[Retracted] Automatic Classification Method of Music Genres Based on Deep Belief Network and Sparse Representation

Abstract

Aiming at the problems of poor classification effect, low accuracy, and long time in the current automatic classification methods of music genres, an automatic classification method of music genres based on deep belief network and sparse representation is proposed. The music signal is preprocessed by framing, pre-emphasis, and windowing, and the characteristic parameters of the music signal are extracted by Mel frequency cepstrum coefficient analysis. The restricted Boltzmann machine is trained layer by layer to obtain the connection weights between layers of the depth belief network model. According to the output classification, the connection weights in the model are fine-tuned by using the error back-propagation algorithm. Based on the deep belief network model after fine-tuning training, the structure of the music genre classification network model is designed. Combined with the classification algorithm of sparse representation, for the training samples of sparse representation music genre, the sparse solution is obtained by using the minimum norm, the sparse representation of test vector is calculated, the category of training samples is judged, and the automatic classification of music genre is realized. The experimental results show that the music genre automatic classification effect of the proposed method is better, the classification accuracy rate is higher, and the classification time can be effectively shortened.

Music sentiment classification based on an optimized CNN-RF-QPSO model

“…Compared to LR, which is based on global decision-making, the RF algorithm estimates missing values and maintains a certain level of classification accuracy in the presence of missing data or missing features in the sample set (Tian et al , 2022), thus more resistant to interference than LR. Unlike the commonly used SVM in classification, RF as a multi-classifier does not require multiple training sessions and has higher training efficiency (Pan, 2022; Shan and Kuo, 2003; Elbit and Aydin, 2020). For these reasons, RF is selected as the classifier of the model.…”

Retracted: Automatic Classification Method of Music Genres Based on Deep Belief Network and Sparse Representation

“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”