Paper: Revisiting Pivot Language Approach for Machine Translation

ACL ID P09-1018
Title Revisiting Pivot Language Approach for Machine Translation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009

This paper revisits the pivot language ap- proach for machine translation. First, we investigate three different methods for pivot translation. Then we employ a hybrid method combining RBMT and SMT systems to fill up the data gap for pivot translation, where the source- pivot and pivot-target corpora are inde- pendent. Experimental results on spo- ken language translation show that this hybrid method significantly improves the translation quality, which outperforms the method using a source-target corpus of the same size. In addition, we pro- pose a system combination approach to select better translations from those pro- duced by various pivot translation meth- ods. This method regards system com- bination as a translation evaluation prob- lem and formalizes it with a regression learning ...