Classification method of popular music score style based on SVM
by Qiang Tuo; Xiaoming Zhao
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 15, No. 3/4, 2023

Abstract: In order to improve the classification accuracy of popular music score style, this paper proposes a new classification method of popular music score style based on SVM. Firstly, the fractional spectral subtraction algorithm is used to enhance the popular music score signal. Secondly, according to the unique characteristics of the striking component and the harmony part in the pop music spectrum, the striking part and the harmony part in the pop music spectrum are separated by means of energy peak removal and peak frequency filtering. Finally, taking the striking part and harmony part of the separated pop music spectrum as input, the SVM algorithm is used to realise the style classification of pop music. The experimental results show that this method can enhance the popular music score signal, and can effectively classify different styles of popular music score, with a classification accuracy of 99.4%.

Online publication date: Wed, 31-Jan-2024

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