Large-Scale Statistical Machine Translation with Weighted Finite State Transducers

Abstract

The Cambridge University Engineering Department phrase-based statistical machine translation system follows a generative model of translation and is implemented by the composition of component models of translation and movement realised as Weighted Finite State Transducers. Our flexible architecture requires no special purpose decoder and readily handles the large-scale natural language processing demands of state-of-the-art machine translation systems. In this paper we describe the CUED system's participation in the NIST 2008 Arabic-English machine translation evaluation task.