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Data Analysis and Knowledge Discovery  2020, Vol. 4 Issue (12): 68-75    DOI: 10.11925/infotech.2096-3467.2020.0400
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Automatic Extraction of Traditional Music Terms of Intangible Cultural Heritage
Liu Liu(),Qin Tianyun,Wang Dongbo
College of Information Management, Nanjing Agricultural University, Nanjing 210095, China
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Abstract  

[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.
Key words： Intangible Cultural Heritage      Digital Humanities      BERT      Term Extraction      Entity Recognition     
Received: 08 May 2020      Published: 25 December 2020
ZTFLH:  TP391  
Corresponding Authors: Liu Liu     E-mail: liuliu@njau.edu.cn
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Liu Liu
Tianyun Qin
Dongbo Wang

Cite this article:

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.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2020.0400     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2020/V4/I12/68

实体类别 类别标记 示例 数量
非遗名称 ICH-TITLE 江河号子、老河口丝弦、
回族宴席曲		 1 518
独有术语 ICH-TERM 横抱琵琶、酒歌、六字真言歌 8 881
传承人姓名 ICH-INHERITOR 陈子敬、沈浩初、沈肇州 217
地名 ICH-PLACE 青海省玉树藏族自治州、卫藏地区、安多 2 772
作品名 ICH-WORKS 《对歌》、《口提哥哥》、
《英雄的村庄》		 1 396
工具器具名 ICH-INST 琵琶、笛子、唢呐、小管 2 122
The Summary of Traditional Music Terminology
测试编号 准确率（%） 召回率（%） F1值（%）
1 94.94 84.29 89.30
2 94.59 85.10 89.59
3 94.32 89.02 91.59
4 93.92 86.96 90.31
5 96.12 85.64 90.58
6 95.03 91.55 93.26
7 95.71 84.55 89.78
8 96.77 85.27 90.66
9 96.34 86.23 91.00
10 95.31 89.71 92.42
宏平均 95.31 86.83 90.85
Recognition Results of Traditional Music Entities Based on CRF
测试编号 准确率（%） 召回率（%） F1值（%）
1 84.12 84.12 84.12
2 83.38 85.80 84.57
3 87.80 88.67 88.24
4 84.32 84.54 84.43
5 88.22 81.87 84.92
6 83.52 85.63 84.56
7 89.02 84.75 86.83
8 85.68 84.58 85.12
9 84.66 86.68 85.62
10 86.90 89.46 88.16
宏平均 85.76 85.61 85.66
Recognition Results of Traditional Music Entities Based on LSTM
测试编号 准确率（%） 召回率（%） F1值（%）
1 86.14 86.35 86.25
2 84.96 88.41 86.65
3 87.77 90.15 88.94
4 88.42 86.60 87.50
5 90.96 85.87 88.34
6 85.68 90.99 88.25
7 89.76 84.18 86.88
8 91.29 83.55 87.25
9 91.79 83.99 87.71
10 87.53 91.18 89.32
宏平均 88.43 87.13 87.71
Recognition Results of Traditional Music Entities Based on LSTM-CRF
测试编号 准确率（%） 召回率（%） F1值（%）
1 87.96 93.07 90.44
2 89.30 92.15 90.70
3 91.73 95.44 93.55
4 89.35 92.47 90.89
5 91.60 93.82 92.70
6 89.22 94.03 91.56
7 94.48 93.12 93.80
8 91.27 92.99 92.12
9 89.25 90.13 89.69
10 92.73 91.81 92.27
宏平均 90.69 92.90 91.77
Recognition Results of Traditional Music Entities Based on BERT
模型 平均准确率（%） 平均召回率（%） 平均F1值（%）
CRF 95.31 86.83 90.85
LSTM 85.76 85.61 85.66
LSTM-CRF 88.43 87.13 87.71
BERT 90.69 92.90 91.77
The Average Results of Four Models
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