Wang Lulu, Sun Sanjun
School of English and International Studies, Beijing Foreign Studies University, Beijing, China.
Front Psychol. 2023 Jan 19;14:1108898. doi: 10.3389/fpsyg.2023.1108898. eCollection 2023.
Technologies can greatly improve translators' productivity and reduce their workload. Previous research has found that the use of automatic speech recognition (ASR) tools for dictating translations can increase productivity. However, these studies often had small sample sizes and did not consider other important aspects of translators' performance, such as translation quality and cognitive effort. This study aims to investigate the impact of text input method on translators' performance in terms of task duration, time allocation, editing operations, cognitive effort, and translation quality, as well as whether text difficulty affects these factors. To do this, 60 Chinese translation trainees were randomly assigned to either a dictation group or a typing group, and completed two English-Chinese translations of varying levels of source-text difficulty. Data were collected using keylogging, subjective ratings, screen recording, and a questionnaire. The results showed that using ASR reduced the typing effort of participants without negatively affecting translation quality, but did not save time or reduce cognitive effort. No effect of text difficulty was observed. Analysis of the revisions made by the dictation group and the results of the post-test questionnaire provide insights into how ASR systems can be optimized for translation purposes.
技术可以极大地提高翻译人员的工作效率并减轻他们的工作量。先前的研究发现，使用自动语音识别（ASR）工具进行听写翻译可以提高工作效率。然而，这些研究的样本量往往较小，并且没有考虑翻译人员表现的其他重要方面，例如翻译质量和认知努力。本研究旨在从任务时长、时间分配、编辑操作、认知努力和翻译质量等方面，调查文本输入方式对翻译人员表现的影响，以及文本难度是否会影响这些因素。为此，60名中国翻译学员被随机分配到听写组或打字组，并完成了两篇源文本难度不同的英汉翻译。通过按键记录、主观评分、屏幕录制和问卷调查收集数据。结果表明，使用ASR减少了参与者的打字工作量，且对翻译质量没有负面影响，但没有节省时间或减少认知努力。未观察到文本难度的影响。对听写组所做修订的分析以及测试后问卷的结果，为如何针对翻译目的优化ASR系统提供了见解。
