Practical Approach to Syntax-based Statistical Machine Translation

Kenji Imamura, Hideo Okuma, Eiichiro Sumita


Abstract
This paper presents a practical approach to statistical machine translation (SMT) based on syntactic transfer. Conventionally, phrase-based SMT generates an output sentence by combining phrase (multiword sequence) translation and phrase reordering without syntax. On the other hand, SMT based on tree-to-tree mapping, which involves syntactic information, is theoretical, so its features remain unclear from the viewpoint of a practical system. The SMT proposed in this paper translates phrases with hierarchical reordering based on the bilingual parse tree. In our experiments, the best translation was obtained when both phrases and syntactic information were used for the translation process.
Anthology ID:
2005.mtsummit-papers.35
Volume:
Proceedings of Machine Translation Summit X: Papers
Month:
September 13-15
Year:
2005
Address:
Phuket, Thailand
Venue:
MTSummit
SIG:
Publisher:
Note:
Pages:
267–274
Language:
URL:
https://aclanthology.org/2005.mtsummit-papers.35
DOI:
Bibkey:
Cite (ACL):
Kenji Imamura, Hideo Okuma, and Eiichiro Sumita. 2005. Practical Approach to Syntax-based Statistical Machine Translation. In Proceedings of Machine Translation Summit X: Papers, pages 267–274, Phuket, Thailand.
Cite (Informal):
Practical Approach to Syntax-based Statistical Machine Translation (Imamura et al., MTSummit 2005)
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PDF:
https://preview.aclanthology.org/author-url/2005.mtsummit-papers.35.pdf