Convergence of Translation Memory and Statistical Machine Translation

Philipp Koehn, Jean Senellart


Abstract
We present two methods that merge ideas from statistical machine translation (SMT) and translation memories (TM). We use a TM to retrieve matches for source segments, and replace the mismatched parts with instructions to an SMT system to fill in the gap. We show that for fuzzy matches of over 70%, one method outperforms both SMT and TM baselines.
Anthology ID:
2010.jec-1.4
Volume:
Proceedings of the Second Joint EM+/CNGL Workshop: Bringing MT to the User: Research on Integrating MT in the Translation Industry
Month:
November 4
Year:
2010
Address:
Denver, Colorado, USA
Editor:
Ventsislav Zhechev
Venue:
JEC
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
21–32
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/2010.jec-1.4/
DOI:
Bibkey:
Cite (ACL):
Philipp Koehn and Jean Senellart. 2010. Convergence of Translation Memory and Statistical Machine Translation. In Proceedings of the Second Joint EM+/CNGL Workshop: Bringing MT to the User: Research on Integrating MT in the Translation Industry, pages 21–32, Denver, Colorado, USA. Association for Machine Translation in the Americas.
Cite (Informal):
Convergence of Translation Memory and Statistical Machine Translation (Koehn & Senellart, JEC 2010)
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PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/2010.jec-1.4.pdf