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。

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

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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。

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.

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为了处理统计机器翻译中的长距离调序，在基于短语的统计翻译模型的基础上提出了句法调序模型。

To deal with the long-distance reordering, a linguistically syntax-based reordering model was presented for phrasal statistical machine translation.

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