|| L. Rabiner and B. H. Juang, “Fundamentals of Speech Recognition,” Prentice Hall, vol.103, 1993.|
 J. P. Campbell and JR., “Speaker recognition: a tutorial,” Proceedings of the IEEE, vol.85, pp. 1437 – 1462, 1997
 C. H. Wu and J. H. Chen, “Speech activated telephony email reader (SATER) based on speaker verification and text-to-speech conversion,” IEEE Transactions on Consumer Electronics, vol.43, pp. 707-716, 1997.
 T. Jacobs and A. Setlur, “A field study of performance improvements in HMM-based speaker verification,” Second IEEE Workshop on Interactive Voice Technology for Telecommunications Applications, pp.121-124, 1994.
 D. Burton, “Text-dependent speaker verification using vector quantization source coding,” IEEE Transactions on Acoustics, Speech and Signal Processing, vol.35, pp.133-143, 1987.
 H. Gish and M. Schmidt, “Text-independent speaker identification,” IEEE Signal Processing Magazine, vol.11, pp. 18-32, 1994.
 R. C. Eberhart and Y. Shi, “Particle swarm optimization: developments, applications and resources,” Proceedings of the 2001 Congress on Evolutionary Computation, vol.1, pp. 81-86, 2001.
 C. Y. Chen and F. Ye, “Particle swarm optimization algorithm and its application to clustering analysis,” IEEE International Conference on Networking, Sensing and Control, vol.2 , pp. 789 – 794, 2004.
 L. Xiao and Z. Shao and G. Liu, “K-means Algorithm Based on Particle Swarm Optimization Algorithm for Anomaly Intrusion Detection,” The Sixth World Congress on Intelligent Control and Automation, vol.2, pp. 5854 – 5858, 2006.
 M. S. Kim and I. H. Yang and H. J. Yu, “Maximizing Distance between GMMs for Speaker Verification Using Particle Swarm Optimization,” Fourth International Conference on Natural Computation, vol.6, pp. 175 – 178, 2008.
 Y. Liu, “A particle swarm optimization algorithm for Mandarin speech recognition,” Asia-Pacific Conference on Computational Intelligence and Industrial Applications, vol.2, pp. 205-208, 2009.
 R. Saeidi and H. R. S. Mohammadi and T. Ganchev and R. D. Rodman, “Particle Swarm Optimization for Sorted Adapted Gaussian Mixture Models,” IEEE Transactions on Audio, Speech, and Language Processing, vol.17, pp.344-353, 2009
 S. W. Lin and K. C. Ying and S. C. Chen and Z. J. Lee, “Particle swarm optimization for parameter determination and feature selection of support vector machines,” Expert Systems with Applications, vol.35, 2008.
 N. M. Nasrabadi and R. A. King, “Image coding using vector quantization: a review,” IEEE Transactions on Communications, vol.36, pp.957-971, 1988.
 J. Makhoul and S. Roucos and H. Gish, “Vector quantization in speech coding,” Proceedings of the IEEE, vol.73, pp. 1551-1588, 1985.
 V. Delport and M. Koschorreck, “Genetic algorithm for codebook design in vector quantisation,” Electronics Letters, vol.31, pp. 84-85, 1995.
 V. Delport and D. Liesch, “Fuzzy-c-mean algorithm for codebook design in vector quantisation,” ectronics Letters, vol. 30, pp. 1025-1026, 1994.
 M. H. Horng and T. W. Jiang, “The codebook design of image vector quantization based on the firefly algorithm,” Proceedings of the Second international conference on Computational collective intelligence, vol.3, 2010.
 M. H. Horng and T. W. Jiang, “Image vector quantization algorithm via honey bee mating optimization,” Expert Systems with Applications, vol. 38, pp. 1382-1392, 2011.
 L. S. Tue and A. Hegde and D. Erdogmus and J. C. Principe, “Vector quantization using information theoretic concepts,” Natural Computing: an international journal, vol. 4, pp.39-51, 2005.
 V. Wan and W. M. Campbell, “Support vector machines for speaker verification and identification,” Proceedings of Neural Networks for Signal Processing X, vol.2, pp. 775-784, 2000.
