[Objective] Focus on the task of entity recognition of traditional music terms of intangible cultural heritage. [Methods] This research constructed a corpus of national intangible cultural heritage projects based on the China Intangible Cultural Heritage Network, and built an entity recognition framework on traditional music terms based on the CRF, LSTM, LSTM-CRF, and BERT. [Results] According to the performance comparison, the BERT model for recognition of traditional music terms had achieved a better result, with an average F1 value of 91.77%. [Limitations] This study only extract unique terms, and the training set is small. [Conclusions] The entity recognition model constructed by BERT is a valid model for automatically extracting traditional musical terms of intangible cultural heritage. It can provide a reliable reference for the related research of intangible cultural heritage.
刘浏,秦天允,王东波. 非物质文化遗产传统音乐术语自动抽取*[J]. 数据分析与知识发现, 2020, 4(12): 68-75.
Liu Liu,Qin Tianyun,Wang Dongbo. Automatic Extraction of Traditional Music Terms of Intangible Cultural Heritage. Data Analysis and Knowledge Discovery, 2020, 4(12): 68-75.
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