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Error types of machine translation of popular science text

Published: 17 October 2019 Publication History

Abstract

This paper summarizes and categorizes the common error types of machine translation of popular science text, which includes mistranslation of technical terms, omission, over-translation, mistranslation of clauses, mistranslation of attributive sequences, and mistranslation caused by rigidly converting English special sentence structures. The categorization of these common errors in machine translation might be helpful as a reference for machine translation program improvement.

References

[1]
Vasconcellos, M. A comparison of MT post-editing and translational revision. In Proceedings of the 28th Annual Conference of the American Translators Association, 1987: 409--416.
[2]
Martins, D. B. J. and Caseli, H. M. Automatic machine translation error identification. Machine Translation, 2015(29): 1--24.
[3]
Wang Huashu, and Wang Shaoshuang. Research on the composition and training of translation technical ability in the information age. Journal of East Translation, 2013(1):11--15.
[4]
Cui Qiliang. On post-translation editing of machine translation. Chinese Translation Journal, 2014(6): 68--73.
[5]
Xu Bin, Guo Hongmei. Non-technical text translation practice based on computer translation technology. Chinese Translators Journal, 2015(1): 71--76.
[6]
Li Mei, Zhu Ximing. Error classification and statistical analysis of English-Chinese machine translation [J]. Journal of Shanghai University of Science and Technology (Social Science Edition), 2013(3): 83--87.
[7]
Luo Jimei, Li Mei. Machine translation error analysis. Chinese Translators Journal, 2012(5): 84--89.
[8]
Cui Qiliang, Li Wen. Research on types of editing errors after translation -- based on scientific and technological texts. China Science and Technology Translation, 2015(4): 19--22.

Cited By

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  • (2024)Adopting machine translation in the healthcare sectorComputer Speech and Language10.1016/j.csl.2023.10158284:COnline publication date: 4-Mar-2024
  • (2023)Incorporating Collaborative and Active Learning Strategies in the Design and Deployment of a Master Course on Computer-Assisted Scientific TranslationTechnology, Knowledge and Learning10.1007/s10758-023-09679-129:1(253-308)Online publication date: 7-Aug-2023

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  1. Error types of machine translation of popular science text

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    Published In

    cover image ACM Other conferences
    AIAM 2019: Proceedings of the 2019 International Conference on Artificial Intelligence and Advanced Manufacturing
    October 2019
    418 pages
    ISBN:9781450372022
    DOI:10.1145/3358331
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 17 October 2019

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    Author Tags

    1. Machine translation
    2. post-editing
    3. translation quality

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    • Research-article
    • Research
    • Refereed limited

    Funding Sources

    • humanities and social science research fund from China?s ministry of education
    • Xi?an International Studies University

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    AIAM 2019

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    Overall Acceptance Rate 100 of 285 submissions, 35%

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    Cited By

    View all
    • (2024)Adopting machine translation in the healthcare sectorComputer Speech and Language10.1016/j.csl.2023.10158284:COnline publication date: 4-Mar-2024
    • (2023)Incorporating Collaborative and Active Learning Strategies in the Design and Deployment of a Master Course on Computer-Assisted Scientific TranslationTechnology, Knowledge and Learning10.1007/s10758-023-09679-129:1(253-308)Online publication date: 7-Aug-2023

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