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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Main Author: Chen, Melvin
Other Authors: School of Humanities
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/170132
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Institution: Nanyang Technological University
Language: English
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spelling 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
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Humanities::Linguistics
Engineering::Computer science and engineering::Computing methodologies
Machine Translation
Automation
spellingShingle 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
description 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.
author2 School of Humanities
author_facet School of Humanities
Chen, Melvin
format Article
author Chen, Melvin
author_sort Chen, Melvin
title 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
title_full_unstemmed Trust, understanding, and machine translation: the task of translation and the responsibility of the translator
title_sort trust, understanding, and machine translation: the task of translation and the responsibility of the translator
publishDate 2023
url https://hdl.handle.net/10356/170132
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