Speech Emotion Recognition using GFCC and BPNN
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2014 by IJETT Journal|
|Year of Publication : 2014|
|Authors : Shaveta Sharma , Parminder Singh
|DOI : 10.14445/22315381/IJETT-V18P265|
Shaveta Sharma , Parminder Singh "Speech Emotion Recognition using GFCC and BPNN", International Journal of Engineering Trends and Technology (IJETT), V18(6),321-322 Dec 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
From the past years, researchers have showed a very interest in the speech recognition systems based on the emotions. Mainly the research has been done with the aim to bring closer both human and computer with each other by recognizing mood swings. In the recognizing process we must know how to represent the emotions on the basis of some features like sad, happy etc. When the verbal content is well recognized on the speaker’s emotion, a promising enhancement of such systems would come. So recognition in speech is a crucial step. In the proposed work speech emotions will be recognized using hybridization of GFCC (Gammatone Frequency Cepstral Coefficients) and BPNN (Back Propagation Neural Network). The whole simulation will be done in the MATLAB environment to check the comparison result.
 J. C. Platt, “Fast Training of Support Vector Machines using Sequential Minimal Optimization”, Advances in Kernel Methods: Support Vector Learning, pp 185–208, 2000.
 Md. Ali Hossain, Md. Mijanur Rahman, Uzzal Kumar Prodhan, Md. Farukuz zaman Khan, “Implementation Of Back-Propagation Neural Network For Isolated Bangla Speech Recognition”, International Journal of Information Sciences and Techniques , vol.3, pp 1-9,2013.
 Raul Rojas, “Neural Networks: A Systematic Introduction. Springer”, 2005.
 Dimitrios Ververidis and Constantine Kotropoulos “Emotional speech recognition:Resources, features, and methods”,Speech Communication 48, pp. 1161-1182,2006.
 John C. Platt, “Sequential Minimal Optimization: A Fast Algorithm for Training Support Vector Machines”, Advances in Neural Information Processing Systems 11, M. S. Kearns, S. A. Solla, D. A. Cohn, eds., MIT Press, 1999.
 Wouter Gevaert, Georgi Tsenov, Valeri Mladenov, “Neural Networks used for Speech Recognition”, Journal of Automatic Control, University of Belgrade, vol. 20:1-7, 2010.
 Mirza Cilimkovic, “Neural Networks and Back Propagation Algorithm”, Institute of Technology Blanchardstown, Blanchardstown Road North Dublin 15, Ireland.
Back Propagation Neural Network, GFCC, Speech Recognition, Emotions.