Across Languages and Cultures
Volume/Issue:
Volume 23: Issue 2
A corpus-based search for machine translationese in terms of discourse coherence
Authors:
Yue Jiang School of Foreign Studies, Xi'an Jiaotong University, Xi'an, PR China

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https://orcid.org/0000-0002-0310-2657
and
Jiang Niu School of Foreign Studies, Xi'an Jiaotong University, Xi'an, PR China

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https://orcid.org/0000-0003-4980-1936
Pages:
148–166
Online Publication Date:
07 Nov 2022
Publication Date:
07 Nov 2022
Article Category:
Research Article
DOI:
https://doi.org/10.1556/084.2022.00182
Keywords:
translationese; machine translationese; corpus; discourse coherence; Coh-Metrix
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Abstract

Earlier studies have corroborated that human translation exhibits unique linguistic features, usually referred to as translationese. However, research on machine translationese, in spite of some sparse efforts, is still in its infancy. By comparing machine translation with human translation and original target language texts, this study aims to investigate if machine translation has unique linguistic features of its own too, to what extent machine translations are different from human translations and target-language originals, and what characteristics are typical of machine translations. To this end, we collected a corpus containing English translations of modern Chinese literary texts produced by neural machine translation systems and human professional translators and comparable original texts in the target language. Based on the corpus, a quantitative study of discourse coherence was conducted by observing metrics in three dimensions borrowed from Coh-Metrix, including connectives, latent semantic analysis and the situation/mental model. The results support the existence of translationese in both human and machine translations when they are compared with original texts. However, machine translationese is not the same as human translationese in some metrics of discourse coherence. Additionally, machine translation systems, such as Google and DeepL, when compared with each other, show unique features in some coherence metrics, although on the whole they are not significantly different from each other in those coherence metrics.

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Cover Across Languages and Cultures
Across Languages and Cultures
Print ISSN:
1585-1923
Online ISSN:
1588-2519

Editor-in-Chief: Krisztina KÁROLY (Eötvös Loránd University, Hungary)

Consulting Editor: Dániel MÁNY  (Semmelweis University, Hungary)

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Founding Editor-in-Chief: Kinga KLAUDY (Eötvös Loránd University, Hungary)

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  • Andrew CHESTERMAN (University of Helsinki, Finland)
  • Kirsten MALMKJÆR (University of Leicester, UK)
  • Christiane NORD (University of Free State, Bloemfontein, South Africa)
  • Anthony PYM (Universitat Rovira i Virgili, Tarragona, Spain, University of Melbourne, Australia)
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  • Alessandra RICCARDI (University of Trieste, Italy)
  • Edina ROBIN (Eötvös Loránd University, Hungary)
  • Myriam SALAMA-CARR (University of Manchester, UK)
  • Mohammad Saleh SANATIFAR (independent researcher, Iran)
  • Sanjun SUN (Beijing Foreign Studies University, China)
  • Anikó SOHÁR (Pázmány Péter Catholic University,  Hungary)
  • Sonia VANDEPITTE (University of Gent, Belgium)
  • Albert VERMES (Eszterházy Károly University, Hungary)
  • Yifan ZHU (Shanghai Jiao Tong Univeristy, China)

Prof. Dr. Krisztina KÁROLY 
School of English and American Studies, Eötvös Loránd University
H-1088 Budapest, Rákóczi út 5., Hungary 
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Across Languages and Cultures
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