參考文獻 |
[1] M. A. Casey, R. Veltkamp, M. Goto, M. Leman, C. Rhodes, and M. Slaney, “Content-Based Music Information Retrieval: Current Directions and Feature Challenges,” in Proc. of the IEEE, vol. 96 no. 4, pp. 668-696, April 2008.
[2] 侯志欽,聲學原理與多媒體音訊科技,初版,台灣商務印書館,台北市,民國九十六年。
[3] 陳仁寬,樂理入門與指導,初版,五洲出版有限公司,台北市,民國八十五年。
[4] Music Information Retrieval Evaluation eXchange,
http://www.music-ir.org/mirex/wiki/2006:Main_Page
[5] J. Serra, E. Gomez, and P. Herrera, “Audio cover song identification and similarity: background, approaches, evaluation, and beyond,” Advances in Music Information Retrieval, vol. 274, ch. 14, pp. 307-332, March 2010.
[6] D. P. W. Ellis, and G.E. Poliner, “Identifying ‘Cover Songs’ with Chroma Features and Dynamic Programming Beat Tracking,” in Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, Honolulu, Hawaii, U.S.A., pp. 1429-1432, April 15-20, 2007.
[7] K. Lee, “Identifying Cover Songs from Audio Using Harmonic Representation,” extended abstract submitted to MIREX (Music Information Retrieval Evaluation eXchange) task on Audio Cover Song Identification, 2006.
[8] C. Sailer, and Karin Dressler, “Finding cover songs by melodic similarity,” extended abstract submitted to MIREX (Music Information Retrieval Evaluation eXchange) task on Audio Cover Song Identification, 2006.
[9] D. P. W. Ellis, and C. Cotton, “THE 2007 LABROSA COVER SONG DETECTION SYSTEM,” extended abstract submitted to MIREX (Music Information Retrieval Evaluation eXchange) task on Audio Cover Song Identification, 2006.
[10] J. Serra, and E. Gomez, “Audio cover song identification based on tonal sequence alignment,” in Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, Las Vegas, Nevada, U.S.A., pp.61-64, March 30- April 4, 2008.
[11] S. Ravuri, and D. P. W. Ellis, “Cover song detection: From high scores to general classification,” in Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, Dallas, Texas, U.S.A., pp. 65-68, March 14-19, 2010.
[12] J. Serra, “Music similarity based on sequences of descriptors: tonal features applied to audio cover song identification,” M.S. thesis, MTG, Universitat Pompeu Fabra, Barcelona, Spain, 2007.
[13] 謝佳斌,AAC壓縮域翻唱歌曲辨識系統。中央大學通訊工程學系碩士學位論文,2012。
[14] 莊詠婷,利用AAC壓縮域特徵之古典樂翻奏曲檢索系統。中央大學通訊工程學系碩士學位論文,2013。
[15] E. Keogh, C. A. Ratanamahatana, “Exact indexing of dynamic time warping,” Knowledge and Information Systems, 2004.
[16] Yue Liu, and Hui Liu, and Bofeng Zhang and Gengfeng Wu, “Extraction of if-then rules from trained neural network and its application to earthquake prediction,” Cognitive Informatics, 2004. Proceedings of the Third IEEE International Conference.
[17] T. Kondo, J. Ueno, and S. Takao, “Medical image diagnosis of lung cancer by revised GMDH-type neural network self-selecting optimum neuron architectures,” System Integration (SII), IEEE/SICE International Symposium, 2011.
[18] N. L. D. Khoa, K. Sakakibara, and I. Nishikawa, “Stock Price Forecasting using Back Propagation Neural Networks with Time and Profit Based Adjusted Weight Factors,” SICE-ICASE, International Joint Conference, 2006.
[19] G. E. Hinton, and R. R , Salakhutdinov, “Reducing the dimensionality of data with neural networks,” Science, Vol. 313. no. 5786, pp. 504 - 507, 28 July 2006.
[20] http://www.ling.fju.edu.tw/hearing/brain-into.htm
[21] D. E. Rumelhart, G. E. Hinton, R. J. Williams, “Learning representations by back-propagating errors,” Nature 323 (6088): 533–536, 8 October 1986.
[22] http://www.nature.com/news/computer-science-the-learning-machines-1.14481#/b1
[23] D. H. Ackley, G. E. Hinton, T. J. Sejnowski, “A Learning Algorithm for Boltzmann Machines,” In D. E. Rumelhart, J. L. McClelland, and the PDP Research Group. Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Volume 1: Foundations (Cambridge: MIT Press): 282–317. 1985.
[24] P. Smolensky, Parallel Distributed Processing: Volume 1:Foundations, D. E. Rumelhart, J. L. McClelland, Eds. (MIT Press, Cambridge, 1986), pp. 194–281
[25] A. Mnih, and G. E. Hinton, “Learning Unreliable Constraints using Contrastive Divergence,” In IJCNN 2005, Montreal.
[26] Y. Bengio, P. Lamblin, D. Popovici, H. Larochelle, “Greedy Layer-Wise Training of Deep Networks,” Advances in Neural Information Processing Systems 19, 2007.
[27] G. Casella, E. I. George, “Explaining the Gibbs Sampler,” The American Statistician 46 (3): 167, 1992.
[28] V. Nair, and G. E. Hinton, “3-D Object recognition with deep belief nets,” Advances in Neural Information Processing Systems 22, Y. Bengio, D. Schuurmans, J. lafferty, C. K. I. Williams, and A. Culotta (Eds.), pp 1339-1347.
[29] A. R. Mohamed, G. E. Dahl, and G. E. Hinton, “Deep belief networks for phone recognition,” NIPS 22 workshop on Deep Learning for Speech Recognition.
[30] G. E. Hinton, L. Deng, D. Yu, G. Dahl, A. Mohamed, Navdeep Jaitly, A. Senior, V. Vanhoucke, P. Nguyen, T. Sainath, and B. Kingsbury, “Deep Neural Networks for Acoustic Modeling in Speech Recognition,” IEEE Signal Processing Magazine, November, 2012.
[31] Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, “Gradient-Based Learning Applied to Document Recognition,” Proceedings of the IEEE, vol. 86, no. 11, pp. 2278-2324, Nov. 1998.
[32] I. Mrazova, M. Kukacka, “Hybrid convolutional neural networks,” Industrial Informatics INDIN 2008. 6th IEEE International Conference, 2008.
[33] C. Neubauer, “Evaluation of convolutional neural networks for visual recognition,” IEEE Transactions on Neural Networks, VOL. 9, NO. 4, July 1998
[34] Andrew Ng, “Sparse Autoencoder,” Lecture notes. Deep Learning and Unsupervised Feature Learning, Winter, 2011
[35] Matlab Central, Deep Learning Toolbox,
http://www.mathworks.com/matlabcentral/fileexchange/38310-deep-learning-toolbox
[36] The Covers80 cover song data set,
http://labrosa.ee.columbia.edu/projects/coversongs/covers80/
|