We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Call for Paper
December Edition
IJCA solicits high quality original research papers for the upcoming December edition of the journal. The last date of research paper submission is 20 November 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

SVM Scheme for Speech Emotion Recognition using MFCC Feature

by A.milton, S. Sharmy Roy, S. Tamil Selvi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 9
Year of Publication: 2013
Authors: A.milton, S. Sharmy Roy, S. Tamil Selvi
10.5120/11872-7667

A.milton, S. Sharmy Roy, S. Tamil Selvi . SVM Scheme for Speech Emotion Recognition using MFCC Feature. International Journal of Computer Applications. 69, 9 ( May 2013), 34-39. DOI=10.5120/11872-7667

@article{ 10.5120/11872-7667,
author = { A.milton, S. Sharmy Roy, S. Tamil Selvi },
title = { SVM Scheme for Speech Emotion Recognition using MFCC Feature },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 9 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 34-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number9/11872-7667/ },
doi = { 10.5120/11872-7667 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:29:49.153200+05:30
%A A.milton
%A S. Sharmy Roy
%A S. Tamil Selvi
%T SVM Scheme for Speech Emotion Recognition using MFCC Feature
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 9
%P 34-39
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Emotion recognition from speech has developed as a recent research area in Human–Computer Interaction. The objective of this paper is to use a 3-stage Support Vector Machine classifier to classify seven different emotions present in the Berlin Emotional Database. For the purpose of classification, MFCC features from all the 535 files present in the database are extracted. Nine statistical measurements are performed over these features from each frame of a sentence. The linear and RBF kernels are employed in hierarchical SVM with RBF sigma value equal to one. For training and testing of data, 10-fold cross-validation is used. Performance analysis is done by using the confusion matrix and the accuracy obtained is 68%.

