References
- K. Kim and H. Kim, "Scaling learning algorithms towards AI," Journal of Digital Content Society, Vol. 14, No.4, pp.481-491, December, 2013. https://doi.org/10.9728/dcs.2013.14.4.481
- L. Lu, H. Jiang, and H. Zhang, "A robust audio classification and segmentation method," in Proceeding of ACM International Conference on Multimedia, Ottawa, pp.203-211, 2001.
- M. Xu, N. Maddage, C. Xu, M. Kankanhalli, and Q. Tian, "Creating audio keywords for event detection in soccer video," in Proceeding of IEEE International Conference on Multimedia and Expo, Baltimore: MD, pp.281-284, 2003.
- W. Cheng, W. Chu, and J. Wu, "Semantic context v detection based on hierarchical audio models," in Proceeding of ACM SIGMM International Workshop on Multimedia Information Retrieval, Berkeley: CA, pp.109-115, 2003.
- H. Lee, P. Pham, Y. Largman, and Y. Ng, "Unsupervised feature learning for audio classification using convolutional deep belief networks," in Proceeding of Advances in Neural Information Processing Systems, Vancouver, pp.1096-1104, 2009.
- Y. Bengio and Y. LeCun, "Scaling learning algorithms towards AI," Large-scale Kernel Machines, Vol. 34, No.5, pp.321-360, August, 2007.
- J. Portelo, M. Bugalho, I. Trancoso, J. Neto, A. Abad, and A. Serralheiro, "Non-speech audio event detection," in Proceeding of Internationa Conference on Acoustics, Speech and Signal Processing, Taipei, pp.1973-1976, 2009.
- L. Ballan, A. Bazzica, M. Bertini, A. Bimbo, and G. Serra, "Deep networks for audio event classification in soccer videos," in Proceeding of International Conference on Multimedia and Expo, Cancun, pp.474-477, 2009.
- T. Heittola, A. Mesaros, A. Eronen, T. Virtanen, "Scaling learning algorithms towards AI," EURASIP Journal on Audio, Speech, and Music Processing, Vol.1, pp.1-13, January, 2013.
- K. Zvi, and T. Orith, "Audio event classification using deep neural networks," in Proceeding of INTERSPEECH, Lyon, pp.1482-1486, 2013.
- M. Lim and J. Kim, "Audio Event Classification Using Deep Neural Networks," Phonetics and Speech Sciences, Vol. 7, No. 4, pp.27-33, January, 2015. https://doi.org/10.13064/KSSS.2015.7.4.027
- H. Larochelle, D. Erhan, A. Courville, J. Bergstra, and Y. Bengio, "An empirical evaluation of deep architectures on problems with many factors of variation," in Proceeding of International Conference on Machine learning, Corvaliis: OR, pp.473-480, 2007.
- E. Dahl, N. Sainath, and E. Hinton, "Improving deep neural networks for LVCSR using rectified linear units and dropout," in Proceeding of International Conference on Acoustics, Speech and Signal Processing, Vancouver, pp.8609-8613, 2013.
- L. Bottou, Advanced Lectures on Machine Learning, Springer, pp. 146-168, 2004.
- J. Salamon, C. Jacoby, and J. Bello, "A dataset and taxonomy for urban sound research," in Proceeding of ACM International Conference on Multimedia, Orlando: FL, pp.1041-1044, 2014.
- M. Slaney, "Semantic-audio retrieval," in Proceeding of International Conference on Acoustics, Speech and Signal Processing, Orlando: FL, pp.1408-1411, 2002.
- S. Young, G. Evermann, M. Gales, and P. Woodland, The HTK book (for HTK version 3.4), Cambridge, U.K.: Entropic, 2006.
- M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. Corrado, A. Davis, J. Dean, M. Devin, S. Ghemawat, I. Goodfellow, A. Harp, G. Irving, M. Isard, Y. Jia, R. Jozefowicz, L. Kaiser, M. Kudlur, J. Levenberg, D. Mane, R. Monga, S. Moore, D. Murray, C. Olah, M. Schuster, J. Shlens, B. Steiner, I. Sutskever, K. Talwar, P. Tucker, V. Vanhoucke, V. Vasudevan, F. Viegas, O. Vinyals, P. Warden, M. Wattenberg, M. Wicke, Y. Yu, and X. Zheng, Tensorflow: Large-scale machine learning on heterogeneous distributed systems, Available: https://www.tensorflow.org/
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