Feature Analysis and Application of Music Works Based on Artificial Neural Network

[1] Oord, A. V. D., Dieleman, S., & Schrauwen, B. (2013). Deep content-based music recommendation. In Neural Information Processing Systems Conference (NIPS 2013) (pp. 2643-2651). Neural Information Processing Systems Foundation. Oord A. V. D. Dieleman S. Schrauwen B. ( 2013 ). Deep content-based music recommendation . In Neural Information Processing Systems Conference (NIPS 2013) (pp. 2643 – 2651 ). Neural Information Processing Systems Foundation . Search in Google Scholar

[2] Nanni, L., Costa, Y. M. G., Lumini, A., et al. (2016). Combining visual and acoustic features for music genre classification. Expert Systems with Applications, 45, 108–117. Nanni L. Costa Y. M. G. Lumini A. ( 2016 ). Combining visual and acoustic features for music genre classification . Expert Systems with Applications , 45 , 108 – 117 . Search in Google Scholar

[3] Du, W., Lin, H., & Sun, J., et al. (2016). A new hierarchical method for music genre classification. In Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), International Congress on (pp. 1033-1037). IEEE. Du W. Lin H. Sun J. ( 2016 ). A new hierarchical method for music genre classification . In Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), International Congress on (pp. 1033 – 1037 ). IEEE . Search in Google Scholar

[4] Yoon, J., Lim, H., & Kim, D. W. (2016). Music genre classification using feature subset search. International Journal of Machine Learning and Computing, 6(2), 134. Yoon J. Lim H. Kim D. W. ( 2016 ). Music genre classification using feature subset search . International Journal of Machine Learning and Computing , 6 ( 2 ), 134 . Search in Google Scholar

[5] Dai, J., Liu, W., Ni, C., et al. (2015). "Multilingual" deep neural network for music genre classification. In INTERSPEECH (pp. 2907-2911). Dai J. Liu W. Ni C. ( 2015 ). “Multilingual” deep neural network for music genre classification . In INTERSPEECH (pp. 2907 – 2911 ). Search in Google Scholar

[6] Ahmed, F., Paul, P. P., & Gavrilova, M. (2016). Music genre classification using a gradient-based local texture descriptor. In Intelligent Decision Technologies (pp. 455-464). Springer International Publishing. Ahmed F. Paul P. P. Gavrilova M. ( 2016 ). Music genre classification using a gradient-based local texture descriptor . In Intelligent Decision Technologies (pp. 455 – 464 ). Springer International Publishing . Search in Google Scholar

[7] Zhu, J., Xue, X., & Lu, H. (2004). Musical genre classification by instrumental features. In ICMC. Zhu J. Xue X. Lu H. ( 2004 ). Musical genre classification by instrumental features . In ICMC . Search in Google Scholar

[8] Zhang, P., Zheng, X., Zhang, W., et al. (2015). A deep neural network for modeling music. In Proceedings of the 5th ACM on International Conference on Multimedia Retrieval (pp. 379-386). ACM. Zhang P. Zheng X. Zhang W. ( 2015 ). A deep neural network for modeling music . In Proceedings of the 5th ACM on International Conference on Multimedia Retrieval (pp. 379 – 386 ). ACM . Search in Google Scholar

[9] Matityaho, B., & Furst, M. (1995). Neural network based model for classification of music type. In Eighteenth Convention of Electrical and Electronics Engineers in Israel (pp. 4.3.4/1-4.3.4/5). Tel Aviv, Israel. Matityaho B. Furst M. ( 1995 ). Neural network based model for classification of music type . In Eighteenth Convention of Electrical and Electronics Engineers in Israel (pp. 4.3.4/1 – 4.3.4/5 ). Tel Aviv , Israel . Search in Google Scholar

[10] Tzanetakis, G., & Cook, P. (2002). Musical genre classification of audio signals. IEEE Transactions on Speech and Audio Processing, 10(5), 293–302. Tzanetakis G. Cook P. ( 2002 ). Musical genre classification of audio signals . IEEE Transactions on Speech and Audio Processing , 10 ( 5 ), 293 – 302 . Search in Google Scholar

[11] Shao, X., Xu, C., & Kankanhalli, M. S. (2004). Unsupervised classification of music genre using hidden Markov model. In 2004 IEEE International Conference on Multimedia and Expo (ICME) (Vol. 3, pp. 2023-2026). IEEE. Shao X. Xu C. Kankanhalli M. S. ( 2004 ). Unsupervised classification of music genre using hidden Markov model . In 2004 IEEE International Conference on Multimedia and Expo (ICME) (Vol. 3 , pp. 2023 – 2026 ). IEEE . Search in Google Scholar

