Application of Music Data Visualization Technology in Music Appreciation Teaching
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Wiley Open Access
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| Natura: | Artículo Open Access |
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Wiley
2026
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| _version_ | 1867021260940115968 |
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| author | Xiaowei Chen |
| author_facet | Xiaowei Chen Xiaowei Chen |
| collection | Wiley Open Access |
| contents | Application of Music Data Visualization Technology in Music Appreciation Teaching Xiaowei Chen Engineering Reports ABSTRACT Traditional music appreciation teaching has limitations such as excessive reliance on oral explanations, passive acceptance by students, and difficulty in visually presenting the internal structure and emotional logic of music. The purpose of this article is to explore the integration application path of music data visualization technology and Deep Learning (DL) in teaching scenarios. By constructing an experimental system that simulates a real appreciation environment, this study utilizes deep learning algorithms to efficiently preprocess audio data, extract multidimensional features, and recognize rhythm information, achieving intuitive and visual expression of music data. The experiment selected three typical music samples: popular, classical, and folk for verification. The results indicate that this method has high accuracy in audio feature recognition and can generate visual representations that accurately reflect different musical styles, rhythm structures, and emotional features. The research conclusion shows that data visualization technology based on deep learning can significantly enhance the interactivity and participation of music appreciation teaching, assist learners in deeply understanding the inherent laws of music, and effectively stimulate aesthetic creativity imagination. 10.1002/eng2.70849 http://creativecommons.org/licenses/by/4.0/ |
| doi_str_mv | 10.1002/eng2.70849 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_eng2_70849 |
| institution | Wiley Open Access |
| license_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| publishDate | 2026 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | Application of Music Data Visualization Technology in Music Appreciation Teaching Xiaowei Chen Engineering Reports Application of Music Data Visualization Technology in Music Appreciation Teaching Xiaowei Chen Engineering Reports ABSTRACT Traditional music appreciation teaching has limitations such as excessive reliance on oral explanations, passive acceptance by students, and difficulty in visually presenting the internal structure and emotional logic of music. The purpose of this article is to explore the integration application path of music data visualization technology and Deep Learning (DL) in teaching scenarios. By constructing an experimental system that simulates a real appreciation environment, this study utilizes deep learning algorithms to efficiently preprocess audio data, extract multidimensional features, and recognize rhythm information, achieving intuitive and visual expression of music data. The experiment selected three typical music samples: popular, classical, and folk for verification. The results indicate that this method has high accuracy in audio feature recognition and can generate visual representations that accurately reflect different musical styles, rhythm structures, and emotional features. The research conclusion shows that data visualization technology based on deep learning can significantly enhance the interactivity and participation of music appreciation teaching, assist learners in deeply understanding the inherent laws of music, and effectively stimulate aesthetic creativity imagination. 10.1002/eng2.70849 http://creativecommons.org/licenses/by/4.0/ |
| title | Application of Music Data Visualization Technology in Music Appreciation Teaching |
| topic | Engineering Reports |
| url | https://onlinelibrary.wiley.com/doi/10.1002/eng2.70849 |