Paper: An Empirical Study on Computing Consensus Translations from Multiple Machine Translation Systems

ACL ID D07-1105
Title An Empirical Study on Computing Consensus Translations from Multiple Machine Translation Systems
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007
Authors

This paper presents an empirical study on how different selections of input translation systems affect translation quality in system combination. We give empirical evidence that the systems to be combined should be of similar quality and need to be almost uncorrelated in order to be beneficial for sys- tem combination. Experimental results are presented for composite translations com- puted from large numbers of different re- search systems as well as a set of transla- tion systems derived from one of the best- ranked machine translation engines in the 2006 NIST machine translation evaluation.