The Integration of Traditional Music Culture in Modern Informational Music Teaching
In this paper, in the process of music teaching, the music notes characterized in the time domain are Fourier transformed to the frequency domain, and the resulting notes in the frequency domain are analyzed and processed to obtain the inverted spectral domain features of the notes. On the basis of...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2023.2.01627 |
| _version_ | 1797340478730928128 |
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| author | Hou Changzhi |
| author_facet | Hou Changzhi |
| author_sort | Hou Changzhi |
| collection | DOAJ |
| description | In this paper, in the process of music teaching, the music notes characterized in the time domain are Fourier transformed to the frequency domain, and the resulting notes in the frequency domain are analyzed and processed to obtain the inverted spectral domain features of the notes. On the basis of the cepstrum features, the music recognition model based on the depth confidence network is constructed, and after the training of the depth confidence network, the overfitting phenomenon often occurs for the depth confidence network, and the optimization is carried out by embedding the Dropout method between the implicit layers. From the perspective of music recognition and informationized music teaching, the research on traditional music culture integration of informationized music teaching is designed, and statistical analysis and simulation analysis methods are constructed. The results show that better recognition performance than using music features from different convolutional layers can be obtained using Deep Confidence Networks, with values of 77.5%, 78.8%, and 78.2%, respectively, and that music recognition research based on Deep Confidence Networks is able to better explore and pass on traditional music culture. In the linear regression analysis between the factors of incorporating folk songs into music teaching, the Sig. F and Sig values are 0, which are smaller than the significance level of 0.01 and 0.05, indicating that there is a significant relationship between the factors of students’ gender, age, whether they like folk songs, and the channels of exposure to folk songs and whether folk songs are incorporated into the music teaching program of colleges and universities. This study takes folk songs as representative of traditional music culture, raises people’s awareness of the value of folk songs, and enhances their understanding of the importance of music culture inheritance. |
| first_indexed | 2024-03-08T10:04:11Z |
| format | Article |
| id | doaj.art-5191838043434064beee859ee0107728 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:04:11Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-5191838043434064beee859ee01077282024-01-29T08:52:45ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.2.01627The Integration of Traditional Music Culture in Modern Informational Music TeachingHou Changzhi01Conservatory of Music, Chengdu Normal University, Chengdu, Sichuan, 611130, China.In this paper, in the process of music teaching, the music notes characterized in the time domain are Fourier transformed to the frequency domain, and the resulting notes in the frequency domain are analyzed and processed to obtain the inverted spectral domain features of the notes. On the basis of the cepstrum features, the music recognition model based on the depth confidence network is constructed, and after the training of the depth confidence network, the overfitting phenomenon often occurs for the depth confidence network, and the optimization is carried out by embedding the Dropout method between the implicit layers. From the perspective of music recognition and informationized music teaching, the research on traditional music culture integration of informationized music teaching is designed, and statistical analysis and simulation analysis methods are constructed. The results show that better recognition performance than using music features from different convolutional layers can be obtained using Deep Confidence Networks, with values of 77.5%, 78.8%, and 78.2%, respectively, and that music recognition research based on Deep Confidence Networks is able to better explore and pass on traditional music culture. In the linear regression analysis between the factors of incorporating folk songs into music teaching, the Sig. F and Sig values are 0, which are smaller than the significance level of 0.01 and 0.05, indicating that there is a significant relationship between the factors of students’ gender, age, whether they like folk songs, and the channels of exposure to folk songs and whether folk songs are incorporated into the music teaching program of colleges and universities. This study takes folk songs as representative of traditional music culture, raises people’s awareness of the value of folk songs, and enhances their understanding of the importance of music culture inheritance.https://doi.org/10.2478/amns.2023.2.01627deep confidence networkfourier transforminverse spectral domain featuresmusic recognition modelmusic teaching00a65 |
| spellingShingle | Hou Changzhi The Integration of Traditional Music Culture in Modern Informational Music Teaching Applied Mathematics and Nonlinear Sciences deep confidence network fourier transform inverse spectral domain features music recognition model music teaching 00a65 |
| title | The Integration of Traditional Music Culture in Modern Informational Music Teaching |
| title_full | The Integration of Traditional Music Culture in Modern Informational Music Teaching |
| title_fullStr | The Integration of Traditional Music Culture in Modern Informational Music Teaching |
| title_full_unstemmed | The Integration of Traditional Music Culture in Modern Informational Music Teaching |
| title_short | The Integration of Traditional Music Culture in Modern Informational Music Teaching |
| title_sort | integration of traditional music culture in modern informational music teaching |
| topic | deep confidence network fourier transform inverse spectral domain features music recognition model music teaching 00a65 |
| url | https://doi.org/10.2478/amns.2023.2.01627 |
| work_keys_str_mv | AT houchangzhi theintegrationoftraditionalmusiccultureinmoderninformationalmusicteaching AT houchangzhi integrationoftraditionalmusiccultureinmoderninformationalmusicteaching |