Trust, understanding, and machine translation: the task of translation and the responsibility of the translator
Could translation be fully automated? We must first acknowledge the complexity, ambiguity, and diversity of natural languages. These aspects of natural languages, when combined with a particular dilemma known as the computational dilemma, appear to imply that the machine translator faces certain obs...
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sg-ntu-dr.10356-1701322023-09-02T16:54:48Z Trust, understanding, and machine translation: the task of translation and the responsibility of the translator Chen, Melvin School of Humanities Campus for Research Excellence and Technological Enterprise (CREATE) Humanities::Linguistics Engineering::Computer science and engineering::Computing methodologies Machine Translation Automation Could translation be fully automated? We must first acknowledge the complexity, ambiguity, and diversity of natural languages. These aspects of natural languages, when combined with a particular dilemma known as the computational dilemma, appear to imply that the machine translator faces certain obstacles that a human translator has already managed to overcome. At the same time, science has not yet solved the problem of how human brains process natural languages and how human beings come to acquire natural language understanding. We will then distinguish between the task of translation and the responsibility of the translator. Thereafter, we will conduct a survey of the methods of machine translation (viz. RBMT, SMT, NMT, foundation models or large language models). These methods will then be critically evaluated both in general and relative to Bar-Hillel’s hypothesis about the impossibility of fully automatic, high-quality machine translation (Fahqmt). Some concluding remarks will be made about the scope, prospects, and limits of machine translation. National Research Foundation (NRF) Published version This research is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. 2023-08-29T04:59:57Z 2023-08-29T04:59:57Z 2023 Journal Article Chen, M. (2023). Trust, understanding, and machine translation: the task of translation and the responsibility of the translator. AI and Society. https://dx.doi.org/10.1007/s00146-023-01681-6 0951-5666 https://hdl.handle.net/10356/170132 10.1007/s00146-023-01681-6 2-s2.0-85159262625 en AI and Society © The Author(s) 2023, corrected publication 2023. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. application/pdf |
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Humanities::Linguistics Engineering::Computer science and engineering::Computing methodologies Machine Translation Automation Chen, Melvin Trust, understanding, and machine translation: the task of translation and the responsibility of the translator |
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Could translation be fully automated? We must first acknowledge the complexity, ambiguity, and diversity of natural languages. These aspects of natural languages, when combined with a particular dilemma known as the computational dilemma, appear to imply that the machine translator faces certain obstacles that a human translator has already managed to overcome. At the same time, science has not yet solved the problem of how human brains process natural languages and how human beings come to acquire natural language understanding. We will then distinguish between the task of translation and the responsibility of the translator. Thereafter, we will conduct a survey of the methods of machine translation (viz. RBMT, SMT, NMT, foundation models or large language models). These methods will then be critically evaluated both in general and relative to Bar-Hillel’s hypothesis about the impossibility of fully automatic, high-quality machine translation (Fahqmt). Some concluding remarks will be made about the scope, prospects, and limits of machine translation. |
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School of Humanities |
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School of Humanities Chen, Melvin |
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Chen, Melvin |
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Chen, Melvin |
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Trust, understanding, and machine translation: the task of translation and the responsibility of the translator |
title_short |
Trust, understanding, and machine translation: the task of translation and the responsibility of the translator |
title_full |
Trust, understanding, and machine translation: the task of translation and the responsibility of the translator |
title_fullStr |
Trust, understanding, and machine translation: the task of translation and the responsibility of the translator |
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Trust, understanding, and machine translation: the task of translation and the responsibility of the translator |
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trust, understanding, and machine translation: the task of translation and the responsibility of the translator |
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2023 |
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https://hdl.handle.net/10356/170132 |
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