Deadline: 15 January 2019
Most of the translation tools in use today were initially designed to cater for technical, repetitive texts, and this is still their main niche of application 25 years after the appearance of the first versions of those tools. We believe that the evolution of the technologies that underlie computer-aided translation (CAT) – such as concordancing and machine translation –, especially in this era of machine learning and adaptive interfaces, can make electronic translation tools useful to many more translation domains.
One of those domains is that of ‘creative texts’, encompassing fields as varied as literature, advertising, press, etc. Those fields include a wide range of written materials, either in printed or electronic format, which also require high-quality translation. The translation of such materials tends to follow a different workflow when compared to the translation of more specialised texts. However, CAT is becoming more popular among literary translators, who use translation memory tools, for instance, to control repetitiveness in the text (Taivalkoski-Shilov 2018, 3).
It is our vision that translation tools can be made more attractive and useful for professional translators working with creative texts by integrating existing or new technologies into more usable interfaces, which take into account the existing workflows while at the same time providing the benefits reaped by translators in more specialised domains. Those benefits include, for example: storing and retrieving past translations, automatically providing suggestions for expressions that tend to be searched for in external tools, terminology management and quality assurance.
This panel welcomes contributions related, but not limited, to the following topics: - Surveys on the use of technology by creative-text translators† - Case studies of workflows for creative-text translation† - Tools that have been designed for or tested with creative-text translation† - Machine translation systems that have been designed for or tested with creative-text translation† - Studies on the usefulness of specific technologies (translation memory, terminology management, corpora extraction, etc.) for creative-text translation† - Considerations on the potential negative impact of translation technologies on workflows of creative-text translation and work conditions of creative-text translators† - Ethical aspects (e.g. copyright issues)†
- L. Besacier & L. Schwartz. 2015. Automated translation of a literary work: a pilot study. In Proceedings of the Fourth Workshop on Computational Linguistics for Literature. Pp. 114-122.† - J. Moorkens, A. Toral, S. Castilho & A. Way. 2018. Translators’ perceptions of literary post-editing using statistical and neural machine translation. Translation Spaces.† - S. Lšubli, M. Fishel, M. Weibel & M. Volk. 2013. Statistical machine translation for automobile marketing texts. In: Proceedings of the XIV Machine Translation Summit, Nice.† - K. Taivalkoski-Shilov. 2018. Ethical Issues Regarding Machine(-assisted) Translation of Literary Texts. Perspectives: Studies in Translation Theory and Practice. Special Issue: Voice, Translation, and Ethics, ed. by C. Alvstad, A.K. Greenall, H. Jansen & K. Taivalkoski-Shilov. DOI: 10.1080/0907676X.2018.1520907† - A. Toral, M. Wieling & A. Way. 2018. Post-editing Effort of a Novel with Statistical and Neural Machine Translation. Frontiers in Digital Humanities.†
Information about the panel: http://www.est2019.com/wp-content/uploads/2018/10/Translation-technologies-for-creative-text-translation.pdf
Submission instructions: http://www.est2019.com/wp-content/uploads/2018/11/Second-CfP_final.pdf