Improving Pivot Translation by Remembering the Pivot

Pivot translation allows for translation of language pairs with little or no parallel data by introducing a third language for which data exists. In particular, the triangulation method, which translates by combining source-pivot and pivot-target translation models into a source-target model, is known for its high translation accuracy. However, in the conventional triangulation method, information of pivot phrases is forgotten and not used in the translation process. In this paper, we propose a novel approach to remember the pivot phrases in the triangulation stage, and use a pivot language model as an additional information source at translation time. Experimental results on the Europarl corpus showed

• Type: Journal
• Year: 2015
• Where: ACL
• Authors: Akiva Miura, Graham Neubig, Sakriani Sakti, Tomoki Toda, Satoshi Nakamura
• Keywords: ACL 2015, Computational Linguistics