Translation, Cognition & Behavior - Volume 3, Issue 1, 2020

This study investigated cognitive aspects of sight translation by analysing the reading behaviour in the process and the output. In our empirical study, two groups of participants—interpreting trainees and untrained bilinguals—carried out three tasks: (a) silent reading, (b) reading aloud, and (c) sight translation. The results show that the two groups were almost identical in the first two tasks, further substantiating the similarity of their language command, but were drastically different in how they tackled sight translation. Interpreting trainees provided much more accurate, fluent, and adequate renditions with much less time and fewer fixations. However, their efficiency at information retrieval was statistically similar to that of the untrained bilinguals. Thus, interpreting trainees were more efficient by being more “economical” during reading, rather than by reading ahead faster, as some would intuitively expect. Chunking skills seem to have also been at play behind their remarkable performance.

Within the world of interpreting, persistent clichés exist about an interpreter’s required personality and cognitive traits. For instance, an interpreter is thought to be communicative, stress-resistant and to have excellent memory skills. Yet, while research has been conducted into interpreters’ personality type and into their cognitive skills, these two aspects have not yet been combined in one research design. In this contribution we will explore whether some of these traits increase the likelihood of a language major opting for a study programme in interpreting and for a language professional opting for an interpreting career. Through a principal component analysis, we identified five latent components (personality, inhibition, updating, shifting, and working memory span) in a battery of personality and cognitive variables. Binary logistic regression showed that personality and working memory span are strong predictors of language majors and language professionals’ choice for a study programme or career path in interpreting.

Hesitation and lexical repair markers are part of almost every audibly pronounced sentence. Empirical linguistics generally bases its examinations on spontaneous speech production. This paper uses the discourse analytical approach of empirical linguistics to analyse think-aloud protocols produced by translators and lawyers in a mixed methods study combining thinking aloud and eyetracking. Two expert groups—lawyers and translators, comprising both professionals and students—read complex legal texts in French and summarised them in German, their mother tongue. A mainly qualitative analysis evaluates and categorises the occurrences and functions of various German hesitation and discourse markers. This not only provides information about the use of fillers and repair actions during speech but also insights into reception processes and perceptions of text difficulty. A quantitative analysis of pause fillers suggests that the reception processes of lawyers and translators differ.

The translation process can be studied as sequences of activity units. The application of machine learning technology offers researchers new possibilities in the study of the translation process. This research project developed a program, activity unit predictor, using the Hidden Markov Model. The program takes in duration, translation phase, target language and fixation as the input and produces an activity unit type as the output. The highest prediction accuracy reached is 61%. As one of the first endeavors, the program demonstrates strong potential of applying machine learning in translation process research.

This article examines the use of raw, unedited machine-translated texts by patent professionals using the framework of distributed cognition. The goals of the study were to evaluate whether the concept of distributed cognition is a useful theoretical lens for examining and explaining raw MT reception, and to contribute to our knowledge of raw MT use through an analysis of a real-life use case. The study revealed that patent professionals often rely on a large network of artifacts and people to help them in the task of understanding raw MT, and therefore the concept of distributed cognition was applicable and useful. The study also contributed new knowledge to our overall understanding of the use of raw MT.

Norm theory was invented in 1986, by Daniel Kahneman and Dale T. Miller, as a decision-science subdiscipline of psychology, but with close connections with emerging embodied, embedded, enactive, extended and affective (4EA) cognitive science. Notably, they gave affective response a key role in marking not only the intensity but the cognitive load of norm-formative decision-making. A few years later, in the early 1990s, Gideon Toury, Andrew Chesterman, and other translation scholars began to theorize translational norms—with a very different model that apparently owed nothing to Kahneman and Miller’s pioneering work. In translational norm theory, norms are established based on the rational work of competent professionals, and anyone who doesn’t simply obey those norms cannot be considered a professional. This article rethinks translational norm theory using not only Kahneman & Miller but the later convergence of Merleau-Ponty’s lived experience with cognitive science in 4EA cognition.