IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v11y2021i4p21582440211054501.html
   My bibliography  Save this article

Product and Process Analysis of Machine Translation into the Inflectional Language

Author

Listed:
  • Dasa Munkova
  • Michal Munk
  • Katarina Welnitzova
  • Johanna Jakabovicova

Abstract

This study focuses on the influence of quality of Machine Translation (MT) output on a translator’s performance. We analyze the translator’s effort by product analysis and process analysis. The product analysis consists of MT quality evaluation according to the Dynamic Quality Framework; using error typology and the criteria such as fluency and adequacy. We examine translator’s effort from the point of view of typing time, in the context of MT quality—focusing on error rate in language, accuracy, terminology, and style, and also in fluency and adequacy to the source text. We have found that the translator’s performance is influenced by MT quality. The typing time is very closely related to errors in language, accuracy, terminology, and style as well as to fluency and adequacy. We used the Mann-Whitney test to compare the productivity of post-editing of MT with human translation. The results of the study have shown that post-editing—compared to human translation of journalistic text from English into the inflectional Slovak language is more effective.

Suggested Citation

  • Dasa Munkova & Michal Munk & Katarina Welnitzova & Johanna Jakabovicova, 2021. "Product and Process Analysis of Machine Translation into the Inflectional Language," SAGE Open, , vol. 11(4), pages 21582440211, November.
  • Handle: RePEc:sae:sagope:v:11:y:2021:i:4:p:21582440211054501
    DOI: 10.1177/21582440211054501
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440211054501
    Download Restriction: no

    File URL: https://libkey.io/10.1177/21582440211054501?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
    ---><---

    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:11:y:2021:i:4:p:21582440211054501. 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.