"MT and creative texts: a study of translations, translators’ attitude and readers’ views"

by Dr Vilelmini Sosoni, Ionian University

Update: the event has now finished (Jan 29th 2021).


Many of the translation tools in use today were initially designed to cater for technical, repetitive texts. This is still their main niche 25 years after the first versions of these tools appeared. Computer-aided translation (CAT) and Machine translation (MT) were long regarded as unsuitable for the translation of creative texts, which have a predominant expressive or operative function. This means that they exploit the expressive and associative possibilities of language in order to communicate the writer’s thoughts in an artistic, creative way or induce behavioural responses, as stimuli to action or reaction on the part of the reader. Their translation is anything but straightforward, given that it is not sufficient to merely preserve the meaning, but also preserve the reading experience of the original text (Toral and Way, 2018). In other words, the translation of creative texts should “undo the original” (de Man, 1986) to deal with the uniqueness of the source and target languages and source and target audiences. This undoing requires uniquely human skills and does not seem to fit within the dominant translation workflow where a text is fed into an MT engine to be further post-edited by a translator (Lommel and DePalma, 2016).

Lately advances in Neural Machine Translation (NMT) have led to an improved quality of the MT output, especially at the level of fluency (Castilho et al, 2017a; 2017b) even for lexically-rich texts (Bentivogli et al, 2016), and as a result its use for the translation of creative texts is increasingly put to the test. In the present talk, I will attempt to compare the quality of creative texts, i.e. literary and promotional texts, when translated from scratch with their quality following an MT and PE scenario, based on a fine-grained human error analysis. I will also investigate the translators’ attitudes and perceptions vis-à-vis MT and PE of creative texts and the texts’ reception by average readers.


  • Bentivogli, Luisa, Andriana Bisazza, Mauro Cettolo, Marcello Federico. 2016. Neural versus phrase-based machine translation quality: a case study. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, Austin, Texas, pp 257–267
  • Castilho, Sheila, Joss Moorkens, Federico Gaspari, Rico Sennrich, Vilelmini Sosoni, Panayota Georgakopoulou, Pintu Lohar, Andy Way, Antonio Valerio Miceli Barone, Maria Gialama. 2017a. “A Comparative Quality Evaluation of PBSMT and NMT using Professional Translators.” MT Summit 2017, Nagoya, Japan.
  • Castilho, Sheila, Joss Moorkens, Federico Gaspari, Iacer Calixto, John Tinsley, Andy Way. 2017b. “Is Neural Machine Translation the New State of the Art?” The Prague Bulletin of Mathematical Linguistics 108: 109-120.
  • Lommel, Arle, Donald A. DePalma. 2016. Europe’s leading role in Machine Translation: How Europe is driving the shift to MT. Technical report. Common Sense Advisory, Boston.

Speaker’s bio

Dr Vilelmini Sosoni is Senior Lecturer at the Department of Foreign Languages, Translation and Interpreting at the Ionian University in Corfu, Greece, where she teaches Legal and Economic Translation, EU texts Translation and Terminology, Translation Technology, Translation Project Management and Audiovisual Translation (AVT). In the past, she taught Specialised Translation in the UK at the University of Surrey, the University of Westminster and Roehampton University, and in Greece at the National and Kapodistrian University of Athens and the Institut Français d’ Athènes. She also has extensive industrial experience having worked as translator, editor, subtitler and intepreter. She holds a BA in English Language and Linguistics from the National and Kapodistrian University of Athens, an MA in Translation and a PhD in Translation and Text Linguistics from the University of Surrey. Her research interests lie in the areas of Translation of Institutional Texts, Machine Translation (MT), Corpus Linguistics, Cognitive Studies, and AVT. She is a founding member of the Research Lab “Language and Politics” of the Ionian University and a member of the “Centre for Research in Translation and Transcultural Studies” of Roehampton University. She has participated in several EU-funded projects, notably TraMOOC, Eurolect Observatory and Training Action for Legal Practitioners: Linguistic Skills and Translation in EU Competition Law, while she has edited several volumes and books on translation and published numerous articles in international journals and collective volumes.


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