利用句法信息改进交互式机器翻译

张亚鹏,叶 娜,蔡东风

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PDF(3346 KB)
中文信息学报 ›› 2017, Vol. 31 ›› Issue (2) : 42-48.
机器翻译

利用句法信息改进交互式机器翻译

  • 张亚鹏,叶 娜,蔡东风
作者信息 +

Using Syntactic Information to Improve Interactive Machine Translation

  • ZHANG Yapeng,YE Na,CAI Dongfeng
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摘要

在很多领域中,全自动机器翻译的译文质量还无法达到令人满意的程度。要想获得正确无误的译文,往往需要翻译人员对自动翻译系统的输出进行后处理。在交互式机器翻译的框架内,翻译系统和译员协同工作,译员确认系统提供的译文中的最长正确前缀,系统据此对译文后缀进行预测,共同完成翻译任务。该文利用基于短语的翻译模型,建立了交互式机器翻译系统,并结合交互式机器翻译的特点,利用句法层面的子树信息来指导翻译假设的扩展。实验表明,该方法可以有效地减少人机交互次数。

Abstract

In many domains, the performance of fully automatic machine translation is still not satisfactory. In order to obtain error-free translation, human translators need to perform post-editing on the output of automatic translation systems. Under the framework of interactive machine translation, the translation system and the translator work collaboratively. The translator validates the longest correct prefix in the translation provided by the system, and the system predicts the suffix to complete the sentence. On the basis of phrase-based translation model, this paper built an interactive machine translation system. Considering the characteristics of interactive machine translation, syntactic subtree information is used to guide the extension of translation hypotheses. Experiments show that this method can effectively reduce the interaction time between human and the computer.

关键词

交互式机器翻译 / 子树信息 / 译文前缀

Key words

interactive machine translation / subtree information / translation prefix

引用本文

导出引用
张亚鹏,叶 娜,蔡东风. 利用句法信息改进交互式机器翻译. 中文信息学报. 2017, 31(2): 42-48
ZHANG Yapeng,YE Na,CAI Dongfeng. Using Syntactic Information to Improve Interactive Machine Translation. Journal of Chinese Information Processing. 2017, 31(2): 42-48

参考文献

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基金

国家自然科学基金(61402299)
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