 2009: 3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1626344.1626350

Jiang, Hongfei ; Li, Sheng ; Yang, Muyun et al. / A study of translation rule classification for syntax-based statistical machine translation. Proceedings of SSST 2009: 3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009. editor / Dekai Wu ; David Chiang. Association for Computational Linguistics (ACL), 2009. pp. 45-50 (Proceedings of SSST 2009: 3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009).

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title = "A study of translation rule classification for syntax-based statistical machine translation",

abstract = "Recently, numerous statistical machine translation models which can utilize various kinds of translation rules are proposed. In these models, not only the conventional syntactic rules but also the non-syntactic rules can be applied. Even the pure phrase rules are includes in some of these models. Although the better performances are reported over the conventional phrase model and syntax model, the mixture of diversified rules still leaves much room for study. In this paper, we present a refined rule classification system. Based on this classification system, the rules are classified according to different standards, such as lexicalization level and generalization. Especially, we refresh the concepts of the structure reordering rules and the discontiguous phrase rules. This novel classification system may supports the SMT research community with some helpful references.",

author = "Hongfei Jiang and Sheng Li and Muyun Yang and Tiejun Zhao",

note = "Publisher Copyright: {\textcopyright} 2009 Association for Computational Linguistics; 3rd Workshop on Syntax and Structure in Statistical Translation, SSST 2009 at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009 ; Conference date: 05-06-2009",

year = "2009",

doi = "10.3115/1626344.1626350",

language = "英语",

series = "Proceedings of SSST 2009: 3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009",

publisher = "Association for Computational Linguistics (ACL)",

pages = "45--50",

editor = "Dekai Wu and David Chiang",

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Jiang, H, Li, S, Yang, M & Zhao, T 2009, A study of translation rule classification for syntax-based statistical machine translation. in D Wu & D Chiang (eds), Proceedings of SSST 2009: 3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009. Proceedings of SSST 2009: 3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009, Association for Computational Linguistics (ACL), pp. 45-50, 3rd Workshop on Syntax and Structure in Statistical Translation, SSST 2009 at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009, Boulder, United States, 5/06/09. https://doi.org/10.3115/1626344.1626350

A study of translation rule classification for syntax-based statistical machine translation. / Jiang, Hongfei; Li, Sheng; Yang, Muyun et al.
Proceedings of SSST 2009: 3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009. ed. / Dekai Wu; David Chiang. Association for Computational Linguistics (ACL), 2009. p. 45-50 (Proceedings of SSST 2009: 3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009).

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

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AB - Recently, numerous statistical machine translation models which can utilize various kinds of translation rules are proposed. In these models, not only the conventional syntactic rules but also the non-syntactic rules can be applied. Even the pure phrase rules are includes in some of these models. Although the better performances are reported over the conventional phrase model and syntax model, the mixture of diversified rules still leaves much room for study. In this paper, we present a refined rule classification system. Based on this classification system, the rules are classified according to different standards, such as lexicalization level and generalization. Especially, we refresh the concepts of the structure reordering rules and the discontiguous phrase rules. This novel classification system may supports the SMT research community with some helpful references.

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Jiang H, Li S, Yang M , Zhao T. A study of translation rule classification for syntax-based statistical machine translation. In Wu D, Chiang D, editors, Proceedings of SSST 2009: 3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009. Association for Computational Linguistics (ACL). 2009. p. 45-50. (Proceedings of SSST 2009: 3rd Workshop on Syntax and Structure in Statistical Translation at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009). doi: 10.3115/1626344.1626350

A study of translation rule classification for syntax-based statistical machine translation

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