The translation industry is constantly seeking ways to improve speed and quality, leading to the incorporation of various technological advancements into translation workflows ( Bowker, 2002 Mossop, 2006 O’Brien, 2012). 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. No effect of text difficulty was observed. 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. Data were collected using keylogging, subjective ratings, screen recording, and a questionnaire. 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. 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. 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. ![]() Previous research has found that the use of automatic speech recognition (ASR) tools for dictating translations can increase productivity. ![]() Technologies can greatly improve translators’ productivity and reduce their workload. School of English and International Studies, Beijing Foreign Studies University, Beijing, China.
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