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A Structured Language Model for Incremental Tree-to-String Translation

机译:增量树形到字符串转换的结构化语言模型

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Tree-to-string systems have gained significant popularity thanks to their simplicity and efficiency by exploring the source syntax information, but they lack in the target syntax to guarantee the grammaticality of the output. Instead of using complex tree-to-tree models, we integrate a structured language model, a left-to-right shift-reduce parser in specific, into an incremental tree-to-string model, and introduce an efficient grouping and pruning mechanism for this integration. Large-scale experiments on various Chinese-English test sets show that with a reasonable speed our method gains an average improvement of 0.7 points in terms of (T -B )/2 than a state-of-the-art tree-to-string system.
机译:由于通过探索源语法信息,因此通过探索源语法信息,但是通过探索源语法信息,但缺乏效率,因此对目标语法缺乏效率,以保证输出的语法性,因此缺乏普及。 我们不使用复杂的树到树模型,而不是使用特定的左右移位减少解析器集成了一个结构化语言模型,进入了增量树到串模型,并引入了一个有效的分组和修剪机制 这一集成。 关于各种汉英检测集的大型实验表明,具有合理速度,我们的方法在(T-T-T-T-T-T-T-T-T-T-T-T-T-T-T-T Tree-To String方面平均改善了0.7点的平均改善 系统。

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