Towards Effective Ancient Chinese Translation: Dataset, Model, and Evaluation

• URL: http://arxiv.org/abs/2308.00240v1
• Date: Tue, 1 Aug 2023 02:43:27 GMT
• Title: Towards Effective Ancient Chinese Translation: Dataset, Model, and Evaluation
• Authors: Geyang Guo, Jiarong Yang, Fengyuan Lu, Jiaxin Qin, Tianyi Tang, Wayne Xin Zhao
• Abstract summary: In this paper, we propose Erya for ancient Chinese translation. From a dataset perspective, we collect, clean, and classify ancient Chinese materials from various sources. From a model perspective, we devise Erya training method oriented towards ancient Chinese.
• Score: 28.930640246972516
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Interpreting ancient Chinese has been the key to comprehending vast Chinese literature, tradition, and civilization. In this paper, we propose Erya for ancient Chinese translation. From a dataset perspective, we collect, clean, and classify ancient Chinese materials from various sources, forming the most extensive ancient Chinese resource to date. From a model perspective, we devise Erya training method oriented towards ancient Chinese. We design two jointly-working tasks: disyllabic aligned substitution (DAS) and dual masked language model (DMLM). From an evaluation perspective, we build a benchmark to judge ancient Chinese translation quality in different scenarios and evaluate the ancient Chinese translation capacities of various existing models. Our model exhibits remarkable zero-shot performance across five domains, with over +12.0 BLEU against GPT-3.5 models and better human evaluation results than ERNIE Bot. Subsequent fine-tuning further shows the superior transfer capability of Erya model with +6.2 BLEU gain. We release all the above-mentioned resources at https://github.com/RUCAIBox/Erya.

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