Paper: Smooth Bilingual $N$-Gram Translation

ACL ID D07-1045
Title Smooth Bilingual $N$-Gram Translation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007

We address the problem of smoothing trans- lation probabilities in a bilingual N-gram- based statistical machine translation system. It is proposed to project the bilingual tuples onto a continuous space and to estimate the translation probabilities in this representa- tion. A neural network is used to perform the projection and the probability estimation. Smoothing probabilities is most important for tasks with a limited amount of training material. We consider here the BTEC task of the 2006 IWSLT evaluation. Improve- ments in all official automatic measures are reported when translating from Italian to En- glish. Using a continuous space model for the translation model and the target language model, an improvement of 1.5 BLEU on the test data is observed.