References
  1. Alexander I. Iliev, Michael S. Scordilis, Joao P. Papa and Alexandre X. Falcao, 2010,"Spoken emotion recognition through optimum-path forest classification using glottal features", Computer Speech and Language 24, pp. 445 - 460.
  2. Ashish B. Ingale and Dr. D. S. Chaudhari, 2012, "Speech Emotion Recognition Using Hidden Markov Model and Support Vector Machine", International Journal of Advanced Engineering Research and Studies, Vol. 1, Issue 3.
  3. Bhoomika Panda, Debananda Padhi, Kshamamayee Dash and Prof. Sanghamitra Mohanty, 2012, "Use of SVM Classifier & MFCC in Speech Emotion Recognition System", International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 2, Issue 3.
  4. Bottou L. and Chih-Jen Lin, 2007, "Support Vector Machine Solvers", Dorling Kindersley Publication.
  5. Enrique M. Albornoz, Diego H. Milone and Hugo L. Rufiner, 2011,"Spoken emotion recognition using hierarchical classifiers", Computer Speech and Language 25, pp. 556 –570.
  6. http://www. fon. hum. uva. nl/praat/, Last accessed on 12. 11. 2012.
  7. http://www. expressive-speech. net/, Berlin emotional speech database, Last accessed on 25. 10. 2012.
  8. Iker Luengo, Eva Navas and Inmaculada Hernaez, 2010, "Feature Analysis an Evaluation for Automatic Emotion Identification in Speech", IEEE Transactions on Multimedia, Vol. 12, No. 6, pp. 490 - 501. .
  9. Iker Luengo, Eva Navas, Inmaculada Hernaez and Jon Sanchez, 2005,"Emotion Recognition using Prosodic Parameters", Interspeech, pp. 433 – 442.
  10. Jeong-Sik Park, Ji-Hwan Kim and Yung-Hwan Oh, 2009, "Feature Vector Classification based Speech Emotion Recognition for Service Robots", IEEE Transactions on Consumer Electronics, Vol. 55, No. 3, pp. 1590 – 1596.
  11. Lawrence R. Rabiner and Ronald W. Schafer, 1978, "Digital Processing of Speech Signals", Prentice Hall.
  12. Shashidhar G. Koolagudi and K. Sreenivasa Rao, 2011, "Emotion recognition from speech: a review", Int J Speech Tech, pp. 119 – 128.
  13. Shashidhar G. Koolagudi and K. Sreenivasa Rao, 2012, "Emotion recognition from speech using source, system and prosodic features", Int J Speech Tech, pp. 265 – 289.
  14. Simon Haykin, 1999, "Neural networks: A Comprehensive Foundation", Pearson Education.
  15. Siqing Wu, Tiago H. Falk, Wai-Yip Chan, 2011,"Automatic Speech Emotion Recognition Using Modulation Spectral Features", Speech Communication 53, pp. 768 - 785.
  16. Sujata B. Wankhade, Pritish Tijare and Yashpalsing Chavhan, 2011, "Speech Emotion Recognition System Using SVM AND LIBSVM", International Journal Of Computer Science And Applications, Vol. 4, No. 2.
  17. Tin Lay Nwe, Say Wei Foo, Liyanage C. De Silva, 2003, "Speech Emotion Recognition Using Hidden Markov Models", Speech Communication 41,pp. 603 - 623.
  18. Vaishali M. Chavan, V. V. Gohokar, 2012, "Speech Emotion Recognition by using SVM-Classifier", International Journal of Engineering and Advanced Technology, IJEAT, Vol. 1, Issue 5.
  19. Vibha Tiwari, 2010, "MFCC and its applications in speaker recognition", International Journal on Emerging Technologies, ISSN : 0975-8364.
  20. Vimala. C, Dr. V. Radha, 2011, "Speaker Independent Isolated Speech Recognition System for Tamil Language using HMM", International Conference on Communication Technology and System Design, Speech Communication 46.
  21. Yixiong Pan, Peipei Shen and Liping Shen, 2012, "Speech Emotion Recognition Using Support Vector Machine", International Journal of Smart Home, Vol. 6, No. 2.
  22. Yongjin Wang and Ling Guan, 2008, "Recognizing Human Emotional State from Audiovisual Signals", IEEE Transactions on Multimedia, Vol. 10, No. 5, pp. 936 – 946.
  23. Emily Mower, Maja J Mataric, and Shrikanth Narayanan, 2011, "A Framework for Automatic Human Emotion Classification Using Emotion Profiles", IEEE Transactions on Audio, Speech and Language Processing, Vol. 19, No. 5, pp. 1057 - 1070.
  24. Chung-Hsien Wu and Wei-Bin Liang, 2011, "Emotion Recognition of Affective Speech Based on Multiple Classifiers Using Acoustic-Prosodic Information and Semantic Labels", IEEE Transactions on Affective Computing, Vol. 2, No. 1, pp. 10 - 21.
  25. Moataz El Ayadi, Mohamed S. Kamel, Fakhri Karray, 2011,"Survey on Speech Emotion Recognition: Features, Classification Schemes, and Databases", Pattern Recognition 44, pp. 572 – 587.
  26. Bjorn Schuller, Gerhard Rigoll, and Manfred Lang, 2004,"Speech Emotion Recognition Combining Acoustic Features and Linguistic Information in a Hybrid Support Vector Machine-Belief Network Architecture", IEEE, ICASSP, pp. I – 577 - I – 580.
  27. Cowie. R, 2011,"Emotion Recognition in Human-Computer Interaction", IEEE Signal Processing Magazine, Vol. 18, No. 1, pp. 22-80.
  28. Rabiner, L. R. , & Juang, B. H. , 1993,"Fundamentals of Speech Recognition", Englewood Cliffs, Prentice-Hall.
  29. Hsu C. W, Chang. C, Lin C. J,"A Practical Guide to Support Vector Classification", Technical Report, Department of Computer Science and Information Engineering, National Taiwan University, Taiwan.
  30. Lin. Y, Wei. G, 2005, "Speech Emotion Recognition Based on HMM and SVM", International Conference on Machine Learning and Cybernetics, Vol. 8, pp. 4898-4901.
  31. Han Y, Wang G, Yang Y, 2008, "Speech Emotion Recognition Based on MFCC", Journal of Chong Qing University of Posts and Telecommunication, Natural Science Edition 20(5).
Index Terms

Computer Science
Information Sciences

Keywords

Speech Emotion Recognition MFCC SVM RBF Linear Kernel

Powered by PhDFocusTM