A novel dependency based word-level reordering model for phrased-based translation

Author

Liu, Shui ; Li, Sheng ; Zhao, Tiejun ; Li, Shiqi

Author_Institution

Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China

fYear

2010

fDate

21-23 Aug. 2010

Firstpage

1

Lastpage

6

Abstract

Phrase based statistic MT (SMT) is an important milestone in MT. However, the translation model in the phrase based SMT is structure free which limits its reordering capacity to some extent. In order to enhance the reordering capacity of phrase based SMT, in this paper we propose a head-modifier relation based reordering model, which exploits the way how to utilize the structured linguistic analysis information in source language. Within very small size of reordering model, we enhance the performance of the phrase based SMT significantly.

Keywords

language translation; linguistics; statistical analysis; head-modifier relation; phrase based statistical machine translation; phrased-based translation; source language; structured linguistic analysis information; word-level reordering model; Artificial neural networks; IP networks; NIST; Noise measurement; Head-modifier; Phrase Based SMT; Reordering Model; Statistical Machine Translation;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Language Processing and Knowledge Engineering (NLP-KE), 2010 International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-6896-6

Type

conf

DOI

10.1109/NLPKE.2010.5587829

Filename

5587829