 W. M. Campbell and J. P. Campbell and D. A. Reynolds and E. Singer and P. A. T. Carrasquillo, “Support vector machines for speaker and language recognition,” Computer Speech & Language, vol.20, pp. 210-229, 2006.
 T. Jaakkola and D. Haussler, “Exploiting generative models in discriminative classifiers,” Proceedings of the 1998 conference on Advances in neural information, pp.487-493, 1999.
 W. M. Campbell and D. E. Sturim and D. A. Reynolds, “Support vector machines using GMM supervectors for speaker verification,” IEEE Signal Processing Letters, vol.13, pp. 308-311, 2006.
 Z. N. Karam and W. M. Campbell, “A multi-class MLLR kernel for SVM speaker recognition,” IEEE International Conference on Acoustics, Speech and Signal Processing, PP. 4117-4120, 2008.
 J. S Park and J. H. Kim and Y. H. Oh, “Feature vector classification based speech emotion recognition for service robots,” IEEE Transactions on Consumer Electronics, vol.55, pp. 1590-1596, 2009.
 J. Kennedy and R. Eberhart, “Particle swarm optimization,” IEEE International Conference on Neural Networks, vol.4, pp. 1942-1948, 1995.
 Y. Shi and R. Eberhart, “A modified particle swarm optimizer,” The 1998 IEEE International Conference on Evolutionary Computation Proceedings, pp. 69-73, 1998.
 Y. Shi and R. Eberhart, “Parameter Selection in Particle Swarm Optimization,” Proceedings of the 7th International Conference on Evolutionary Programming VII, 1998.
 R. Gray, “Vector quantization,” IEEE ASSP Magazine, vol.1, pp.4-29, 1984.
 D. Lee and S. Baek and K. Sung, “Modified K-means algorithm for vector quantizer design,” IEEE Signal Processing Letters, vol.4, pp.2-4, 1997.
 Y. Linde and A. Buzo and R. Gray, “An Algorithm for Vector Quantizer Design,” IEEE Transactions on Communications, vol.28, pp.84-95, 1980.
 M. A. Hearst and S. T Dumais and E. Osman and J. Platt and B. Scholkopf, “Support vector machines,” IEEE Intelligent Systems and their Applications, vol.13, pp.18-28, 1998.
 M. Kaumann, “Transductive Inference for Text Classification using Support Vector Machines,” Proceedings of the Sixteenth International Conference on Machine Learning, pp.200-209, 1999.
 S. Tong and E. Chang, “Support vector machine active learning for image retrieval,” Proceedings of the ninth ACM international conference on Multimedia, 2001.
 D. Zhang and W. S. Lee, “Web taxonomy integration using support vector machines,” Proceedings of the 13th international conference on World Wide Web, 2004.
 E. N. Issam and Y. Yang and M. N. Wernick and N. P. Galatsanos and R. M. Nishikawa, “A support vector machine approach for detection of microcalcifications,” IEEE Transactions on Medical Imaging, vol.21, pp. 1552 – 1563, 2002.
 M. Pardo and G. Sberveglieri, “Classification of electronicnose data with support vector machines,” Sensors and Actuators B: Chemical , vol.107, pp.730-737, 2005.
 C. W. Hsu and C. C. Chang and C. J. Lin, “A Practical Guide to Support Vector Classification,” Department of Computer Science National Taiwan University, vol.1, pp.1-16, 2010.
 C. C. Chang and C. J. Lin, “LIBSVM: a library for support vector machines,” Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm/.
 C. C. Chang and C. J. Lin, “LIBSVM: A library for support vector machines,” ACM Transactions on Intelligent Systems and Technology, vol.2, 2011.
 The NIST Year 2001 Speaker Recognition Evaluation, Available at http://www.itl.nist.gov/iad/mig/tests/sre/2001/index.html.
 A. Martin and G. Doddington and T. Kamm and M. Ordowski and M. Przybocki, “The DET curve in assessment of detection task performance,” Proceeding of European Conference on Speech Communication and Technology, pp. 1895-1898, 1997.