BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Minimum error rate training in statistical machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Paraphrasing with bilingual parallel corpora
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Machine translation system combination using ITG-based alignments
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Further meta-evaluation of machine translation
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
CMU system combination for WMT'09
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
The RWTH system combination system for WMT 2009
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
Machine translation system combination with flexible word ordering
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
Extending the meteor machine translation evaluation metric to the phrase level
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
CMU system combination in WMT 2011
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
The UZH system combination system for WMT 2011
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
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This paper describes our submission, cmu--heafield--combo, to the WMT 2010 machine translation system combination task. Using constrained resources, we participated in all nine language pairs, namely translating English to and from Czech, French, German, and Spanish as well as combining English translations from multiple languages. Combination proceeds by aligning all pairs of system outputs then navigating the aligned outputs from left to right where each path is a candidate combination. Candidate combinations are scored by their length, agreement with the underlying systems, and a language model. On tuning data, improvement in BLEU over the best system depends on the language pair and ranges from 0.89% to 5.57% with mean 2.37%.