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This paper presents the University of Cambridge submission to WMT16.Motivated by the complementary nature of syntactical machine translation andneural machine translation (NMT), we exploit the synergies of Hiero and NMT indifferent combination schemes. Starting out with a simple neural latticerescoring approach, we show that the Hiero lattices are often too narrow forNMT ensembles. Therefore, instead of a hard restriction of the NMT search spaceto the lattice, we propose to loosely couple NMT and Hiero by composition witha modified version of the edit distance transducer. The loose combinationoutperforms lattice rescoring, especially when using multiple NMT systems in anensemble.

The Edit Distance Transducer in Action: The University of Cambridge English-German System at WMT16