Ngram-based statistical machine translation enhanced with multiple weighted reordering hypotheses

This paper describes the 2007 Ngram-based sta-tistical machine translation system developed at the TALP Research Center of the UPC (Uni-versitat Politecnica de Catalunya) in Barcelona. Emphasis is put on improvements and extensions of the previous years system, being highlighted and empirically compared. Mainly, these include a novel word ordering strategy based on: (1) sta-tistically monotonizing the training source cor-pus and (2) a novel reordering approach based on weighted reordering graphs. In addition, this system introduces a target language model based on statistical classes, a feature for out-of-domain units and an improved optimization procedure. The paper provides details of this system par-ticipation in the ACL 2007 SECOND WORK-SHOP ON STATISTICAL MACHINE TRANSLA-TION. Results on three pairs of languages are reported, namely from Spanish, French and Ger-man into English (and the other way round) for both the in-domain and out-of-domain tasks.