Neural Machine Translation Applied in English Chinese: Turn Grammar Connotation into Words

DOI

10.2991/aebmr.k.220405.276How to use a DOI?

Keywords

Neural Machine Translation; English Chinese; participles; grammar connotation; lexical words

Abstract

Recent advances in Neural Machine Translation (NMT) have largely improved the quality of translations in a variety of language pairs, which helps promote the efficiency in communication and information exchange. English to Chinese translation, however, still suffers from lower accuracy and intelligibility partly due to their inequivalent language structures. This work compares the performance of three frequently used commercial NMT systems and aims to propose a new method of turning English grammar connotations, participles in particular, into Chinese lexical words. Hopefully, with more data analyzed, the performance of NMT in the language pair of English Chinese can be improved to meet the needs in different contexts.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license.

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TY  - CONF
AU  - Tongyao Diao
PY  - 2022
DA  - 2022/04/29
TI  - Neural Machine Translation Applied in English Chinese: Turn Grammar Connotation into Words
BT  - Proceedings of the 2022 7th International Conference on Social Sciences and Economic Development (ICSSED 2022)
PB  - Atlantis Press
SP  - 1665
EP  - 1668
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.220405.276
DO  - 10.2991/aebmr.k.220405.276
ID  - Diao2022
ER  -