01438nas a2200229   4500000000100000000000100001000000100002008004100003653000900044653002300053653002300076653003300099653002000132100001100152700001100163700001200174245008400186300001000270490000600280520090200286022002001188       2020                            d10aBERT10aDigital humanities10aEntity Recognition10aIntangible cultural heritage10aTerm Extraction1 aL. Liu1 aT. Qin1 aD. Wang00aAutomatic extraction of traditional music terms of intangible cultural heritage  a68-750 v43 a[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.  a20963467 (ISSN)