Tevor Cohn and Mirella Lapata. 2007. Machine Translation by Triangulation: Making Effective Use of Multi-Parallel Corpora. In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics, 348-355. Prague.

Current phrase-based SMT systems perform poorly when using small training sets. This is a consequence of unreliable translation estimates and low coverage over source and target phrases. This paper presents a method which alleviates this problem by exploiting multiple translations of the same source phrase. Central to our approach is triangulation, the process of translating from a source to a target language via an intermediate third language. This allows the use of a much wider range of parallel corpora for training, and can be combined with a standard phrase table using conventional smoothing methods. Experimental results demonstrate Bleu improvements for triangulated models over a standard phrase-based system.

@InProceedings{Cohn:Lapata:07a
  author = 	 {Trevor Cohn and Mirella Lapata},
  title = 	 {Machine Translation by Triangulation: Making
                  Effective Use of Multi-Parallel Corpora},
  crossref =	 {ACL:07},
  pages =        {728--735}
}

@Proceedings{NAACL:07,
  title = 	 {Proceedings  of the 45th Annual Meeting of the 
                  Association for Computational Linguistics},
  booktitle =    {Proceedings of the 45th Annual Meeting of the
                  Association for Computational Linguistics},
  year = 	 2007,
  address =	 {Prague}
}