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://aclanthology.org/2010.jec-1.4
- DOI:
- 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)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/2010.jec-1.4.pdf