Abstract
Abstract: Music genre classification is a fundamental task in the field of music information retrieval (MIR) and has gained significant attention in recent years due to the rapid growth of digital music collections. This research paper presents a comprehensive review of the application of machine learning techniques for music genre classification. We explore various methodologies, feature extraction techniques, and classification algorithms used in the domain, highlighting their strengths, limitations, and recent advancements. The objective of this paper is to provide researchers and practitioners with a comprehensive understanding of the current state-of- the-art approaches, challenges, and future directions in music genre classification using machine learning.
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