Research on Music Style Classification Based on Deep Learning

Abstract

Music style is one of the important labels for music classification, and the current music style classification methods extract features such as rhythm and timbre of music and use classifiers to achieve classification. The classification accuracy is not only affected by the classifier but also limited by the effect of music feature extraction, which leads to poor classification accuracy and stability. In response to the abovementioned defects, a deep-learning-based music style classification method will be studied. The music signal is framed using filters and Hamming windows, and the MFCC coefficient features of music are extracted by discrete Fourier transform. A convolutional recurrent neural network structure combining CNN and RNN is designed and trained to determine the parameters to achieve music style classification. Analysis of the simulation experimental data shows that the classification accuracy of the studied classification method is at least 93.3%, and the classification time overhead is significantly reduced, the classification results are stable, and the results are reliable.

Classification of Assamese Folk Songs’ Melody using Supervised Learning Techniques

“…https://www.indjst.org/ To identify melody, Standard MIDI files, as well as symbolic scores, are used (1,2) whereas our approach is based on MFCC features. Several pieces of research are performed that use MFCC in order to identify Music style, Musical instruments as well as Singer (4,5,8) . In the identification of singers, MFCC features are found to be better than the CRP features (8) .…”

“…To classify the songs into their respective genre CNN is also on spectrograms extracted from the songs (3) . MFCC-based CNN and RNN (Recurrent Neural Network) are used to determine the music style where 93.3% classification accuracy is achieved (4) .…”

“…In other words, these are the cepstral representation of a signal where the frequency bands are distributed according to mel-scale. The MFCCs have been applied in a wide range of audio analyses, and have shown good performance compared to other features (4,5,8) .…”

Retracted: Research on Music Style Classification Based on Deep Learning

“…Computational and Mathematical Methods in Medicine has retracted the article titled “Research on Music Style Classification Based on Deep Learning” [ 1 ] due to concerns that the peer review process has been compromised.…”

“…Computational and Mathematical Methods in Medicine has retracted the article titled "Research on Music Style Classification Based on Deep Learning" [1] due to concerns that the peer review process has been compromised. Following an investigation conducted by the Hindawi Research Integrity team [2], significant concerns were identified with the peer reviewers assigned to this article; the investigation has concluded that the peer review process was compromised.…”