Effects of machine translation on collaborative work
Effects of machine translation on collaborative work
复制标题
DOI：
10.1145/1180875.1180955
复制
发表时间：
2006-11
期刊：
影响因子：
--
通讯作者：
Naomi Yamashita;T. Ishida
中科院分区：
文献类型：
--
作者：
Naomi Yamashita;T. Ishida
尽管使用机器翻译来克服语言障碍的多语言群体正在增加，但我们仍然缺乏对机器翻译如何影响交流的全面理解。在这项研究中，来自三个不同语言群体（中国、韩国和日本）的八对人员使用嵌入机器翻译的聊天系统，以他们共通的第二语言（英语）以及母语完成指称任务。根据先前的研究，我们预测在对话效率和内容以及在试验过程中指称表达的简化方面会存在差异。定量结果结合访谈数据表明，在机器翻译介导的交流中词汇协同受到了干扰，因为机器翻译的不对称性破坏了重复。此外，指称表达简化的过程也受到了干扰，因为在整个对话过程中翻译对相同的术语不能始终如一地进行翻译。为了在机器翻译介导的交流中支持自然的指称行为，我们需要解决由机器翻译导致的不对称和不一致问题。
Even though multilingual communities that use machine translation to overcome language barriers are increasing, we still lack a complete understanding of how machine translation affects communication. In this study, eight pairs from three different language communities--China, Korea, and Japan--worked on referential tasks in their shared second language (English) and in their native languages using a machine translation embedded chat system. Drawing upon prior research, we predicted differences in conversational efficiency and content, and in the shortening of referring expressions over trials. Quantitative results combined with interview data show that lexical entrainment was disrupted in machine translation-mediated communication because echoing is disrupted by asymmetries in machine translations. In addition, the process of shortening referring expressions is also disrupted because the translations do not translate the same terms consistently throughout the conversation. To support natural referring behavior in machine translation-mediated communication, we need to resolve asymmetries and inconsistencies caused by machine translations.