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One of the important topics in the research field of Chinese classical poetryis to analyze the poetic style. By examining the relevant works of previousdynasties, researchers judge a poetic style mostly by their subjectivefeelings, and refer to the previous evaluations that have become a certainconclusion. Although this judgment method is often effective, there may be someerrors. This paper builds the most perfect data set of Chinese classical poetryat present, trains a BART-poem pre -trained model on this data set, and putsforward a generally applicable poetry style judgment method based on thisBART-poem model, innovatively introduces in-depth learning into the field ofcomputational stylistics, and provides a new research method for the study ofclassical poetry. This paper attempts to use this method to solve the problemof poetry style identification in the Tang and Song Dynasties, and takes thepoetry schools that are considered to have a relatively clear and consistentpoetic style, such as the Hongzheng Qizi and Jiajing Qizi, Jiangxi poeticschool and Tongguang poetic school, as the research object, and takes the poemsof their representative poets for testing. Experiments show that the judgmentresults of the tested poetry work made by the model are basically consistentwith the conclusions given by critics of previous dynasties, verify someavant-garde judgments of Mr. Qian Zhongshu, and better solve the task of poetrystyle recognition in the Tang and Song dynasties.

A Method to Judge the Style of Classical Poetry Based on Pre-trained Model