Human factors in machine translation and post-editing among institutional translators

被引:40
|
作者
Cadwell, Patrick [1 ]
Castilho, Sheila [2 ]
O'Brien, Sharon [1 ]
Mitchell, Linda [3 ]
机构
[1] Dublin City Univ, ADAPT Ctr, Sch Appl Language & Intercultural Studies, Dublin 9, Ireland
[2] Dublin City Univ, ADAPT Ctr, Dublin 9, Ireland
[3] Thaler Str 27, D-13129 Berlin, Germany
关键词
machine translation (MT); post-editing (PE); ergonomics; human factors; Directorate-General for Translation (DGT); focus groups;
D O I
10.1075/ts.5.2.04cad
中图分类号
H [语言、文字];
学科分类号
05 ;
摘要
In September 2015, the ADAPT Centre for Digital Content Technology carried out a focus group study of 70 translators at the European Commission's Directorate-General for Translation (DGT). (1) The aim was to better understand the factors involved in the translators' adoption and non-adoption of machine translation (MT) during their translation tasks. Our analysis showed that, while broadly positive attitudes to MT could be observed, MT was not consistently adopted for all tasks. We argue that ergonomic factors related to a human translator's needs, abilities, limitations, and overall well-being heavily impacted on participants' decisions to use MT or not in their tasks. We further claim that it is only by taking into account the special institutional circumstances in which the activity of DGT translation is situated that these ergonomic factors can be fully understood and explained.
引用
收藏
页码:222 / 243
页数:22
相关论文
共 50 条
  • [21] Post-editing neural machine translation versus translation memory segments
    Sanchez-Gijon, Pilar
    Moorkens, Joss
    Way, Andy
    [J]. MACHINE TRANSLATION, 2019, 33 (1-2) : 31 - 59
  • [22] Cognitive effort in human translation and machine translation post-editing processes A holistic and phased view
    Wang, Yu
    Jalalian Daghigh, Ali
    [J]. FORUM-REVUE INTERNATIONALE D INTERPRETATION ET DE TRADUCTION-INTERNATIONAL JOURNAL OF INTERPRETATION AND TRANSLATION, 2023, 21 (01): : 139 - 162
  • [23] Patterns of Terminological Variation in Post-editing and of Cognate Use in Machine Translation in Contrast to Human Translation
    Culo, Oliver
    Nitzke, Jean
    [J]. BALTIC JOURNAL OF MODERN COMPUTING, 2016, 4 (02): : 106 - 114
  • [24] Post-editing for Professional Translators: Cheer or Fear?
    Vidal, Sergi Alvarez
    Oliver, Antoni
    Badia, Toni
    [J]. TRADUMATICA-TRADUCCIO I TECNOLOGIES DE LA INFORMACIO I LA COMUNICACIO, 2020, (18): : 49 - 69
  • [25] System for Post-Editing and Automatic Error Classification of Machine Translation
    Munkova, Dasa
    Kapusta, Jozef
    Drlik, Martin
    [J]. DIVAI 2016: 11TH INTERNATIONAL SCIENTIFIC CONFERENCE ON DISTANCE LEARNING IN APPLIED INFORMATICS, 2016, : 571 - 579
  • [26] Training in machine translation post-editing for foreign language students
    Zhang, Hong
    Torres-Hostench, Olga
    [J]. LANGUAGE LEARNING & TECHNOLOGY, 2022, 26 (01):
  • [27] Re-thinking Machine Translation Post-Editing Guidelines
    Perez, Celia Rico
    [J]. JOURNAL OF SPECIALISED TRANSLATION, 2024, (41): : 26 - 47
  • [28] The Trials and Tribulations of Predicting Machine Translation Post-Editing Productivity
    Marg, Lena
    [J]. LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 2016, : 23 - 26
  • [29] Social groups in machine translation post-editing A SCOT analysis
    Sakamoto, Akiko
    Yamada, Masaru
    [J]. TRANSLATION SPACES, 2020, 9 (01) : 78 - 97
  • [30] Multi-Modal Approaches for Post-Editing Machine Translation
    Herbig, Nico
    Pal, Santanu
    van Genabith, Josef
    Krueger, Antonio
    [J]. CHI 2019: PROCEEDINGS OF THE 2019 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 2019,