Music Genre Classification using Deep Learning
Mitt Shah, Nandit Pujara, Kaushil Mangaroliya, Lata Gohil, Tarjni Vyas, Sheshang Degadwala
20222022 6th International Conference on Computing Methodologies and Communication (ICCMC)30 citationsDOI
Abstract
One of the fascinating subjects in the area of Music Information Retrieval (MIR) is the classification of music as it is played into different genres. Machine learning is used in this analysis. To predict the genre of the audio signal, models such as Support Vector Machines (SVM), Random Forests, XGB (eXtreme Gradient Boosting), and Convolutional Neural Networks (CNN) are used. The GTZAN dataset was used for model training and testing. Machine learning and deep learning models each had their own set of features. A comparison analysis is proposed between these models, demonstrating that CNN outperforms machine learning models.
Topics & Concepts
Computer scienceSupport vector machineArtificial intelligenceRandom forestConvolutional neural networkMachine learningMusic information retrievalBoosting (machine learning)Deep learningGradient boostingOnline machine learningSet (abstract data type)Artificial neural networkPattern recognition (psychology)ArtProgramming languageVisual artsMusicalMusic and Audio ProcessingSpeech and Audio ProcessingMusic Technology and Sound Studies