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dc.contributor.authorKunilovskaya, Maria
dc.contributor.authorCorpas Pastor, Gloria
dc.contributor.editorWang, Vincent
dc.contributor.editorLim, Lily
dc.contributor.editorLi, Defeng
dc.date.accessioned2021-10-15T11:34:05Z
dc.date.available2021-10-15T11:34:05Z
dc.date.issued2021-10-12
dc.identifier.citationKunilovskaya M., Corpas Pastor G. (2021) Translationese and register variation in English-to-Russian professional translation. In: Wang V.X., Lim L., Li D. (eds) New Perspectives on Corpus Translation Studies. New Frontiers in Translation Studies. Springer, Singapore. https://doi.org/10.1007/978-981-16-4918-9_6en
dc.identifier.isbn9789811649172en
dc.identifier.doi10.1007/978-981-16-4918-9_6en
dc.identifier.urihttp://hdl.handle.net/2436/624409
dc.descriptionThis is an accepted manuscript of a chapter published by Springer in Wang V.X., Lim L., Li D. (eds.) New Perspectives on Corpus Translation Studies. New Frontiers in Translation Studies, available online: https://doi.org/10.1007/978-981-16-4918-9_6 The accepted version of the publication may differ from the final published version. For re-use please see the publisher's reuse policy.en
dc.description.abstractThis study explores the impact of register on the properties of translations. We compare sources, translations and non-translated reference texts to describe the linguistic specificity of translations common and unique between four registers. Our approach includes bottom-up identification of translationese effects that can be used to define translations in relation to contrastive properties of each register. The analysis is based on an extended set of features that reflect morphological, syntactic and text-level characteristics of translations. We also experiment with lexis-based features from n-gram language models estimated on large bodies of originally- authored texts from the included registers. Our parallel corpora are built from published English-to-Russian professional translations of general domain mass-media texts, popular-scientific books, fiction and analytical texts on political and economic news. The number of observations and the data sizes for parallel and reference components are comparable within each register and range from 166 (fiction) to 525 (media) text pairs; from 300,000 to 1 million tokens. Methodologically, the research relies on a series of supervised and unsupervised machine learning techniques, including those that facilitate visual data exploration. We learn a number of text classification models and study their performance to assess our hypotheses. Further on, we analyse the usefulness of the features for these classifications to detect the best translationese indicators in each register. The multivariate analysis via text classification is complemented by univariate statistical analysis which helps to explain the observed deviation of translated registers through a number of translationese effects and detect the features that contribute to them. Our results demonstrate that each register generates a unique form of translationese that can be only partially explained by cross-linguistic factors. Translated registers differ in the amount and type of prevalent translationese. The same translationese tendencies in different registers are manifested through different features. In particular, the notorious shining-through effect is more noticeable in general media texts and news commentary and is less prominent in fiction.en
dc.formatapplication/pdfen
dc.language.isoenen
dc.publisherSpringer Singaporeen
dc.relation.ispartofseriesNew Frontiers in Translation Studiesen
dc.relation.urlhttps://link.springer.com/chapter/10.1007/978-981-16-4918-9_6en
dc.subjectEnglishen
dc.subjectRussianen
dc.subjectparallel corporaen
dc.subjecttranslationese indicatorsen
dc.subjectregister variationen
dc.subjectlanguage and arts disciplinesen
dc.subjecttranslationen
dc.subjecttranslationese trendsen
dc.subjectmachine learningen
dc.titleTranslationese and register variation in English-to-Russian professional translationen
dc.typeChapter in booken
dc.date.updated2021-10-14T10:04:09Z
pubs.edition1
pubs.place-of-publicationSingapore
rioxxterms.funderUniversity of Wolverhamptonen
rioxxterms.identifier.projectUOW15102021GCPen
rioxxterms.versionAMen
dc.source.booktitleNew Perspectives on Corpus Translation Studies
dc.description.versionPublished version
refterms.dateFCD2021-10-15T11:17:05Z
refterms.versionFCDAM


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