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        <title>Machine Translation Implementation in Automatic Subtitling from a Subtitlers’ Perspective</title>
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            <title>Proceedings of Machine Translation Summit XIX, Vol. 2: Users Track</title>
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            <namePart type="given">Masaru</namePart>
            <namePart type="family">Yamada</namePart>
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            <namePart type="given">Felix</namePart>
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    <abstract>In recent years, automatic subtitling has gained considerable scholarly attention. Implementing machine translation in subtitling editors faces challenges, being a primary process in automatic subtitling. Therefore, there is still a significant research gap when it comes to machine translation implementation in automatic subtitling. This project compared different levels of non-verbal input videos from English to Chinese Simplified to examine post-editing efforts in automatic subtitling. The research collected the following data: process logs, which records the total time spent on the subtitles, keystrokes, and user experience questionnaire (UEQ). 12 subtitlers from a translation agency in Mainland China were invited to complete the task. The results show that there are no significant differences between videos with low and high levels of non-verbal input in terms of time spent. Furthermore, the subtitlers spent more effort on revising spotting and segmentation than translation when they post-edited texts with a high level of non-verbal input. While a majority of subtitlers show a positive attitude towards the application of machine translation, their apprehension lies in the potential overreliance on its usage.</abstract>
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%0 Conference Proceedings
%T Machine Translation Implementation in Automatic Subtitling from a Subtitlers’ Perspective
%A Xie, Bina
%Y Yamada, Masaru
%Y do Carmo, Felix
%S Proceedings of Machine Translation Summit XIX, Vol. 2: Users Track
%D 2023
%8 September
%I Asia-Pacific Association for Machine Translation
%C Macau SAR, China
%F xie-2023-machine
%X In recent years, automatic subtitling has gained considerable scholarly attention. Implementing machine translation in subtitling editors faces challenges, being a primary process in automatic subtitling. Therefore, there is still a significant research gap when it comes to machine translation implementation in automatic subtitling. This project compared different levels of non-verbal input videos from English to Chinese Simplified to examine post-editing efforts in automatic subtitling. The research collected the following data: process logs, which records the total time spent on the subtitles, keystrokes, and user experience questionnaire (UEQ). 12 subtitlers from a translation agency in Mainland China were invited to complete the task. The results show that there are no significant differences between videos with low and high levels of non-verbal input in terms of time spent. Furthermore, the subtitlers spent more effort on revising spotting and segmentation than translation when they post-edited texts with a high level of non-verbal input. While a majority of subtitlers show a positive attitude towards the application of machine translation, their apprehension lies in the potential overreliance on its usage.
%U https://aclanthology.org/2023.mtsummit-users.5
%P 54-64

Markdown (Informal)

[Machine Translation Implementation in Automatic Subtitling from a Subtitlers’ Perspective](https://aclanthology.org/2023.mtsummit-users.5) (Xie, MTSummit 2023)

• Machine Translation Implementation in Automatic Subtitling from a Subtitlers’ Perspective (Xie, MTSummit 2023)

ACL

• Bina Xie. 2023. Machine Translation Implementation in Automatic Subtitling from a Subtitlers’ Perspective. In Proceedings of Machine Translation Summit XIX, Vol. 2: Users Track, pages 54–64, Macau SAR, China. Asia-Pacific Association for Machine Translation.