Human vs. AI: An Assessment of the Translation Quality Between Translators and Machine Translation

Hanji Li, Haiqing Chen

Source Title: International Journal of Translation, Interpretation, and Applied Linguistics (IJTIAL)1(1)

ISSN: 2575-6974|EISSN: 2575-6982|EISBN13: 9781522568926|DOI: 10.4018/IJTIAL.2019010104

MLA

Li, Hanji, and Haiqing Chen. "Human vs. AI: An Assessment of the Translation Quality Between Translators and Machine Translation." IJTIAL vol.1, no.1 2019: pp.1-12. http://doi.org/10.4018/IJTIAL.2019010104

APA

Li, H. & Chen, H. (2019). Human vs. AI: An Assessment of the Translation Quality Between Translators and Machine Translation. International Journal of Translation, Interpretation, and Applied Linguistics (IJTIAL), 1(1), 1-12. http://doi.org/10.4018/IJTIAL.2019010104

Chicago

Li, Hanji, and Haiqing Chen. "Human vs. AI: An Assessment of the Translation Quality Between Translators and Machine Translation," International Journal of Translation, Interpretation, and Applied Linguistics (IJTIAL) 1, no.1: 1-12. http://doi.org/10.4018/IJTIAL.2019010104

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Abstract

As one of the most important applications of AI, machine translation has always been the hot topic among scholars in linguistics, computer science, cognitive science and other areas. This article made an assessment of translations of 4 selected major online machine translation platforms from perspectives of efficiency, operating mode and condition. The outputs of machine and human were compared by employing new “6-4” table and comprehensive error rate. The assessment shows that although the quality of machine translation is improving, the gap still exists between the quality of machine translation and human translation. Based on the research findings, the author predicts that machine translation cannot possibly replace human translation and the two will continue to coexist in the foreseeable future.