Voting on N-grams for Machine Translation System Combination

Kenneth Heafield, Alon Lavie


Abstract
System combination exploits differences between machine translation systems to form a combined translation from several system outputs. Core to this process are features that reward n-gram matches between a candidate combination and each system output. Systems differ in performance at the n-gram level despite similar overall scores. We therefore advocate a new feature formulation: for each system and each small n, a feature counts n-gram matches between the system and candidate. We show post-evaluation improvement of 6.67 BLEU over the best system on NIST MT09 Arabic-English test data. Compared to a baseline system combination scheme from WMT 2009, we show improvement in the range of 1 BLEU point.
Anthology ID:
2010.amta-papers.34
Volume:
Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers
Month:
October 31-November 4
Year:
2010
Address:
Denver, Colorado, USA
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
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URL:
https://aclanthology.org/2010.amta-papers.34
DOI:
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Cite (ACL):
Kenneth Heafield and Alon Lavie. 2010. Voting on N-grams for Machine Translation System Combination. In Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers, Denver, Colorado, USA. Association for Machine Translation in the Americas.
Cite (Informal):
Voting on N-grams for Machine Translation System Combination (Heafield & Lavie, AMTA 2010)
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PDF:
https://preview.aclanthology.org/nodalida-main-page/2010.amta-papers.34.pdf