In statistical machine translation field, the phrase-based translation model outperforms the word-based translation model.

在统计机器翻译领域，基于短语的翻译模型的性能优于基于词的翻译模型。

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Based on phrase-based statistical machine translation, a dynamical programming beam search decoding algorithm is put forward combining multi futures model using log-liner model approach.

在基于短语的统计机器翻译的基础上，结合对数线性模型的思想加入多个特征模型，研究了一种动态规划的柱搜索解码算法。

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Based on the current statistical machine translation, the size of corpus and the accuracy of word alignment mainly affect the performance of SMT systems.

在当前的基于统计的翻译方法中，双语语料库的规模、词对齐的准确率对于翻译系统的性能有很大的影响。

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