Proceedings of the 2019 3rd International Conference on Economic Development and Education Management (ICEDEM 2019)

Application of Human-Machine Interactive Translation Model and Its Implications

Authors
Zhaohui Wang
Corresponding Author
Zhaohui Wang
Available Online October 2019.
DOI
10.2991/icedem-19.2019.92How to use a DOI?
Keywords
human-machine interactive translation model; AI translation; application; implication
Abstract

Machine translation has developed from statistical machine translation to neural machine translation (also called AI translation). With the quality of AI translation being much superior to that of statistical machine translation, an epoch-making revolution has taken place in the field of translation technology. This paper discusses the application of AI translation in a human-machine interactive model, which has important enlightenment and practical significance for translation industry, translation teaching and research, as well as translation practice.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2019 3rd International Conference on Economic Development and Education Management (ICEDEM 2019)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
October 2019
ISBN
10.2991/icedem-19.2019.92
ISSN
2352-5398
DOI
10.2991/icedem-19.2019.92How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhaohui Wang
PY  - 2019/10
DA  - 2019/10
TI  - Application of Human-Machine Interactive Translation Model and Its Implications
BT  - Proceedings of the 2019 3rd International Conference on Economic Development and Education Management (ICEDEM 2019)
PB  - Atlantis Press
SP  - 391
EP  - 394
SN  - 2352-5398
UR  - https://doi.org/10.2991/icedem-19.2019.92
DO  - 10.2991/icedem-19.2019.92
ID  - Wang2019/10
ER  -