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This paper describes the 2007 Ngram-based statistical machine translation system developed at the TALP Research Center of the UPC (Universitat Politecnica de Catalunya) in Barcelona. Emphasis is put on improvements and extensions of the previous years system, being highlyghted and empirically compared. Mainly, these include a novel word ordering strategy based on: (1) statistically monotonizing the training source corpus 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 participation in the ACL 2007 SECOND WORKSHOP ON STATISTICAL MACHINE TRANSLATION. Results on three pairs of languages are reported, namely from Spanish, French and German into English (and the other way round) for both the in-domain and out-of-domain tasks.

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