Using Machine Learning Algorithm to Describe the Connection between the Types and Characteristics of Music Signal

Abstract

Music classification is conducive to online music retrieval, but the current music classification model finds it difficult to accurately identify various types of music, which makes the classification effect of the current music classification model poor. In order to improve the accuracy of music classification, a music classification model based on multifeature fusion and machine learning algorithm is proposed. First, we obtain the music signal, and then extract various features from the classification of the music signal, and use machine learning algorithms to describe the type of music signal and the relationship between the features. The music classifier and deep belief network machine learning models in shallow logistic regression are established, respectively. Experiments were designed for these two models to verify the applicability of the model for music classification. By comparing the experimental results, it is found that the classification accuracy of the deep confidence network model is higher than that of the logistic regression model, but the number of iterations needed for its accuracy to converge is also higher than that of the logistic regression model. Compared with other current music classification models, this model reduces the time of constructing music classifier, speeds up the speed of music classification, and can identify various types of music with high precision. The accuracy of music classification is obviously improved, which verifies the superiority of this music classification model.

[Retracted] Music Classification Method Using Big Data Feature Extraction and Neural Networks

“…Sun suggested that third-party recommendations be used in mobile application scenarios. They use the current location of users as context information and collect preferences of other users at the current location as recommendations [ 14 ]. Kim suggested using new features such as harmonic coefficients in features and proposed a more robust music and speech classification algorithm [ 15 ].…”

Music Intervention in Human Life, Work, and Disease: A Survey

“…Harmonic progression is the horizontal connection of chords, i.e., the sound formed by connecting chords in a certain order. Harmonies are produced simultaneously in music, but they are in harmony with each other [7] , making the music less monotonous and richer in content and being important for harmonizing the musical structure and for composing the musical form. The general style of music can sometimes be inferred from chords.…”

“…Melody is the trajectory of sound movement formed by the arrangement and combination of different high and low notes [7] . Melody is the main thread of music and is a critical factor in determining music genres [8] .…”