In order to effectively direct the translation process by syntax information, a greedy direct decoding algorithm is proposed for the syntax-based tree-to-string statistical translation model.

为了有效利用句法信息指导翻译过程，提出了基于贪心搜索的树-串句法统计翻译模型的正向解码算法。

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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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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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