MT for Subtitling: Investigating professional translators’ user experience and feedback

Maarit Koponen; Umut Sulubacak; Kaisa Vitikainen; Jörg Tiedemann

MT for Subtitling: Investigating professional translators’ user experience and feedback

Maarit Koponen, Umut Sulubacak, Kaisa Vitikainen, Jörg Tiedemann

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Professional

Abstract

This paper presents a study of machine translation and post-editing in the field of audiovisual translation. We analyse user experience data collected from post-editing tasks completed by twelve translators in four language pairs. We also present feedback provided by the translators in semi-structured interviews. The results of the user experience survey and thematic analysis of interviews shows that the translators’ impression of post-editing subtitles was on average neutral to somewhat negative, with segmentation and timing of subtitles identified as a key factor. Finally, we discuss the implications of the issues arising from the user experience survey and interviews for the future development of automatic subtitle translation.

Original language	English
Title of host publication	Proceedings of the 14th Conference of the Association for Machine Translation in the Americas October 6 - 9, 2020 : 1st Workshop on Post-Editing in Modern-Day Translation
Editors	John E. Ortega, Marcello Federico, Constantin Orasan, Maja Popovic
Number of pages	14
Place of Publication	East Stroudsburg
Publisher	AMTA
Publication date	Nov 2020
Pages	79-92
Publication status	Published - Nov 2020
MoE publication type	D3 Professional conference proceedings
Event	Workshop on Post-Editing in Modern-Day Translation - [Virtual event] Duration: 6 Oct 2020 → 9 Oct 2020 Conference number: 1

Fields of Science

6121 Languages

Access to Document

koponen-etal_2020.amta-pemdt.6Final published version, 528 KBLicence: CC BY-ND

https://www.aclweb.org/anthology/2020.amta-pemdt.6/Licence: CC BY-ND

MeMAD: Methods for Managing Audiovisual Data: Combining Automatic Efficiency with Human Accuracy
Hirvonen, M., Tiedemann, J., Tiittula, L., Sulubacak, U., Vazquez , R. & Koponen, M.
European Commission / Horizon 2020
01/01/2018 → 31/03/2021
Project: Research project

Cite this

Koponen, M., Sulubacak, U., Vitikainen, K., & Tiedemann, J. (2020). MT for Subtitling: Investigating professional translators’ user experience and feedback. In J. E. Ortega, M. Federico, C. Orasan, & M. Popovic (Eds.), Proceedings of the 14th Conference of the Association for Machine Translation in the Americas October 6 - 9, 2020: 1st Workshop on Post-Editing in Modern-Day Translation (pp. 79-92). AMTA. https://www.aclweb.org/anthology/2020.amta-pemdt.6/

Koponen, Maarit ; Sulubacak, Umut ; Vitikainen, Kaisa et al. / MT for Subtitling : Investigating professional translators’ user experience and feedback. Proceedings of the 14th Conference of the Association for Machine Translation in the Americas October 6 - 9, 2020: 1st Workshop on Post-Editing in Modern-Day Translation. editor / John E. Ortega ; Marcello Federico ; Constantin Orasan ; Maja Popovic. East Stroudsburg : AMTA, 2020. pp. 79-92

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title = "MT for Subtitling: Investigating professional translators{\textquoteright} user experience and feedback",

abstract = "This paper presents a study of machine translation and post-editing in the field of audiovisual translation. We analyse user experience data collected from post-editing tasks completed by twelve translators in four language pairs. We also present feedback provided by the translators in semi-structured interviews. The results of the user experience survey and thematic analysis of interviews shows that the translators{\textquoteright} impression of post-editing subtitles was on average neutral to somewhat negative, with segmentation and timing of subtitles identified as a key factor. Finally, we discuss the implications of the issues arising from the user experience survey and interviews for the future development of automatic subtitle translation.",

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author = "Maarit Koponen and Umut Sulubacak and Kaisa Vitikainen and J{\"o}rg Tiedemann",

