Emotion Detection Using MFCC and Cepstrum Features
Author:
Publisher
Elsevier BV
Subject
General Engineering
Reference6 articles.
1. Bedoya-Jaramillo, E. Belalcazar-Bolanos, T. Villa-Canas, J.R. Orozco-Arroyave, J.D. AriasLondono, J.F. Varagas-Bonnilla “Automatic Emotion detection in Speech using Mel frequency Cepstral Coefficients”, XV Simposio De Tratamiento De Senales, Images, Vision, Artificial-STSIVA 2012.
2. FirozShah. A, Vimal Krishnan V.R., RajiSukumar. A, AthulyaJayakumar, BabuAnto. P “Speaker Independent Automatic Emotion Recognition from Speech:-A Comparison of MFCCs and Discrete Wavelet Transforms” 2009 International Conference on Advances in Recent Technologies in Communication and Computing, pp:528-531,2009.
3. K.V. Krishna Kishore, P. Krishna Satish “Emotion Recognition in Speech using MFCC and Wavelet Features”, 3rd IEEE International Advance Computing Conference.
4. Inma Mohino-Herranz1, Roberto Gil-Pita1, Sagrario Alonso-Diaz2 and Manuel Rosa-Zurera1 “MFCC Based Enlargement of the Training set for Emotion Recognition in Speech” International Journal (SIPIJ) Vol.5, No.1, February 2014.
5. J. SirishaDevi, Dr. Srinivas Yarramalle,Siva Prasad Nandyala “Speaker Emotion Recognition Based on Speech Features and Classification Techniques” I.J. Image, Graphics and Signal Processing, 2014, No:7, pp: 61-77, June 2014.
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