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2007

Machine Translation by Triangulation: Making Effective Use of Multi-Parallel Corpora

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Machine Translation by Triangulation: Making Effective Use of Multi-Parallel Corpora
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.
Trevor Cohn, Mirella Lapata
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where ACL
Authors Trevor Cohn, Mirella Lapata
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