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editor = "Ortega, {John E.} and Marcello Federico and Constantin Orasan and Maja Popovic",

booktitle = "Proceedings of the 14th Conference of the Association for Machine Translation in the Americas October 6 - 9, 2020",

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Koponen, M, Sulubacak, U, Vitikainen, K & Tiedemann, J 2020, MT for Subtitling: Investigating professional translators’ user experience and feedback. in JE Ortega, M Federico, C Orasan & M Popovic (eds), Proceedings of the 14th Conference of the Association for Machine Translation in the Americas October 6 - 9, 2020: 1st Workshop on Post-Editing in Modern-Day Translation. AMTA, East Stroudsburg, pp. 79-92, Workshop on Post-Editing in Modern-Day Translation, 06/10/2020. <https://www.aclweb.org/anthology/2020.amta-pemdt.6/>

MT for Subtitling: Investigating professional translators’ user experience and feedback. / Koponen, Maarit; Sulubacak, Umut; Vitikainen, Kaisa et al.
Proceedings of the 14th Conference of the Association for Machine Translation in the Americas October 6 - 9, 2020: 1st Workshop on Post-Editing in Modern-Day Translation. ed. / John E. Ortega; Marcello Federico; Constantin Orasan; Maja Popovic. East Stroudsburg: AMTA, 2020. p. 79-92.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Professional

TY - GEN

T1 - MT for Subtitling

T2 - Workshop on Post-Editing in Modern-Day Translation

AU - Koponen, Maarit

AU - Sulubacak, Umut

AU - Vitikainen, Kaisa

AU - Tiedemann, Jörg

N1 - Conference code: 1

PY - 2020/11

Y1 - 2020/11

N2 - This paper presents a study of machine translation and post-editing in the field of audiovisual translation. We analyse user experience data collected from post-editing tasks completed by twelve translators in four language pairs. We also present feedback provided by the translators in semi-structured interviews. The results of the user experience survey and thematic analysis of interviews shows that the translators’ impression of post-editing subtitles was on average neutral to somewhat negative, with segmentation and timing of subtitles identified as a key factor. Finally, we discuss the implications of the issues arising from the user experience survey and interviews for the future development of automatic subtitle translation.

AB - This paper presents a study of machine translation and post-editing in the field of audiovisual translation. We analyse user experience data collected from post-editing tasks completed by twelve translators in four language pairs. We also present feedback provided by the translators in semi-structured interviews. The results of the user experience survey and thematic analysis of interviews shows that the translators’ impression of post-editing subtitles was on average neutral to somewhat negative, with segmentation and timing of subtitles identified as a key factor. Finally, we discuss the implications of the issues arising from the user experience survey and interviews for the future development of automatic subtitle translation.

KW - 6121 Languages

M3 - Conference contribution

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EP - 92

BT - Proceedings of the 14th Conference of the Association for Machine Translation in the Americas October 6 - 9, 2020

A2 - Ortega, John E.

A2 - Federico, Marcello

A2 - Orasan, Constantin

A2 - Popovic, Maja

PB - AMTA

CY - East Stroudsburg

Y2 - 6 October 2020 through 9 October 2020

ER -

Koponen M, Sulubacak U, Vitikainen K , Tiedemann J. MT for Subtitling: Investigating professional translators’ user experience and feedback. In Ortega JE, Federico M, Orasan C, Popovic M, editors, Proceedings of the 14th Conference of the Association for Machine Translation in the Americas October 6 - 9, 2020: 1st Workshop on Post-Editing in Modern-Day Translation. East Stroudsburg: AMTA. 2020. p. 79-92

MT for Subtitling: Investigating professional translators’ user experience and feedback

Abstract

Fields of Science

Access to Document

Projects

MeMAD: Methods for Managing Audiovisual Data: Combining Automatic Efficiency with Human Accuracy

Cite this