Phrase-level System Combination for Machine Translation Based on Target-to-Target Decoding

Wei-Yun Ma, Kathleen McKeown


Abstract
In this paper, we propose a novel lattice-based MT combination methodology that we call Target-to-Target Decoding (TTD). The combination process is carried out as a “translation” from backbone to the combination result. This perspective suggests the use of existing phrase-based MT techniques in the combination framework. We show how phrase extraction rules and confidence estimations inspired from machine translation improve results. We also propose system-specific LMs for estimating N-gram consensus. Our results show that our approach yields a strong improvement over the best single MT system and competes with other state-of-the-art combination systems.
Anthology ID:
2012.amta-papers.11
Volume:
Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Research Papers
Month:
October 28-November 1
Year:
2012
Address:
San Diego, California, USA
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
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Pages:
Language:
URL:
https://aclanthology.org/2012.amta-papers.11
DOI:
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Cite (ACL):
Wei-Yun Ma and Kathleen McKeown. 2012. Phrase-level System Combination for Machine Translation Based on Target-to-Target Decoding. In Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Research Papers, San Diego, California, USA. Association for Machine Translation in the Americas.
Cite (Informal):
Phrase-level System Combination for Machine Translation Based on Target-to-Target Decoding (Ma & McKeown, AMTA 2012)
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PDF:
https://aclanthology.org/2012.amta-papers.11.pdf