Hybrid Decoding: Decoding with Partial Hypotheses Combination over Multiple SMT Systems
In this paper, we present hybrid decod-ing — a novel statistical machine transla-tion (SMT) decoding paradigm using mul-tiple SMT systems. In our work, in ad-dition to component SMT systems, sys-tem combination method is also employed in generating partial translation hypothe-ses throughout the decoding process, in which smaller hypotheses generated by each component decoder and hypotheses combination are used in the following de-coding steps to generate larger hypothe-ses. Experimental results on NIST evalu-ation data sets for Chinese-to-English ma-chine translation (MT) task show that our method can not only achieve significant improvements over individual decoders, but also bring substantial gains compared with a state-of-the-art word-level system combination method.
Lei Cui Dongdong Zhang Mu Li Ming Zhou Tiejun Zhao
School of Computer Science and TechnologyHarbin Institute of Technology Microsoft Research Asia School of Computer Science and Technology Harbin Institute of Technology
国际会议
The 23rd International Conference on Computational Linguistics(第23届国际计算语言学大会)
北京
英文
214-222
2010-08-01（万方平台首次上网日期，不代表论文的发表时间）