Contrasting and Analyzing Machine and Human Translation: A Case Study on Red Sorghum

DOI

10.2991/assehr.k.211220.437How to use a DOI?

Keywords

Machine translation; Error analysis; Chinese-English translation; Literary text

Abstract

The quality of machine translation is an important part in machine language competence. Currently, there are still many differences between machine translation and human translation. The quality of machine translation still could not reach the quality of human translation. We take a Chinese literary text, Mo Yan’s Red Sorghum, as the material to translate, and used LIWC2015 to analyze the differences between machine and human translation. Also, we make a linguistical attribution analysis to find out the reasons behind the errors machines make. For the engines of machine translation, we choose Baidu, Youdao and Google as machine translate engines. By analyzing the results from LIWC2015 and error analysis, we find that compared to human translators, machine translate engines tend to use simpler words and often fail to recognize discoursal connection; the errors machine translate engines make are usually caused by long sentences, Chinese names, encyclopedic knowledge, unique expressions and constructions in Chinese and literary expression.

Copyright

© 2021 The Authors. Published by Atlantis Press SARL.

Open Access

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

Download article (PDF)

TY  - CONF
AU  - Manxin Lan
AU  - Linshan Zhao
PY  - 2021
DA  - 2021/12/24
TI  - Contrasting and Analyzing Machine and Human Translation: A Case Study on Red Sorghum
BT  - Proceedings of the 2021 4th International Conference on Humanities Education and Social Sciences (ICHESS 2021)
PB  - Atlantis Press
SP  - 2522
EP  - 2528
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.211220.437
DO  - 10.2991/assehr.k.211220.437
ID  - Lan2021
ER  -