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        <title>Technical Report on Ancient Chinese Machine Translation Based on mRASP Model</title>
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            <title>Proceedings of ALT2023: Ancient Language Translation Workshop</title>
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            <publisher>Asia-Pacific Association for Machine Translation</publisher>
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    <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.</abstract>
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%0 Conference Proceedings
%T Technical Report on Ancient Chinese Machine Translation Based on mRASP Model
%A Liu, Wenjing
%A Xie, Jing
%S Proceedings of ALT2023: Ancient Language Translation Workshop
%D 2023
%8 September
%I Asia-Pacific Association for Machine Translation
%C Macau SAR, China
%F liu-xie-2023-technical
%X 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.
%U https://aclanthology.org/2023.alt-1.7
%P 48-54

Markdown (Informal)

[Technical Report on Ancient Chinese Machine Translation Based on mRASP Model](https://aclanthology.org/2023.alt-1.7) (Liu & Xie, alt 2023)

• Technical Report on Ancient Chinese Machine Translation Based on mRASP Model (Liu & Xie, alt 2023)

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.