Abstract: Music classification is a field in the field of Music Recovery and sound signal processing research. Neural Network is a modern way of classifying music. The classification of music using neural networks (NN) has become very successful in past few years. Different song collections, machine learning methods, input formats, and neural network applications are all to varying degrees effective. Spectrograms made from time-slices of songs are input to a neural network in order to classify songs into the appropriate musical genres. The Neural Network (NN) employs spectrograms generated by time song slaves as an entry to classify songs into their numerous genres. The Convolutional Neural Network (CNN) audio signal input system will employ the generated spectrograms. Tasks involving picture pattern recognition are handled by CNNs. Acoustic feature extraction is the most important process while evaluating music. Models are trained using the GTZAN dataset in the suggested system.

Keywords: Deep learning, spectrogram, music, classification of music genre, Convolution Neural Network (CNN).

PDF | DOI: 10.17148/IJARCCE.2023.12231

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