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cs.CL2026
What do the metrics mean? A critical analysis of the use of Automated Evaluation Metrics in Interpreting
Jonathan Downie, Joss Moorkens
With the growth of interpreting technologies, from remote interpreting and Computer-Aided Interpreting to automated speech translation and interpreting avatars, there is now a high…
cs.CL2025
Extending CREAMT: Leveraging Large Language Models for Literary Translation Post-Editing
Antonio Castaldo, Sheila Castilho, Joss Moorkens +1
Post-editing machine translation (MT) for creative texts, such as literature, requires balancing efficiency with the preservation of creativity and style. While neural MT systems s…
cs.CL2025
Sociotechnical Effects of Machine Translation
Joss Moorkens, Andy Way, Séamus Lankford
While the previous chapters have shown how machine translation (MT) can be useful, in this chapter we discuss some of the side-effects and risks that are associated, and how they m…