Recognition of translator expertise using sequences of fixations and keystrokes
Recognition of translator expertise using sequences of fixations and keystrokes
复制标题
使用注视和击键序列来识别译者的专业知识
DOI：
10.1145/2578153.2578201
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Akiko Aizawa
中科院分区：
文献类型：
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作者：
Pascual Martínez;A. Minocha;Jin Huang;M. Carl;S. Bangalore;Akiko Aizawa
专业的人工翻译对于满足工业和政府机构的高质量标准是必要的。翻译人员在翻译过程中从事多种活动，有必要对他们的行为进行建模，目的是了解和优化翻译过程。近年来，用户界面使我们能够记录用户事件，如眼球运动或击键。虽然对翻译过程已经有了深刻的描述性分析，但在进行定量推理方面有多种优势。我们提出了将注视和击键序列分类为活动和模型翻译会话的方法，目的是识别译者的专业知识。我们在识别认证译者及其多年经验的任务中显示了显著的错误减少，并分析了特征模式。
Professional human translation is necessary to meet high quality standards in industry and governmental agencies. Translators engage in multiple activities during their task, and there is a need to model their behavior, with the objective to understand and optimize the translation process. In recent years, user interfaces enabled us to record user events such as eye-movements or keystrokes. Although there have been insightful descriptive analysis of the translation process, there are multiple advantages in enabling quantitative inference. We present methods to classify sequences of fixations and keystrokes into activities and model translation sessions with the objective to recognize translator expertise. We show significant error reductions in the task of recognizing certified translators and their years of experience, and analyze the characterizing patterns.