@article {13740,
	title = {Combining outputs from multiple machine translation systems},
	journal = {Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Proceedings of the Main Conference},
	year = {2007},
	month = {2007///},
	pages = {228 - 235},
	abstract = {Currently there are several approaches tomachine 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 N -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.
},
	author = {Rosti,A.V.I. and Ayan,N.F. and Xiang,B. and Matsoukas,S. and Schwartz,R. and Dorr, Bonnie J}
}
