Combining Outputs from Multiple Machine Translation Systems
HLT-NAACL(2007)
摘要
Currently there are several approaches to machine translation (MT) based on differ- ent paradigms; e.g., phrasal, hierarchical and syntax-based. These three approaches yield similar translation accuracy despite using fairly different levels of linguistic knowledge. The availability of such a variety of systems has led to a growing interest toward finding better translations by combining outputs from multiple sys- tems. This paper describes three differ- ent approaches to MT system combina- tion. These combination methods oper- ate on sentence, phrase and word level exploiting information from -best lists, system scores and target-to-source phrase alignments. The word-level combination provides the most robust gains but the best results on the development test sets (NIST MT05 and the newsgroup portion of GALE 2006 dry-run) were achieved by combining all three methods.
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关键词
machine translation
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