Example-based decoding for statistical machine translation

Taro Watanabe, Eiichiro Sumita


Abstract
This paper presents a decoder for statistical machine translation that can take advantage of the example-based machine translation framework. The decoder presented here is based on the greedy approach to the decoding problem, but the search is initiated from a similar translation extracted from a bilingual corpus. The experiments on multilingual translations showed that the proposed method was far superior to a word-by-word generation beam search algorithm.
Anthology ID:
2003.mtsummit-papers.54
Volume:
Proceedings of Machine Translation Summit IX: Papers
Month:
September 23-27
Year:
2003
Address:
New Orleans, USA
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MTSummit
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URL:
https://aclanthology.org/2003.mtsummit-papers.54
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Cite (ACL):
Taro Watanabe and Eiichiro Sumita. 2003. Example-based decoding for statistical machine translation. In Proceedings of Machine Translation Summit IX: Papers, New Orleans, USA.
Cite (Informal):
Example-based decoding for statistical machine translation (Watanabe & Sumita, MTSummit 2003)
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PDF:
https://aclanthology.org/2003.mtsummit-papers.54.pdf