CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Vocal Indicators of Emotional Stress

by Savita Sondhi, Munna Khan, Ritu Vijay, Ashok K. Salhan
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 15
Year of Publication: 2015
Authors: Savita Sondhi, Munna Khan, Ritu Vijay, Ashok K. Salhan
10.5120/21780-5056

Savita Sondhi, Munna Khan, Ritu Vijay, Ashok K. Salhan . Vocal Indicators of Emotional Stress. International Journal of Computer Applications. 122, 15 ( July 2015), 38-43. DOI=10.5120/21780-5056

@article{ 10.5120/21780-5056,
author = { Savita Sondhi, Munna Khan, Ritu Vijay, Ashok K. Salhan },
title = { Vocal Indicators of Emotional Stress },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 15 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 38-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number15/21780-5056/ },
doi = { 10.5120/21780-5056 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:10:40.556009+05:30
%A Savita Sondhi
%A Munna Khan
%A Ritu Vijay
%A Ashok K. Salhan
%T Vocal Indicators of Emotional Stress
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 15
%P 38-43
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Background: Voice, apart from its semantic content also carries information about the speaker's psychological and physical state. Emotional stress or physical fatigue, are the pathological elements of this condition. The possible relationship between emotional stress and the measurable changes to the voice signal was the subject of this study. Method: Eleven subjects were interviewed with questions from two domains and their responses were recorded. In the first domain, two men, two women and three teenagers were asked to remember an incident from their past where they felt embarrassed or ashamed of their own act. In the second domain, three women and one man from the house keeping staff were interviewed for the stolen mobile phone. These subjects were different from the subjects who participated in domain 1. Stress in voice was detected as a measure of shift in the acoustic parameters with respect to the baseline. All recordings were analyzed using PRAAT software. Spectrograms were also plotted for qualitative comparison between normal speech and stressed speech. Result: Significant increase in mean pitch and substantial decrease in the first two formants (F1 and F2) were observed under stress. Other acoustic measures did undergo change under stress but failed to reveal any significance. Spectrograms were distinct for the two conditions. Conclusion: Obtained results indicate that, when a person is emotionally charged, stress could be discerned in his voice. Mean pitch and Formants F1 and F2 have been obtained as reliable vocal indicators of emotional stress. This study proposes a simple non-invasive approach which can act as an alibi for innocent people.

