Stress and emotion classification using jitter and shimmer features

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 4, Issue , 2007, Pages 1081-1084

  Xi, Li ^a   Jidong, Tao ^a   Johnson, Michael T ^a   Solds, Joseph ^b   Savage, Anne ^b   Leong, Kirsten M ^c   Newman, John D ^d  

^a MARQUETTE UNIVERSITY   (United States)

^b DISNEY S ANIMAL KINGDOM   (United States)

^c Department of Obstetrics Gynecology   (United States)

^d NATIONAL INSTITUTES OF HEALTH   (United States)

Author keywords

GFCC; HMM; Jitter; MFCC; Shimmer

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA REDUCTION; FREQUENCY ESTIMATION; JITTER; MATHEMATICAL MODELS; SPEECH INTELLIGIBILITY;

EMOTION CLASSIFICATION; MEL-FREQUENCY CEPSTRAL COEFFICIENTS (MFCC); SHIMMER FEATURES; SPEECH FEATURES;

GESTURE RECOGNITION;

EID: 34547504420     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2007.367261     Document Type: Conference Paper

References (14)

1. J. H. L. Hansen, "Analysis and compensation of speech under stress and noise for environmental robustness in speech recognition," Speech Communications, Special Issue on Speech Under Stress, vol. 20(2). pp. 151-170, November 1996.
2. S. Bou-Ghazale and J. H. L. Hansen. "A novel training approach for improving speech recognition under adverse stressful environments," EUROSPEECH-97, vol. 5, pp. 2387-2390, Sept. 1997.
3. S. Bou-Ghazale and J. H. L. Hansen, "A Comparative Study of Traditional and Newly Proposed Features for Recognition of Speech Under Stress," IEEE Transactions on Speech and Audio Processing, vol. 8(4), pp. 429-442, July 2000.
4. J. Soltis, K. M. Leong, and A. Savage, "African elephant vocal communication II: rumble variation reflects the individual identity and emotional state of callers," Animal Behaviour, vol. 70, pp. 589-599, 2005.
5. A. Nogueiras, A. Moreno, A. Bonafante, and J. Maririo, "Speech Emotion Recognition Using Hidden Markov Models," Eurospeech 2001, Poster Proceedings, pp. 2679-2682, 2001.
6. K. Oh-Wook, C. Kwokleung, H. Jiucang, and L. Te-Won, "Emotion Recognition by Speech Signals," presented at Eurospeech, Geneva, 2003.
7. B. F. Fuller, Y. Horii, and D. A. Conner, "Validity and reliability of nonverbal voice measures as indicators of stressor-provoked anxiety," Research in Nurse & Health, vol. 15(5), pp. 379-389, Oct. 1992.
8. X. Huang, A. Acero, and H.-W. Hon, Spoken Language Processing. Upper Saddle River, New Jersey: Prentice Hall, 2001.
9. D. D. Greenwood, "Critical bandwidth and the frequency coordinates of the basilar membrane," The Journal of the Acoustical Society of America, vol. 33. pp. 1344-1356, 1961.
10. P. J. Clemins, M. B. Trawicki, K. Adi, J. Tao, and M. T. Johnson, "Generalized perceptual features for vocalization analysis across multiple species," Proceedings of the IEEE ICASSP, vol. 1, pp. 1253 -1256, May 2006.
11. P. Loizou, "COLEA: A MATLAB software tool for speech analysis." Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX, 1999.
12. J. H. L. Hansen, S. E. Bou-Ghazale, R. Sarikaya, and B. Pellom, "Getting Started with the SUSAS: Speech Under Simulated and Actual Stress Database," Robust Speech Processing Laboratory April 15, 1998.
13. K. M. Leong, A. Ortolani, K. D. Burks, J. D. Mellen, and A. Savage, "Quantifying acoustic and temporal characteristics of vocalizations of a group of captive African elephants (Loxodonta africana)," Bioacoustics, vol. 13, pp. 213-231, 2003.
14. S. Young, et al., the HTK Book (for HTK Version 3.2.1), 2002.