Design and Application of the Piano Teaching System Integrating Videos and Images
The art of piano playing has been continuously entering into people’s life. However, with the continuous improvement of science and technology and living standards, the traditional teaching mode can no longer meet the piano teaching mode. The teaching of piano is different from traditional subjects,...
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Published in | Scientific programming Vol. 2022; pp. 1 - 9 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
New York
Hindawi
27.06.2022
John Wiley & Sons, Inc |
Subjects | |
Online Access | Get full text |
ISSN | 1058-9244 1875-919X |
DOI | 10.1155/2022/8651415 |
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Abstract | The art of piano playing has been continuously entering into people’s life. However, with the continuous improvement of science and technology and living standards, the traditional teaching mode can no longer meet the piano teaching mode. The teaching of piano is different from traditional subjects, such as Chinese and mathematics. It requires students to experience the artistic characteristics and the live atmosphere of the players brought by the piano. This study integrates video and image teaching methods with piano teaching. Videos and images can more intuitively show the live atmosphere brought by piano players and musical artistic features brought by the piano. At the same time, this study uses the convolutional neural network (CNN) method to study the relevant features of videos and images of piano teaching. These features are mainly the characteristics of piano music, the behavior of players, and the basic knowledge of a piano. The research results show that the clustering method can effectively classify the features of videos and images in piano teaching, and the maximum classification error is only 1.89%. The CNN method also has high performance in predicting the relevant features of piano teaching videos and images. Accuracy. The largest prediction error is only 2.23%, and the linear correlation coefficient also exceeds 0.95. This set of the piano teaching mode that combines videos and images is beneficial to both teachers and students. |
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AbstractList | The art of piano playing has been continuously entering into people’s life. However, with the continuous improvement of science and technology and living standards, the traditional teaching mode can no longer meet the piano teaching mode. The teaching of piano is different from traditional subjects, such as Chinese and mathematics. It requires students to experience the artistic characteristics and the live atmosphere of the players brought by the piano. This study integrates video and image teaching methods with piano teaching. Videos and images can more intuitively show the live atmosphere brought by piano players and musical artistic features brought by the piano. At the same time, this study uses the convolutional neural network (CNN) method to study the relevant features of videos and images of piano teaching. These features are mainly the characteristics of piano music, the behavior of players, and the basic knowledge of a piano. The research results show that the clustering method can effectively classify the features of videos and images in piano teaching, and the maximum classification error is only 1.89%. The CNN method also has high performance in predicting the relevant features of piano teaching videos and images. Accuracy. The largest prediction error is only 2.23%, and the linear correlation coefficient also exceeds 0.95. This set of the piano teaching mode that combines videos and images is beneficial to both teachers and students. |
Author | Li, Lina |
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Cites_doi | 10.1155/2022/9174441 10.1155/2022/5816453 10.1016/j.jobe.2021.103182 10.1007/s11277-018-5245-0 10.1007/s00500-019-04095-z 10.1155/2022/1268303 10.1155/2022/6328768 10.1049/iet-spr.2017.0320 10.1088/1402-4896/abd50f 10.1080/14613808.2021.2015309 10.3389/fpsyg.2021.705116 10.3390/s20061734 10.3389/fpsyg.2021.751406 |
ContentType | Journal Article |
Copyright | Copyright © 2022 Lina Li. Copyright © 2022 Lina Li. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 |
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SubjectTerms | Artificial neural networks Audiences Big Data Clustering Continuous improvement Correlation coefficients Design Education Efficiency Happiness Image classification Knowledge Learning Music Musical instruments Neural networks Performance prediction Piano Pianos Players Students Teaching methods Video |
Title | Design and Application of the Piano Teaching System Integrating Videos and Images |
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