Music Genre Classification: Training an AI model

• URL: http://arxiv.org/abs/2405.15096v1
• Date: Thu, 23 May 2024 23:07:01 GMT
• Title: Music Genre Classification: Training an AI model
• Authors: Keoikantse Mogonediwa,
• Abstract summary: Music genre classification is an area that utilizes machine learning models and techniques for the processing of audio signals. In this research I explore various machine learning algorithms for the purpose of music genre classification, using features extracted from audio signals. I aim to asses the robustness of machine learning models for genre classification, and to compare their results.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Music genre classification is an area that utilizes machine learning models and techniques for the processing of audio signals, in which applications range from content recommendation systems to music recommendation systems. In this research I explore various machine learning algorithms for the purpose of music genre classification, using features extracted from audio signals.The systems are namely, a Multilayer Perceptron (built from scratch), a k-Nearest Neighbours (also built from scratch), a Convolutional Neural Network and lastly a Random Forest wide model. In order to process the audio signals, feature extraction methods such as Short-Time Fourier Transform, and the extraction of Mel Cepstral Coefficients (MFCCs), is performed. Through this extensive research, I aim to asses the robustness of machine learning models for genre classification, and to compare their results.

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