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arXiv · 2009.11473

AnchiBERT: A Pre-Trained Model for Ancient ChineseLanguage Understanding and Generation

Huishuang Tian·Kexin Yang·Dayiheng Liu·Jiancheng Lv
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Abstract

Ancient Chinese is the essence of Chinese culture. There are several natural language processing tasks of ancient Chinese domain, such as ancient-modern Chinese translation, poem generation, and couplet generation. Previous studies usually use the supervised models which deeply rely on parallel data. However, it is difficult to obtain large-scale parallel data of ancient Chinese. In order to make full use of the more easily available monolingual ancient Chinese corpora, we release AnchiBERT, a pre-trained language model based on the architecture of BERT, which is trained on large-scale ancient Chinese corpora. We evaluate AnchiBERT on both language understanding and generation tasks, including poem classification, ancient-modern Chinese translation, poem generation, and couplet generation. The experimental results show that AnchiBERT outperforms BERT as well as the non-pretrained models and achieves state-of-the-art results in all cases.

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Huishuang Tian, Kexin Yang, Dayiheng Liu, Jiancheng Lv. 2020-09-24. AnchiBERT: A Pre-Trained Model for Ancient ChineseLanguage Understanding and Generation. https://arxiv.org/abs/2009.11473

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