[12] Lampropoulos, A. S., Lampropoulou, P. S., & Tsihrintzis, G. A. (2005). Musical genre classification enhanced by improved source separation technique. In International Society for Music Information Retrieval Conference (pp. 576-581). Lampropoulos A. S. Lampropoulou P. S. Tsihrintzis G. A. ( 2005 ). Musical genre classification enhanced by improved source separation technique . In International Society for Music Information Retrieval Conference (pp. 576 – 581 ). Search in Google Scholar

[13] Tzagkarakis, C., Mouchtaris, A., & Tsakalides, P. (2006). Musical genre classification generalized and alpha-stable modeling. In Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. IEEE International Conference on (Vol. 5, pp. V-V). IEEE. Tzagkarakis C. Mouchtaris A. Tsakalides P. ( 2006 ). Musical genre classification generalized and alpha-stable modeling . In Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. IEEE International Conference on (Vol. 5 , pp. V – V ). IEEE . Search in Google Scholar

[14] Lee, H., Pham, P., Largman, Y., & Ng, A. Y. (2009). Unsupervised feature learning for audio classification using convolutional deep belief networks. In Advances in Neural Information Processing Systems (pp. 1096-1104). Lee H. Pham P. Largman Y. Ng A. Y. ( 2009 ). Unsupervised feature learning for audio classification using convolutional deep belief networks . In Advances in Neural Information Processing Systems (pp. 1096 – 1104 ). Search in Google Scholar

[15] Fan, S. (2021). Music genre classification based on improved BP neural network. Software Engineering, 24(9), 17–20. Fan S. ( 2021 ). Music genre classification based on improved BP neural network . Software Engineering , 24 ( 9 ), 17 – 20 . Search in Google Scholar

[16] Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9(8), 1735–1780. Hochreiter S. Schmidhuber J. ( 1997 ). Long short-term memory . Neural Computation , 9 ( 8 ), 1735 – 1780 . Search in Google Scholar

[17] Liuyuqing, X., Jun, X., & Caoshouqi. (2022). Path planning of underwater autonomous navigation robot based on improved ant colony algorithm. Computer Engineering and Science, 44(3), 536–544. Liuyuqing X. Jun X. Caoshouqi . ( 2022 ). Path planning of underwater autonomous navigation robot based on improved ant colony algorithm . Computer Engineering and Science , 44 ( 3 ), 536 – 544 . Search in Google Scholar

[18] Wang, F. (2020). Research and implementation of forest fire identification and detection system based on deep learning [Doctoral dissertation]. University of Electronic Science and Technology. Wang F. ( 2020 ). Research and implementation of forest fire identification and detection system based on deep learning [Doctoral dissertation]. University of Electronic Science and Technology . Search in Google Scholar

[19] Wanglingxia, & Zhao, H. (2016). Improved ant colony algorithm for task scheduling in cloud computing environment. Industrial Instruments and Automation Devices, (2), 3–6. Wanglingxia Zhao H. ( 2016 ). Improved ant colony algorithm for task scheduling in cloud computing environment . Industrial Instruments and Automation Devices , ( 2 ), 3 – 6 . Search in Google Scholar

[20] Chenqinrong, Liushunlai, & Linxibin. (2016). A hybrid optimization algorithm for cloud computing resource scheduling. Journal of Hanshan Normal University, 37(6), 15–23. Chenqinrong Liushunlai Linxibin ( 2016 ). A hybrid optimization algorithm for cloud computing resource scheduling . Journal of Hanshan Normal University , 37 ( 6 ), 15 – 23 . Search in Google Scholar

[21] Wang, B., & Xu, J. (2014). Research on ant colony optimization algorithm based on cloud computing environment. New Technology and Process, (8), 49–52. Wang B. Xu J. ( 2014 ). Research on ant colony optimization algorithm based on cloud computing environment . New Technology and Process , ( 8 ), 49 – 52 . Search in Google Scholar

[22] Grey, J. M., & Gordon, J. W. (1978). Perceptual effects of spectral modifications on musical timbres. Journal of the Acoustical Society of America, 63(63), 1493–1500. Grey J. M. Gordon J. W. ( 1978 ). Perceptual effects of spectral modifications on musical timbres . Journal of the Acoustical Society of America , 63 ( 63 ), 1493 – 1500 . Search in Google Scholar

[23] Zhang, Z., Qiao, J., & Yang, G. (2011). Structure model of function-dividing design for BP neural network. Control and Decision, 26(11). Zhang Z. Qiao J. Yang G. ( 2011 ). Structure model of function-dividing design for BP neural network . Control and Decision , 26 ( 11 ). Search in Google Scholar