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Research on Pattern Recognition Methods of Traditional Music Style Characteristics in Big Data Environment

Qinfei Han

Qinfei Han

Conservatory of Music, Youngnam UniversityGyeongsan, Korea
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Han, Qinfei
 und 
Ning Wang

Ning Wang

School of Music, Linyi UniversityLinyi, China
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Wang, Ning
  
21. März 2025
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Online veröffentlicht: 21. März 2025
Eingereicht: 03. Nov. 2024
Akzeptiert: 24. Feb. 2025
DOI: https://doi.org/10.2478/amns-2025-0658
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© 2025 Qinfei Han et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Optimal hyperplane in linearly separable case
Optimal hyperplane in linearly separable case

Figure 2.

Optimal hyperplane in the case of linear indivisibility
Optimal hyperplane in the case of linear indivisibility

Figure 3.

Changes of support vector after increment
Changes of support vector after increment

Figure 4.

Pre-aggravated comparison
Pre-aggravated comparison

Figure 5.

Music signal frame
Music signal frame

Figure 6.

Traditional time-domain characteristic parameter extraction
Traditional time-domain characteristic parameter extraction

Figure 7.

Hamming frequency response
Hamming frequency response

Figure 8.

The energy spectrum of one frame signal after processing
The energy spectrum of one frame signal after processing

Figure 9.

MFCC of different music styles
MFCC of different music styles

Figure 10.

Identification result contrast
Identification result contrast

Figure 11.

Incremental SVM model recognition results
Incremental SVM model recognition results
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Englisch
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Fachgebiete der Zeitschrift:
Biologie, Biologie, andere, Mathematik, Angewandte Mathematik, Mathematik, Allgemeines, Physik, Physik, andere
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