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        <title>Challenges of Human vs Machine Translation of Emotion-Loaded Chinese Microblog Texts</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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    <abstract>This paper attempts to identify challenges professional translators face when translating emotion-loaded texts as well as errors machine translation (MT) makes when translating this content. We invited ten Chinese-English translators to translate thirty posts of a Chinese microblog, and interviewed them about the challenges encountered during translation and the problems they believe MT might have. Further, we analysed more than five-thousand automatic translations of microblog posts to observe problems in MT outputs. We establish that the most challenging problem for human translators is emotion-carrying words, which translators also consider as a problem for MT. Analysis of MT outputs shows that this is also the most common source of MT errors. We also find that what is challenging for MT, such as non-standard writing, is not necessarily an issue for humans. Our work contributes to a better understanding of the challenges for the translation of microblog posts by humans and MT, caused by different forms of expression of emotion.</abstract>
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%0 Conference Proceedings
%T Challenges of Human vs Machine Translation of Emotion-Loaded Chinese Microblog Texts
%A Qian, Shenbin
%A Orăsan, Constantin
%A do Carmo, Félix
%A Kanojia, Diptesh
%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 qian-etal-2023-challenges
%X This paper attempts to identify challenges professional translators face when translating emotion-loaded texts as well as errors machine translation (MT) makes when translating this content. We invited ten Chinese-English translators to translate thirty posts of a Chinese microblog, and interviewed them about the challenges encountered during translation and the problems they believe MT might have. Further, we analysed more than five-thousand automatic translations of microblog posts to observe problems in MT outputs. We establish that the most challenging problem for human translators is emotion-carrying words, which translators also consider as a problem for MT. Analysis of MT outputs shows that this is also the most common source of MT errors. We also find that what is challenging for MT, such as non-standard writing, is not necessarily an issue for humans. Our work contributes to a better understanding of the challenges for the translation of microblog posts by humans and MT, caused by different forms of expression of emotion.
%U https://aclanthology.org/2023.mtsummit-users.21
%P 217-236

Markdown (Informal)

[Challenges of Human vs Machine Translation of Emotion-Loaded Chinese Microblog Texts](https://aclanthology.org/2023.mtsummit-users.21) (Qian et al., MTSummit 2023)

• Challenges of Human vs Machine Translation of Emotion-Loaded Chinese Microblog Texts (Qian et al., MTSummit 2023)

ACL

• Shenbin Qian, Constantin Orăsan, Félix do Carmo, and Diptesh Kanojia. 2023. Challenges of Human vs Machine Translation of Emotion-Loaded Chinese Microblog Texts. In Proceedings of Machine Translation Summit XIX, Vol. 2: Users Track, pages 217–236, Macau SAR, China. Asia-Pacific Association for Machine Translation.