A Multiclass Semi-Supervised Deep Convolutional Generative Adversarial Network for Music Genre Classification Using Mel-Frequency Cepstral Coefficients

• Published in: 2024 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE) pp. 1 - 6
• Main Authors: Satapathy, Ashutosh, Duda, Neelima, Machcha, Jaswanthi, Thottempudi, Kokila
• Format: Conference Proceeding
• Language: English
• Published: IEEE 24.01.2024
• Subjects: Computational modeling; Data augmentation; Feature extraction; Generative adversarial networks; GTZAN; Indian Music Genre; Mel-frequency Cepstral Coefficients; Multiclass Classification; Music; Semi-Supervised Deep Convolutional Generative Adversarial Network; Training; Training data

The growing consumer base and expanding market for various music styles highlight the necessity of classifying music genres to cater to people's preferences. Manual music ranking is a labor-intensive process for listeners, prompting the need for a more efficient approach. This involves the extr...