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A Review of Machine Translation: Implications to Human Translators and Translation Teaching

Xiaoping Shen

Guilin Tourism University, Guilin, China, 541006.

*Corresponding author: Xiaoping Shen

Published: January 5,2023


Machine translation has witnessed great development in the recent decades and we have entered the era of neural machine translation (NMT). A review of MT is necessary for a better understanding of the relationship between MT and human translators and translation teaching in this era when MT has flourished. This paper first briefs the machine translation (MT) development in the past decades, focusing on the features, application, and drawbacks of each main paradigm of rule-based machine translation (RBMT), corpus-based translation (CBMT), and long-short term memory (LSTM), a main paradigm of NMT. It continues with a discussion of what MT means to human translators and translation teaching in universities. It concludes that MT should not and could not replace human translators which will always be vital in some fields and aspects; only a good integration between the two can ensure satisfying output with post-editing by human translators to meet the increasingly demanding market. This signifies that translation teaching in universities should embrace MT knowledge.


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How to cite this paper

A Review of Machine Translation: Implications to Human Translators and Translation Teaching

How to cite this paper: Xiaoping Shen. (2022). A Review of Machine Translation: Implications to Human Translators and Translation Teaching. The Educational Review, USA6(12), 869-874.