Improving Statistical Machine Translation with a Multilingual Paraphrase Database

Abstract

The multilingual Paraphrase Database (PPDB) is a freely available automatically created resource of paraphrases in mul-tiple languages. In statistical machine translation, paraphrases can be used to provide translation for out-of-vocabulary (OOV) phrases. In this paper, we show that a graph propagation approach that uses PPDB paraphrases can be used to im-prove overall translation quality. We pro-vide an extensive comparison with previ-ous work and show that our PPDB-based method improves the BLEU score by up to 1.79 percent points. We show that our approach improves on the state of the art in three different settings: when faced with limited amount of parallel training data; a domain shift between training and test data; and handling a morpho-logically complex source language. Our PPDB-based method outperforms the use of distributional profiles from monolin-gual source data. 1