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首页> 外文期刊>The Journal of Artificial Intelligence Research >Using Machine Translation to Provide Target-Language Edit Hints in Computer Aided Translation Based on Translation Memories
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Using Machine Translation to Provide Target-Language Edit Hints in Computer Aided Translation Based on Translation Memories

机译：在基于翻译记忆的计算机辅助翻译中使用机器翻译提供目标语言编辑提示

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This paper explores the use of general-purpose machine translation (MT) in assisting the users of computer-aided translation (CAT) systems based on translation memory (TM) to identify the target words in the translation proposals that need to be changed (either replaced or removed) or kept unedited, a task we term as word-keeping recommendation. MT is used as a black box to align source and target sub-segments on the fly in the translation units (TUs) suggested to the user. Source-language (SL) and target-language (TL) segments in the matching TUs are segmented into overlapping sub-segments of variable length and machine-translated into the TL and the SL, respectively. The bilingual subsegments obtained and the matching between the SL segment in the TU and the segment to be translated are employed to build the features that are then used by a binary classifier to determine the target words to be changed and those to be kept unedited. In this approach, MT results are never presented to the translator. Two approaches are presented in this work: one using a word-keeping recommendation system which can be trained on the TM used with the CAT system, and a more basic approach which does not require any training.
机译：本文探讨了通用机器翻译（MT）在协助基于翻译记忆库（TM）的计算机辅助翻译（CAT）系统的用户中识别需要更改的翻译建议中的目标词（替换或删除）或保持未编辑状态（我们称之为“字词建议”的任务）。 MT用作黑匣子，可动态地向用户建议的翻译单位（TU）对齐源子片段和目标子片段。匹配的TU中的源语言（SL）和目标语言（TL）段被分为可变长度的重叠子段，并分别机器翻译为TL和SL。所获得的双语子段以及TU中的SL段与要翻译的段之间的匹配被用来构建特征，然后由二元分类器使用这些特征来确定要更改的目标词和未编辑的目标词。在这种方法中，永远不会将MT结果呈现给翻译者。在这项工作中提出了两种方法：一种是使用可以在CAT系统上使用的TM上进行培训的单词保持推荐系统，另一种是不需要任何培训的基本方法。

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