References
  1. Boersma P, Weenink D, PRAAT: doing phonetics by computer. (v5. 3. 56) 2010. Available from http://www. praat. org/ [Computer program]
  2. Bageshree, V. , Pathak, S. and Panat, A. R. 2012. Extraction of Pitch and Formants and its Analysis to identify 3 different emotional states of a person. International Journal of Computer Science. Vol. 9, No. 4, pp. 296-299.
  3. Cummings, K. E. , and Clements, M. A. 1995. Analysis of the glottal excitation of emotionally styled and stressed speech. Journal of Acoustical Society of America, Vol. 98, pp. 88–98
  4. Costantini, G. , Iaderola, I. , Paoloni, A. and Todisco, M. 2014. EMOVO corpus: an Italian emotional speech database, Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14). European Language Resources Association (ELRA), pp. 3501-3504.
  5. Cosetl, R. C. , and Lopez, D. B. 2011. Voice Stress Detection: A method for stress analysis. Detecting fluctuations on Lippold Microtremor spectrum using FFT. 21st International Conference on Electrical Communications and Computers (CONIELECOMP) IEEE Xplore 2011; 184-189.
  6. Duffy, D. G. 2003. Advanced engineering mathematics with MATLAB, Boca Raton, Fla. Chapman & Hall/CRC, 2nd ed.
  7. Darren, H. , Sharon, W. , Roy, R. , Megan, S. 2002. Investigation and Evaluation of Voice Stress Analysis Technology. The U. S. Department of Justice report (98-LB-VX-A013)
  8. Fielder, K. , and Walka, I. 1993. Training lie detectors to use nonverbal cues instead of global heuristics. Human Communication Research, Vol. 20, No. 2, pp. 199-223.
  9. Hopkins, C. , and Daniel, B. 2005. Evaluation of Voice Stress Analysis Technology. Proceedings of 38th Hawaii International Conference on System Science. IEEE. 2005.
  10. Heisse, J. W. 1976. Audio Stress Analysis—A Validation and Reliability Study of the Psychological Stress Evaluator (PSE). Proceedings of Carnahan Conference on Crime Countermeasures, Lexington, KY, pp. 5-18.
  11. Knapp, M. L. , Hart, R. P. , and Dennis, H. S. 1974. An exploration of deception as a communication construct. Human Communication Research. Vol. 1, pp. 15-29.
  12. Knapp, M. L. and Comadena, M, E. 1979. Telling it like it isn't: A review of theory and research on deceptive communication. Human Communication Research. Vol. 5, pp. 270-285.
  13. Lippold, O. 1971. Physiological Tremor. Scientific American. Vol. 224, No. 3, pp. 65-73.
  14. Ling He; Lech, M. ; Maddage, M. C. ; Allen, N. , 2009. Stress Detection Using Speech Spectrograms and Sigma-pi Neuron Units, Natural Computation, 2009. ICNC '09. Fifth International Conference on, vol. 2, no. , pp. 260-264.
  15. Mohanty, M. N. and Jena, B. 2011. Analysis of stressed human speech. Int. J. Computational Vision and Robotics. Vol. 2, No. 2, pp. 180–187.
  16. Mencattini, A. , Martinelli, E. , Costantini, G. , Todisco, M. , Basile, B. , Bozzali, M. , and Di Natale, C. 2014 'Speech emotion recognition using amplitude modulation parameters and a combined feature selection procedure', Elsevier, Knowledge-Based Systems, Vol. 63, pp. 68–81.
  17. Protopapas, A. , and Liberman, P. 1997. Fundamental frequency of phonation and perceived emotional stress. Journal of Acoustical Society of America. Vol. 101, No. 4, pp. 2267– 2277.
  18. Ruiz, R. , Legros, C. , and Guell A. 1990. Voice Analysis to Predict the Psychological or Physical State of a Speaker. Aviation Space and Environmental Medicine. Vol. 61, No. 3, pp. 266-71
  19. Ruiz, R. , Absil, E. , Harmegnies, B. , and Legros, C. 1996. Time and spectrum-related variability's in stressed speech under laboratory and real conditions. Speech Communication. Vol. 20, pp. 111 - 129
  20. Smith, G. A. 1977. Voice analysis for the measurement of anxiety. British Journal of Medical Psychology. Vol. 50, pp. 367-73
  21. Sigmund, M. 2007. Spectral Analysis of Speech under Stress. ICSNS International Journal of Computer Science and Network Security. Vol. 7, No. 4, pp. 170-72
  22. Sigmund, M. , Prokes, A. and Brabec, Z. 2008. Statistical analysis of glottal pulses in speech under psychological stress. Proceedings of the 16th European Signal Processing Conference (EUSIPCO 2008), August 25-29.
  23. Sigmund, M. 2013. Statistical Analysis of Fundamental Frequency Based Features in Speech under Stress. Information Technology and Control. Vol. 42, No. 3, pp. 286-291.
  24. Salhan, A. , Khan, M. , Sondhi, S. , and Vijay, R. 2012. Online offline voice stress analyzer. Aviation Space and Environmental Medicine. Vol. 83, No. 3, pp. 309.
  25. Sondhi, S. , Khan, M. , Vijay, R. , Salhan, A. , and Vashisth, S. 2012. Real time speech analysis for detection of stress using Autocorrelation function. Proceeding of 11th International Conference on Information Technology and Telecommunication March 29- 30, 2012: 38 – 44 at Cork Institute of Technology, Cork, Ireland.
  26. Scherer, K. R. 2003. Vocal communication of emotion: a review of research paradigms. Speech Comm. Vol. 40, pp. 227–256.
  27. Scherer, K. R. 1986. Voice, Stress and Emotion: In: H. Appley and R. Trumbull, Editors. Dynamics of Stress: Physiological and Psychological Social Perspective. New York: Plenum Press. pp. 157-179.
  28. Scherer, K. R. 2000. The neuropsychology of emotion, chapter Psychological models of emotion. Oxford University Press, Oxford 2000. pp. 137–162.
  29. Scherer, K. R. , Banse, R. , and Wallbott, H. G. 2001. Emotion inferences from vocal expression correlate across languages and cultures. J. Crosscult. Psychol. Vol. 32, pp. 76–92
  30. Streeter, L. A. , Krauss, R. M. , Geller, V. , Olson, C. , and Apple, W. 1977 Pitch changes during attempted deception. Journal of Personality and Social Psychology. Vol. 35, No. 5, pp. 345–350.
  31. Williams, C. E. , and Stevens, K. N. 1972. Emotions and Speech: Some Acoustical Correlates. J. Acoust. Soc. Amer. Vol. 52, pp. 1238-1250.
  32. Warren, J. and Riedel, R. 2004. Emotional Power: tapping the inexhaustible energy of your spirit. Malaysia, Axiom.
  33. Xiao, Y. , Jitsuhiro, T. , Miyajima, C. , Kitaoka, N. , and Takeda, K. 2012. Physical characteristics of vocal folds during speech under stress. Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference, 25-30 March 2012. pp. 4609-4612.
  34. Zhou, G. , Hansen, J. H. L. , and Kaiser, J. F. 2001. Nonlinear Feature based Classification of Speech under Stress. IEEE Trans. On Speech and Audio Processing, Vol. 3, pp. 201-206.
Index Terms

Computer Science
Information Sciences

Keywords

Deception anxiety stress spectrogram mean pitch formants

Powered by PhDFocusTM