No abstract

Machines are learning fast, and human translators must keep pace by learning with, from and about them. Deep learning (DL) and neural machine translation (NMT) are set to change the reality of translation and the distributions of tasks. Although theoretical and practical courses on computer-aided and/or machine translation abound, less attention has been paid to DL and NMT in most translation programmes. The challenge for translation education is to give students the knowledge and toolkits to learn when and how to embrace the new technologies, and to exploit how and when the added value of human intuition, creativity and ethics can and should be deployed.

CAT tools have become a fixture of professional translation over the last two decades yet are still treated with suspicion or disinterest by many freelancers. Acknowledged to contribute to consistency and speed, they can constrain and otherwise negatively affect the translation process in various ways. Surveys of professional translators and observations at the workplace suggest that there is a degree of frustration associated with the use of CAT tools and room for improvement in their usability. A recent large-scale survey of professional translators included specific items for CAT tool users about whether any features of their tools were irritating or missing. Many reported that there were and also availed themselves of the opportunity to provide detailed comments about them. More than half of the CAT tool users said that they found some features irritating, and a quantitative and qualitative analysis of their comments revealed that the most common issues concerned the complexity of the user interface and segmentation. There were some differences in the responses between freelance, institutional and commercial translators but almost none across age groups. The comments about missing features also tended to be about making the tools easier to use. The focus in the survey reported here was on identifying negative aspects of tools with a view to mitigating them and tailoring the tools more to translators' needs. However, there is also room for research exploring the positive aspects of tools in the interests of optimising their usability and reducing cognitive friction.

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Abstract Encountered at all levels of language, conceptual asymmetries between source and target languages present translators with fundamental challenges that require problem awareness, problem identification and problem solving. A case in point is conceptual metaphor in translation. Versions of conceptual metaphor theory have been applied in various productoriented studies of how translators deal with the challenge of metaphor in translation. However, there is potential in combining product-oriented approaches with techniques used to access translators’ cognitive processes, although process-oriented studies on how conceptual metaphor is re-conceptualised or re-mapped in translation are still rare. Building on an exploratory study carried out at our institute, in which findings from translation process data suggest that experience and/or training appears to be a main factor in handling conceptual metaphor, we present some salient features of re-mapping metaphor. Triangulating data from target-text products, keystroke logs and retrospective verbal commentaries collected under very similar conditions in a laboratory setting, we analyse how translators at different levels of experience handle two complex conceptual metaphors. The results appear to suggest that complex metaphor might indeed be culturespecific. They also potentially indicate that re-mapping practices are a function of experience and that re-mapping to a source-language target domain could create more uncertainty than generic-level re-mapping. Both findings hold pedagogical implications, which are discussed together with some methodological issues.