Technical Report on Ancient Chinese Machine Translation Based on mRASP Model

Wenjing Liu, Jing Xie


Abstract
Abstract: Objective This paper aims to improve the performance of machine translation of ancient Chinese classics, which can better promote the development of ancient books research and the spread of Chinese culture. Methods Based on the multilingual translation machine pre-training model of mRASP, the model was trained by fine-tuning the specific language pairs, namely a2m, and a2e, according to the two downstream tasks of classical Chinese translation into modern Chinese and classical Chinese translation into English, using the parallel corpus of ancient white and white and ancient English parallel corpus of Pre-Qin+ZiZhiTongJian, and the translation performance of the fine-tuning model was evaluated by BIEU evaluation index. Results The BIEU4 results of the three downstream tasks of 24_histories_a2m、Pre-Qin+ZiZhiTongJian_a2m、 Pre-Qin+ZiZhiTongJian_a2e were 17.38, 13.69 and 12.90 respectively.
Anthology ID:
2023.alt-1.7
Volume:
Proceedings of ALT2023: Ancient Language Translation Workshop
Month:
September
Year:
2023
Address:
Macau SAR, China
Venue:
alt
SIG:
Publisher:
Asia-Pacific Association for Machine Translation
Note:
Pages:
48–54
Language:
URL:
https://aclanthology.org/2023.alt-1.7
DOI:
Bibkey:
Cite (ACL):
Wenjing Liu and Jing Xie. 2023. Technical Report on Ancient Chinese Machine Translation Based on mRASP Model. In Proceedings of ALT2023: Ancient Language Translation Workshop, pages 48–54, Macau SAR, China. Asia-Pacific Association for Machine Translation.
Cite (Informal):
Technical Report on Ancient Chinese Machine Translation Based on mRASP Model (Liu & Xie, alt 2023)
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PDF:
https://aclanthology.org/2023.alt-1.7.pdf