Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/170132
Title: Trust, understanding, and machine translation: the task of translation and the responsibility of the translator
Authors: Chen, Melvin
Keywords: Humanities::Linguistics
Engineering::Computer science and engineering::Computing methodologies
Issue Date: 2023
Source: 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
Journal: AI and Society 
Abstract: 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.
URI: https://hdl.handle.net/10356/170132
ISSN: 0951-5666
DOI: 10.1007/s00146-023-01681-6
Schools: School of Humanities 
Organisations: Campus for Research Excellence and Technological Enterprise (CREATE) 
Rights: © 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/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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