Paper: Computing Consensus Translation For Multiple Machine Translation Systems Using Enhanced Hypothesis Alignment

ACL ID E06-1005
Title Computing Consensus Translation For Multiple Machine Translation Systems Using Enhanced Hypothesis Alignment
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2006
Authors

This paper describes a novel method for computing a consensus translation from the outputs of multiple machine trans- lation (MT) systems. The outputs are combined and a possibly new transla- tion hypothesis can be generated. Simi- larly to the well-established ROVER ap- proach of (Fiscus, 1997) for combining speech recognition hypotheses, the con- sensus translation is computed by voting on a confusion network. To create the con- fusion network, we produce pairwise word alignments of the original machine trans- lation hypotheses with an enhanced sta- tistical alignment algorithm that explicitly models word reordering. The context of a wholedocumentoftranslationsratherthan a single sentence is taken into account to produce the alignment. The proposed alignment and voting ap- proach was eva...