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The Scientific World Journal
Volume 2015, Article ID 573068, 7 pages
http://dx.doi.org/10.1155/2015/573068
Research Article

Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

Department of Telecommunications, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70833 Ostrava, Czech Republic

Received 27 August 2014; Accepted 27 October 2014

Academic Editor: Ivan Zelinka

Copyright © 2015 Pavol Partila et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [7 citations]

The following is the list of published articles that have cited the current article.

  • Shajini Majuran, and Amirthalingam Ramanan, “A feature-driven hierarchical classification approach to emotions in speeches using SVMs,” 2017 IEEE International Conference on Industrial and Information Systems (ICIIS), pp. 1–5, . View at Publisher · View at Google Scholar
  • Suneet Narula Garg, Renu Vig, and Savita Gupta, “Feature selection using soft computing algorithms in biometrics,” 2017 International Conference on Inventive Systems and Control (ICISC), pp. 1–5, . View at Publisher · View at Google Scholar
  • Pankaj Shegokar, and Pradip Sircar, “Continuous wavelet transform based speech emotion recognition,” 2016 10th International Conference on Signal Processing and Communication Systems (ICSPCS), pp. 1–8, . View at Publisher · View at Google Scholar
  • M Faurholt-Jepsen, J Busk, M Frost, M Vinberg, E M Christensen, O Winther, J E Bardram, and L V Kessing, “Voice analysis as an objective state marker in bipolar disorder,” Translational Psychiatry, vol. 6, no. 7, pp. e856, 2016. View at Publisher · View at Google Scholar
  • Miroslav Voznak, Dominik Uhrin, Jaromir Tovarek, Pavol Partila, Jan Rozhon, Jan Skapa, and Zdenka Chmelikova, “Optimization of multilayer neural network parameters for speaker recognition,” Proceedings of SPIE - The International Society for Optical Engineering, vol. 9850, 2016. View at Publisher · View at Google Scholar
  • Miroslav Voznak, Pavol Partila, and Jaromir Tovarek, “Self-organizing map classifier for stressed speech recognition,” Proceedings of SPIE - The International Society for Optical Engineering, vol. 9850, 2016. View at Publisher · View at Google Scholar
  • Sai Prasad Potharaju, and Sreedevi, “A novel clustering based candidate feature selection framework using correlation coefficient for improving classification performance,” Journal of Engineering Science and Technology Review, vol. 10, no. 6, pp. 38–43, 2017. View at Publisher · View at Google Scholar