计算机应用 ›› 2015, Vol. 35 ›› Issue (4): 1009-1012.DOI: 10.11772/j.issn.1001-9081.2015.04.1009

• 人工智能 • 上一篇    下一篇

交互式机器翻译中译文查询行为的预测技术

季铎1,2, 马斌2, 叶娜2   

  1. 1. 南京航空航天大学 计算机科学与技术学院, 南京 210016;
    2. 沈阳航空航天大学 知识工程研究中心, 沈阳 110136
  • 收稿日期:2014-10-21 修回日期:2014-12-17 出版日期:2015-04-10 发布日期:2015-04-08
  • 通讯作者: 马斌
  • 作者简介:季铎(1981-),男,辽宁葫芦岛人,副教授,博士研究生,主要研究方向:自然语言处理、机器翻译; 马斌(1990-),男,山东聊城人,硕士研究生,主要研究方向:自然语言处理、机器翻译; 叶娜(1981-),女,辽宁沈阳人,讲师,博士,主要研究方向:机器翻译。
  • 基金资助:

    国家自然科学基金资助项目(61403262)。

Prediction technology of translation query behavior in interactive machine translation

JI Duo1,2, MA Bin2, YE Na2   

  1. 1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing Jiangsu 210016, China;
    2. Knowledge Engineering Research Center, Shenyang Aerospace University, Shenyang Liaoning 110136, China
  • Received:2014-10-21 Revised:2014-12-17 Online:2015-04-10 Published:2015-04-08

摘要:

以交互式机器翻译(IMT)为研究背景,针对用户在翻译过程中调用双语查词而导致的鼠标-键盘频繁切换的问题,提出了一种面向翻译查词行为的预测模型。该模型将查词行为转化为当前翻译条件下的译文选择问题,利用对齐模型、翻译模型和语言模型实现了高准确率的查词行为预测。在人工双语对齐语料的测试中,该方法预测准确率约为64.99%,特别对占有比例较高的名词预测正确率可达71.43%,能有效减少人工翻译中的重复性和机械性操作,改善了用户使用交互翻译系统的翻译体验,从而提高翻译效率。

关键词: 机器翻译, 交互式翻译, 翻译行为, 预测模型

Abstract:

To deal with the problems of frequent switches between mouse and keyboard when the users call the bilingual words searching in the process of translation, a prediction model oriented word searching behavior was proposed based on Interactive Machine Translation (IMT). This behavior of word searching was transformed into the selection problems under the condition of current translation, and the prediction of the word searching behavior was achieved with a high accuracy using the alignment model, translation model and language model. In the tests of artificial bilingual alignment corpus, the prediction accuracy of the approach is about 64.99%, and especially for the prediction of noun, the prediction accuracycan reach 71.43%. The approach effectively reduces the repeatability and mechanical operations in the manual translation, and improves the user's translation experience when using the interactive translation system, which also improves the translation efficiency.

Key words: Machine Translation (MT), interactive translation, translation behavior, prediction model

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