Machine Translation by Triangulation: Making Effective Use of Multi-Parallel Corpora
Trevor Cohn, Mirella Lapata · Edinburgh Research Explorer (University of Edinburgh) · 2007
Current phrase-based SMT systems perform poorly when using small training sets. This is a consequence of unreliable translation es-timates and low coverage over source and target phrases. This paper presents a method which alleviates this problem by exploit-ing multiple translations of the same source phrase. Central to our approach is triangula-tion, 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 train-ing, and can be combined with a standard phrase-table using conventional smoothing methods. Experimental results demonstrate BLEU improvements for triangulated mod-els over a standard phrase-based system. 1