Cognitive efficiency in translation

Abstract

This article concerns the cognitive mechanisms that underlie the efficient allocation of cognitive resources during the translation process. Three indicators of efficient resource allocation are outlined and examined as correlates of translation expertise: flexibility, automaticity, and processing flow. Analyses of eye tracking and keylogging data from two groups of translatorsprofessional translators and student translators-reveal that the more experienced group performs more efficiently. Professionals exhibit greater variation in attention unit duration, indicating greater cognitive flexibility and adaptability, while analysis of pupillary data suggests a lower cognitive load on professional translators' cognitive systems. The two groups of translators exhibit different processing flow patterns. The study demonstrates that analyses of cognitive flexibility, cognitive automaticity, and processing flow are useful to determine processing efficiency in translation.

Translators’ Use of Digital Resources during Translation

“…Automation, or automaticity, is the execution of an activity with relatively few cognitive resources (Anderson 2000: 98, Baddeley 2007. In translation, automation has been proposed as a likely explanation for professional translators' relatively smaller pupils compared with those of novice translators (Hvelplund 2016). Through repetition and practice, professional translators have developed habit patterns and schemata which enable them to perform certain tasks, such as typing and text scanning, relatively more effortlessly than novice translators.…”

“…Taking a more granular look at the different kinds of reading that may take place during the translation process, While measures of fixations have been popular to describe overall reading characteristics of translation reading, some studies have also examined differences in pupil sizes in order to examine the workload that is placed on the translator's cognitive system while translating. Hvelplund (2011) and(2016) are examples of such studies and they demonstrate that expertise (professional vs novice) as well as reading type (source text reading vs target text reading) have a clear effect on pupil size: professionals seem to automate translation behaviour more than novices and target text reading involves more effort than source text reading.…”

Processing possessives in translation between unequal systems. An exploratory study

“…A follow-up study might benefit from inferential statistical testing of the results (cf. Hvelplund (2016)).…”

Stress, cognitive, emotional and ergonomic demands in interpreting and translation

“…Almost all studies used physiological data to investigate cognitive demands (n=14). They did so with regard to post-editing (Fonseca, 2019;Koglin & Cunha, 2019), directionality (Chang, 2011;Pavlović & Jensen, 2009;Su & Li, 2019), translation memory matches (O'Brien, 2006(O'Brien, , 2008), text difficulty (Liu, Zheng, & Zhou, 2019), word translation difficulty (Lachaud, 2011;Pfurtscheller et al, 2007), professionality (Hvelplund, 2016), the processing of subtasks in dubbing translation (Hvelplund, 2017a), source text versus target text processing (Hvelplund, 2017b), and digital resource consultation (Hvelplund, 2017c). The two exceptions are Baghi and Khoshsaligheh (2019) who conducted a study on stress during written and sight translation, and Lehr and Hvelplund (2020) who investigated emotional response to different source texts and how that response affected the allocation of cognitive resources.…”