Predictive translation memory: a mixed-initiative system for human language translation
Predictive translation memory: a mixed-initiative system for human language translation
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预测翻译记忆库：人类语言翻译的混合主动系统
DOI：
10.1145/2642918.2647408
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Christopher D. Manning
中科院分区：
文献类型：
--
作者：
Spence Green;Jason Chuang;Jeffrey Heer;Christopher D. Manning
计算机辅助语言翻译的标准方法是后编辑：机器生成一个单一的翻译，由人工翻译纠正。最近的研究表明，这项简单的技术令人惊讶地有效，但它没有充分利用面向精确的人类和面向召回的机器的互补优势。我们提出了预测翻译记忆库，这是一个交互式的、混合主动性的人类语言翻译系统。翻译者通过考虑根据用户的当前部分翻译进行更新的机器建议来增量地构建翻译。在一项大规模的研究中，我们发现，专业翻译人员在互动模式下速度略慢，但翻译质量略高，尽管之前对基准编辑后条件有丰富的经验。我们的分析确定了时间和质量的重要预测因素，并表征了交互式援助的使用情况。受试者通过互动辅助输入了99%以上的字符，这一比例明显高于之前的研究。
The standard approach to computer-aided language translation is post-editing: a machine generates a single translation that a human translator corrects. Recent studies have shown this simple technique to be surprisingly effective, yet it underutilizes the complementary strengths of precision-oriented humans and recall-oriented machines. We present Predictive Translation Memory, an interactive, mixed-initiative system for human language translation. Translators build translations incrementally by considering machine suggestions that update according to the user's current partial translation. In a large-scale study, we find that professional translators are slightly slower in the interactive mode yet produce slightly higher quality translations despite significant prior experience with the baseline post-editing condition. Our analysis identifies significant predictors of time and quality, and also characterizes interactive aid usage. Subjects entered over 99% of characters via interactive aids, a significantly higher fraction than that shown in previous work.
影响因子：
4.3
作者：
Barr, Dale J.;Levy, Roger;Scheepers, Christoph;Tily, Harry J.
通讯作者：
Tily, Harry J.