Abstract
References
1.Z. Fu, G. Lu, K.M. Ting, and D. Zhang, “A survey of audio-based music classification and annotation,” IEEE Trans. Multimedia 13, 303-319 (2011). 2.M. Casey, R. Veltkamp, M. Goto, M. Leman, C. Rhodes, and M. Slaney, “Content-based music information retrieval: current directions and future challenges,” Proceedings of the IEEE 96, 668-696 (2008). 3.J. Seo, “A robust audio fingerprinting method based on segmentation boundaries” (in Korean) J. Acoust. Soc. Kr. 31, 260-265 (2012). 4.C. Park, M. Park, S. Kim, and H. Kim, “Music identification using pitch histogram and MFCC-VQ dynamic pattern” (in Korean), J. Acoust. Soc. Kr. 24, 178-185 (2005). 5.G. Tzanetakis and P. Cook, “Musical genre classification of audio signals,” IEEE Trans. Speech and Audio Process. 10 , 293-302 (2002). 6.J. Seo, “A musical genre classification method based on the octave-band order statistics” (in Korean), J. Acoust. Soc. Kr. 33, 81-86 (2014). 7.B. Logan and A. Salomon, “A music similarity function based on signal analysis,” in Proc. ICME-2001, 745-748 (2001). 8.C. Cao and M. Li, “Thinkit’s submissions for MIREX2009 audio music classification and similarity tasks,” in Mirex abstracts of ISMIR-2009, (2009). 9.C. Charbuillet, D. Tardieu, and G. Peeters, “GMM supervector for content based music similarity,” in Proc. DAFx-11, 425-428 (2011). 10.J. Seo, “A music similarity function based on the centroid model,” IEICE Trans. Information and Systems 96, 1573- 1576 (2013). 11.D. A. Reynolds, T. F. Quatieri, and R. B. Dunn, “Speaker verification using adapted Gaussian mixture models,” Digital Signal Processing 10, 19-41 (2000). 12.W. M. Campbell, D. E. Sturim, and D. A. Reynolds, “Support vector machines using GMM supervectors for speaker verification,” IEEE Signal Processing Letters 13, 308-311 (2006). 13.F. Liese and I. Vajda, “On divergences and informations in statistics and information theory,” IEEE Trans. Information Theory 52, 4394-4412 (2006). 15.M. Gil, F. Alajaji, and T. Linder, “Renyi divergence measures for commonly used univariate continuous distributions,” Information Sciences 249, 124-131 (2013). 16.A. Renyi, “On measures of entropy and information,” in Proc. Berkeley Symp. Probability Theory and Mathematical Statist., 547-561 (1961). 17.T. V. Erven and P. Harremoes, “Renyi divergence and Kullback-Leibler divergence,” IEEE Trans. Information Theory 60, 3797-3820 (2014). 18.V. Hautamaki, T. Kinnunen, I. Karkkainen, J. Saastamoinen, M. Tuononen, and P. Franti, “Maximum a posteriori adaptation of the centroid model for speaker verification,” IEEE Signal Process. Letters 15 , 162-165 (2008). 19.J. Seo, “A speaker change detection method based on a weighted distance measure over the centroid model,” IEICE Trans. Information and Systems 95, 1543-1546 (2012). 20.F. Alajaji, P. N. Chen, and Z. Rached, “Csiszar’s cutoff rates for the general hypothesis testing problem,” IEEE Trans. Information Theory 50, 663-678 (2004). 21.P. Harremoes, “Interpretations of Renyi entropies and divergences,” Physica A: Statistical Mechanics and its Applications 365, 57-62 (2006). 22.A. O. Hero, B. Ma, O. Michel, and J. Gorman, “Alpha- divergence for classification, indexing and retrieval,” Tech. rep., University of Michigan, (2001).
Information
- Publisher :The Acoustical Society of Korea
- Publisher(Ko) :한국음향학회
- Journal Title :The Journal of the Acoustical Society of Korea
- Journal Title(Ko) :한국음향학회지
- Volume : 35
- No :2
- Pages :83-91
- Received Date : 2015-08-20
- Revised Date : 2015-11-02
- Accepted Date : 2015-12-18
- DOI :https://doi.org/10.7776/ASK.2016.35.2.083



The Journal of the Acoustical Society of Korea









