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Music genre classification using deep learning: a comparative analysis of CNNs and RNNs

  
18 lis 2024

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Pelchat, N., & Gelowitz, C. M. (2020). Neural network music genre classification. Canadian Journal of Electrical and Computer Engineering, 43(3), 170-173. Search in Google Scholar

Oramas, S., Barbieri, F., Nieto Caballero, O., & Serra, X. (2018). Multimodal deep learning for music genre classification. Transactions of the International Society for Music Information Retrieval. 2018; 1 (1): 4-21. Search in Google Scholar

Costa, Y. M., Oliveira, L. S., Koerich, A. L., Gouyon, F., & Martins, J. G. (2012). Music genre classification using LBP textural features. Signal Processing, 92(11), 2723-2737. Search in Google Scholar

Nanni, L., Costa, Y. M., Lumini, A., Kim, M. Y., & Baek, S. R. (2016). Combining visual and acoustic features for music genre classification. Expert Systems with Applications, 45, 108-117. Search in Google Scholar

Ghildiyal, A., Singh, K., & Sharma, S. (2020, November). Music genre classification using machine learning. In 2020 4th international conference on electronics, communication and aerospace technology (ICECA) (pp. 1368-1372). IEEE. Search in Google Scholar

Ndou, N., Ajoodha, R., & Jadhav, A. (2021, April). Music genre classification: A review of deep-learning and traditional machine-learning approaches. In 2021 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS) (pp. 1-6). IEEE. Search in Google Scholar

Elbir, A., & Aydin, N. (2020). Music genre classification and music recommendation by using deep learning. Electronics Letters, 56(12), 627-629. Search in Google Scholar

Brunner, G., Wang, Y., Wattenhofer, R., & Zhao, S. (2018, November). Symbolic music genre transfer with cyclegan. In 2018 ieee 30th international conference on tools with artificial intelligence (ictai) (pp. 786-793). IEEE. Search in Google Scholar

Goulart, A. J. H., Guido, R. C., & Maciel, C. D. (2012). Exploring different approaches for music genre classification. Egyptian Informatics Journal, 13(2), 59-63. Search in Google Scholar

Yu, Y., Luo, S., Liu, S., Qiao, H., Liu, Y., & Feng, L. (2020). Deep attention based music genre classification. Neurocomputing, 372, 84-91. Search in Google Scholar

Corrêa, D. C., & Rodrigues, F. A. (2016). A survey on symbolic data-based music genre classification. Expert Systems with Applications, 60, 190-210. Search in Google Scholar

Ceylan, H. C., Hardalaç, N., Kara, A. C., & Firat, H. (2021). Automatic music genre classification and its relation with music education. World Journal of Education, 11(2), 36-45. Search in Google Scholar

Chillara, S., Kavitha, A. S., Neginhal, S. A., Haldia, S., & Vidyullatha, K. S. (2019). Music genre classification using machine learning algorithms: a comparison. Int Res J Eng Technol, 6(5), 851-858. Search in Google Scholar

Vishnupriya, S., & Meenakshi, K. (2018, January). Automatic music genre classification using convolution neural network. In 2018 international conference on computer communication and informatics (ICCCI) (pp. 1-4). IEEE. Search in Google Scholar

Bhatia, J. K., Singh, R. D., & Kumar, S. (2021, October). Music genre classification. In 2021 5th International Conference on Information Systems and Computer Networks (ISCON) (pp. 1-4). IEEE. Search in Google Scholar

Markov, K., & Matsui, T. (2014). Music genre and emotion recognition using Gaussian processes. IEEE access, 2, 688-697. Search in Google Scholar

Rajanna, A. R., Aryafar, K., Shokoufandeh, A., & Ptucha, R. (2015, December). Deep neural networks: A case study for music genre classification. In 2015 IEEE 14th international conference on machine learning and applications (ICMLA) (pp. 655-660). IEEE. Search in Google Scholar

Ramírez, J., & Flores, M. J. (2020). Machine learning for music genre: multifaceted review and experimentation with audioset. Journal of Intelligent Information Systems, 55(3), 469-499. Search in Google Scholar

Liu, C., Feng, L., Liu, G., Wang, H., & Liu, S. (2021). Bottom-up broadcast neural network for music genre classification. Multimedia Tools and Applications, 80, 7313-7331. Search in Google Scholar

Rosner, A., & Kostek, B. (2018). Automatic music genre classification based on musical instrument track separation. Journal of Intelligent Information Systems, 50, 363-384. Search in Google Scholar

Walworth, D. D. (2003). The effect of preferred music genre selection versus preferred song selection on experimentally induced anxiety levels. Journal of Music Therapy, 40(1), 2-14. Search in Google Scholar

Singh, Y., & Biswas, A. (2022). Robustness of musical features on deep learning models for music genre classification. Expert Systems with Applications, 199, 116879. Search in Google Scholar

Cheng, Y. H., Chang, P. C., Nguyen, D. M., & Kuo, C. N. (2020). Automatic Music Genre Classification Based on CRNN. Engineering Letters, 29(1). Search in Google Scholar

Język:
Angielski
Częstotliwość wydawania:
1 razy w roku
Dziedziny czasopisma:
Nauki biologiczne, Nauki biologiczne, inne, Matematyka, Matematyka stosowana, Matematyka ogólna, Fizyka, Fizyka, inne