As usual in SMT, it is assumed that the scoring function can be decomposed into a linear combination of K feature functions h k (S), each with a constant weight λ k , so The problem addressed by the decoder is the search for the stateŜ with maximal score, such that The feature functions implemented in our baseline system are identical to the ones found in the popular Moses SMT system (Koehn et al., 2007).
our decoder has the following feature functions: 1. phrase translation scores provided by the phrase table including forward and backward conditional probabilities, lexical weights and a phrase penalty (Koehn et al., 2003), 2. n-gram language model scores implemented with the KenLM toolkit (Heafield, 2011), 3. a word penalty score, 4. a distortion model with geometric decay (Koehn et al., 2003), and 5. a feature indicating the number of times a given distortion limit is exceeded in the current state.