IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v12y2022i4p21582440221142210.html
   My bibliography  Save this article

Automated and Human Interaction in Written Discourse: A Contrastive Parallel Corpus-based Investigation of Metadiscourse Features in Machine-Human Translations

Author

Listed:
  • Muhammad Afzaal
  • Muhammad Imran
  • Xiangtao Du
  • Norah Almusharraf

Abstract

The rise of the internet has generated a need for fast online translations, which human translators cannot meet. Statistical tools such as Google and Baidu Translate provide automatic translation from one written language to another. This study reports the descriptive comparison of the machine-translation (MT) with human translation (HT), considering the metadiscoursal interactional features. The study uses a parallel corpus consisting of 79 texts translated from Chinese to English by professional human translators and machine translations (Baidu translate & Google translate) and a comparable reference corpus of non-translated English text. The statistical analysis revealed no statistically significant difference between Baidu and Google translate regarding all types of metadiscoursal indicators. However, the findings of this study demonstrate significant disparities in the interactional characteristics of various HT and MT groups. Compared to the metadiscourse features in non-translated English political texts, human translators were found to outperform machine translations in the use of attitude markers. In contrast, the distribution of directives in machine-translated texts is more native-like. In addition, MT and HT have utilized a significantly smaller number of hedges, self-mention, and readers than non-translated texts. Our results indicate that the MT systems, though still calling for further improvement, have shown tremendous growth potential and may complement human translators.

Suggested Citation

  • Muhammad Afzaal & Muhammad Imran & Xiangtao Du & Norah Almusharraf, 2022. "Automated and Human Interaction in Written Discourse: A Contrastive Parallel Corpus-based Investigation of Metadiscourse Features in Machine-Human Translations," SAGE Open, , vol. 12(4), pages 21582440221, December.
    • Handle: RePEc:sae:sagope:v:12:y:2022:i:4:p:21582440221142210
    DOI: 10.1177/21582440221142210
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440221142210
    Download Restriction: no
    File URL: https://libkey.io/10.1177/21582440221142210?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Siu Wing Yee Barbara & Muhammad Afzaal & Hessah Saleh Aldayel, 2024. "A corpus-based comparison of linguistic markers of stance and genre in the academic writing of novice and advanced engineering learners," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:sagope:v:12:y:2022:i:4:p:21582440221142210. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.