Speech Synthesis in the Translation Revision Process: Evidence from Error Analysis, Questionnaire, and Eye-Tracking

Abstract

Translation revision is a relevant topic for translator training and research. Recent technological developments justify increased focus on embedding speech technologies—speech synthesis (text-to-speech) and speech recognition (speech-to-text)—into revision workflows. Despite some integration of speech recognition into computer-assisted translation (CAT)/translation environment tools (TEnT)/Revision tools, to date we are unaware of any CAT/TEnT/Revision tool that includes speech synthesis. This paper addresses this issue by presenting initial results of a case study with 11 participants exploring if and how the presence of sound, specifically in the source text (ST), affects revisers’ revision quality, preference and viewing behaviour. Our findings suggest an improvement in revision quality, especially regarding Accuracy errors, when sound was present. The majority of participants preferred listening to the ST while revising, but their self-reported gains on concentration and productivity were not conclusive. For viewing behaviour, a subset of eye-tracking data shows that participants focused more on the target text (TT) than the source regardless of the revising condition, though with differences in fixation counts, dwell time and mean fixation duration (MDF). Orientation and finalisation phases were also identified. Finally, speech synthesis appears to increase perceived alertness, and may prompt revisers to consult external resources more frequently.

Keywords

• translation revision
• speech synthesis
• computer-assisted translation (cat)
• eye-tracking
• error detection
• error analysis