Domain adaptation of statistical machine translation models with monolingual data for cross lingual information retrieval

Abstract

Statistical Machine Translation (SMT) is often used as a black-box in CLIR tasks. We propose an adaptation method for an SMT model relying on the monolingual statistics that can be extracted from the document collection (both source and target if available). We evaluate our approach on CLEF Domain Specific task (German-English and English-German) and show that very simple document collection statistics integrated in SMT translation model allow to obtain good gains both in terms of IR metrics (MAP, P10) and MT evaluation metrics (BLEU, TER). © 2013 Springer-Verlag.