在传统的机器翻译(machine translation,MT)与计算机辅助翻译(computer aided translation,CAT)中,译员与翻译引擎之间的交互受到很大限制,于是产生了交互式机器翻译(interactive machine translation,IMT)技术。但传统的模型只考虑当前源语与部分翻译的目标语的信息,没有将用户交互后的对齐信息加入到之后的预测模型中。该文基于词预测交互式机器翻译的研究思路,将用户交互翻译过程中的鼠标点选行为转化为中间译文的词对齐信息,进而在翻译交互过程中实现了对译文的动态词对齐标注,并在词对齐信息和输入译文的约束下提高了传统词预测的准确性。
Abstract
The traditional interactive machine translation (IMT) is focused on the current source language and the partial translation of the target language, neglecting the feedback from the translators to better predict the subsequent translations. This paper investigates the translation selection clicks, and proposes a dynamic word alignment model for the partial translation. Experiment indicates this method improves the word prediction accuracy during the interactive machine translation process.
关键词
交互式机器翻译 /
词对齐 /
预测模型
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Key words
interactive machine translation /
word alignment /
prediction model
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参考文献
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脚注
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基金
国家自然科学基金(61403262,61402299)
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