CFP last date
15 May 2024
Reseach Article


Published on November 2013 by Akshay S. Utane, S. L. Nalbalwar
2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
Foundation of Computer Science USA
NCIPET - Number 1
November 2013
Authors: Akshay S. Utane, S. L. Nalbalwar

Akshay S. Utane, S. L. Nalbalwar . EMOTION RECOGNITION through SPEECH. 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013). NCIPET, 1 (November 2013), 0-0.

author = { Akshay S. Utane, S. L. Nalbalwar },
journal = { 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013) },
issue_date = { November 2013 },
volume = { NCIPET },
number = { 1 },
month = { November },
year = { 2013 },
issn = 2249-0868,
pages = { 0-0 },
numpages = 1,
url = { /proceedings/ncipet/number1/546-1306/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Proceeding Article
%1 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
%A Akshay S. Utane
%A S. L. Nalbalwar
%J 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
%@ 2249-0868
%N 1
%P 0-0
%D 2013
%I International Journal of Applied Information Systems

In last two decades automatic emotion recognition based on speech become wide area of research for human-machine communication. Many systems has been implemented to recognize emotion in speech signals. In this paper previously implemented speech emotion recognition systems has been reviewed using various types of classifiers. The classifiers used to distinguish emotions such as neutral ,surprise ,anger ,happy, sad, fearful, disgust ,etc. emotional speech samples are used as database for emotion recognition from speech and extracted features from speech samples are prosodic and spectral features such as pitch, energy, formants, speech rate ,(MFCC) Mel frequency cepstrum coefficient and linear prediction cepstrum coefficient (LPCC). the performance of classifiers represented by extracted features. Advantages and performance of speech emotion recognition system using different types of classifiers are also discussed.

  1. M. E. Ayadi , M. S. Kamel , F. Karray, "Survey on Speech Emotion Recognition: Features, Classification Schemes, And Databases", Pattern Recognition 44, PP. 572-587, 2011.
  2. I. Chiriacescu , "Automatic Emotion Analysis Based On Speech" , M. Sc. THESIS Delft University of Technology, 2009.
  3. Nitin Thapliyal , Gargi Amoli "Speech based Emotion Recognition with Gaussian Mixture Model" international Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012
  4. T. Vogt, E. Andre and J. Wagner, "Automatic Recognition of Emotions from Speech: A review of the literature and Recommendations for practical realization", LNCS 4868, PP. 75-91, 2008.
  5. S. Emerich, E. Lupu, A. Apatean, "Emotions Recognitions by Speech and Facial Expressions Analysis", 17th European Signal Processing Conference, 2009.
  6. Shashidhar G. Koolagudi, K. Sreenivasa Rao "Emotion recognition from speech: a review" Int Journal of Speech Technol (2012).
  7. Chung-Hsien Wu, and Wei-Bin Liang "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, JANUARY-MARCH 2011.
  8. A. Nogueiras, A. Moreno, A. Bonafonte, Jose B. Marino, "Speech Emotion Recognition Using Hidden Markov Model", Eurospeech, 2001.
  9. P. Shen, Z. Changjun, X. Chen, "Automatic Speech Emotion Recognition Using Support Vector Machine", International Conference On Electronic And Mechanical Engineering And Information Technology, 2011.
  10. D. Ververidis and C. Kotropoulos, "Emotional Speech Recognition: Resources, Features and Methods", Elsevier Speech communication, vol. 48, no. 9, pp. 1162-1181, September, 2006.
  11. Z. Ciota, "Feature Extraction of Spoken Dialogs for Emotion Detection", ICSP, 2006.
  12. E. Bozkurt, E, Erzin, C. E. Erdem, A. Tanju Erdem, "Formant Position Based Weighted Spectral Features for Emotion Recognition", Science Direct Speech Communication, 2011.
  13. C. M. Lee, S. S. Narayanan, "Towards detecting emotions in spoken dialogs", IEEE transactions on speech and audio processing, Vol. 13, No. 2, March 2005.
  14. Yu Zhou , Yanqing Sun , Jianping Zhang and Yonghong Yan ,"Speech emotion recognition using both spectral and prosodic features" ieee conference 19-20 dec 2009 published in information engineering & computer science.
  15. Mohammad H. sedaaghi , Constantine Kotropoulos and Dimitrios Ververidis " Using Adaptive Genetic Algorithms To Improve Speech Emotion Recognition " ieee conference 2007.
Index Terms

Computer Science
Information Sciences


Emotion recognition Feature extraction Feature Selection spectral features prosodic features Classifier.