This paper describes an algorithm for exact decoding of phrase-based translation models, based on Lagrangian relaxation. The method recovers exact solutions, with certificates of optimality, on over 99% of test examples. The method is much more efficient than approaches based on linear programming (LP) or integer linear programming (ILP) solvers: these methods are not feasible for anything other than short sentences. We compare our method to MOSES (Koehn et al., 2007) , and give precise estimates of the number and magnitude of search errors that MOSES makes.
REF describe an exact method based on Lagrangian relaxation.
Exact Decoding of Phrase-Based Translation Models through Lagrangian Relaxation
EMNLP
Computer Science