| 摘要 |
Systems and methods are described that facilitate phrase-based statistical machine translation (SMT) incorporating bigram (or higher n-gram) language models by modeling bi-phrases as nodes in a graph. Additionally, construction of a translation is modeled as a “tour” amongst the nodes of the graph, such that a translation solution is generated by treating the graph as a generalized traveling salesman problem (GTSP) and solving for an optimal tour. The overall cost of a tour is computed by adding the costs associated with the edges traversed during the tour. Thus, the described systems and methods map the SMT problem directly into a GTSP problem, which itself can be directly converted into a TSP problem.
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