This volume argues for an innovative interdisciplinary approach to the analysis and
translation of literary style, based on a mutually supportive combination of traditional close …

Natural language processing (NLP) applications are now more powerful and ubiquitous
than ever before. With rapidly developing (neural) models and ever-more available data …

Given the rise of the new neural approach to machine translation (NMT) and its promising
performance on different text types, we assess the translation quality it can attain on what is …

In the context of recent improvements in the quality of machine translation (MT) output and
new use cases being found for that output, this article reports on an experiment using …

Literary translation is a culturally significant task, but it is bottlenecked by the small number
of qualified literary translators relative to the many untranslated works published around the …

We conduct the first experiment in the literature in which a novel is translated automatically
and then post-edited by professional literary translators. Our case study is Warbreaker, a …

The continuing growth in digital content means that there is now significantly more linguistic
content to translate using more diverse workflows and tools than ever before. This growth …

Sociolinguistic studies investigate the relation between language and extra-linguistic
variables. This requires both representative text data and the associated socio-economic …

Contrary to perceived wisdom, we explore the role of machine translation (MT) in assisting
with the translation of literary texts, considering both its limitations and its potential. Our …

The recent years have witnessed an increasing importance of machine translation systems
due to the prolific production on online texts in different disciplines and furthermore, the …