Exact Decoding of Syntactic Translation Models through Lagrangian Relaxation.
HLT '11: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1(2011)
摘要
We describe an exact decoding algorithm for syntax-based statistical translation. The approach uses Lagrangian relaxation to decompose the decoding problem into tractable sub-problems, thereby avoiding exhaustive dynamic programming. The method recovers exact solutions, with certificates of optimality, on over 97% of test examples; it has comparable speed to state-of-the-art decoders.
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关键词
decoding problem,exact decoding algorithm,exact solution,Lagrangian relaxation,comparable speed,exhaustive dynamic programming,state-of-the-art decoder,syntax-based statistical translation,test example,tractable sub-problems,syntactic translation model
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