Analysis of high-level features for vocal emotion recognition

2011 34th International Conference on Telecommunications and Signal Processing, TSP 2011 - Proceedings

Volumn , Issue , 2011, Pages 361-366

  Atassi, Hicham ^a,b   Esposito, Anna ^c   Smekal, Zdenek ^b  

^a UNIVERSITY OF STIRLING   (United Kingdom)

^b BRNO UNIVERSITY OF TECHNOLOGY   (Czech Republic)

^c SECOND UNIVERSITY OF NAPLES   (Italy)

Author keywords

classification; Emotion recognition; high level features

Indexed keywords

EMOTION CLASSIFICATION; EMOTION RECOGNITION; EMOTIONAL SPEECH; HIGH-LEVEL FEATURES; HUMAN MACHINE INTERACTION;

DATABASE SYSTEMS; SIGNAL PROCESSING; SPEECH ANALYSIS; TELECOMMUNICATION;

FEATURE EXTRACTION;

EID: 80555139634     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/TSP.2011.6043708     Document Type: Conference Paper

References (24)

1. Christian, J., Deeming, A.: Affective Human-Robotic Interaction. Affect and Emotion in Human-Computer Interaction: From Theory to Applications, Christian Peter, Russell Beale, 2008.
2. Sony AIBO Europe, Sony Entertainment, www.sonydigital-link.com/AIBO/.
3. Petrushin, V.: Emotion in Speech: Recognition and Application to Call Centers, Proceedings of the Conference on Artificial Neural Networks in Engineering, pp. 7-10, 1999.
4. Van Bezooijen, R.: The Characteristics and Recognisability of Vocal Expression of Emotions. Drodrecht, The Netherlands, Foris, 1984.
5. Rahurkar, M., Hansen, J. H. L.: Frequency Band Analysis for Stress Detection Using Teager energy Operator Based Feature. In: Proc. Int. Conf. Spoken Language Processing (ICSLP '02), vol. 3, pp. 2021-2024, 2001.
6. Navas E., Hernáez, Luengo I.: An Objective and Subjective Study of the Role of Semantics and Prosodic Features in Building Corpora for Emotional TTS. IEEE Transactions on Audio, Speech, and Language Processing, vol. 14, pp. 1117-1127, 2006.
7. th Int. Conf. Tools with Artificial Intelligence, ICTAI 2008. Dayton, Ohio, USA: IEEE Computer Society, pp. 147-151, 2008.
8. Pudil P., Ferri. F., Novovicova J., Kittler J.: Floating search method for feature selection with non-monotonic criterion functions. Pattern Recognition, vol. 2, pp. 279-283, 1994.
9. Ververidis, D., Kotropoulos, C.: Emotional Speech Recognition: Resources, Features and Methods. Elsevier Speech Communication, vol. 48, no. 9, pp. 1162-1181, 2006.
10. Mehrabian, A.; Russel, J.: An approach to environmental psychology. Cambridge: MIT Press. 1974.
11. Osgood, C.E., Suci J.G., Tannenbaum P.H.: The measurement of meaning. University of Illinois Press: Urbana. 1957.
12. Douglas-Cowie, E., Campbell N., Cowie R., & Roach P. Emotional speech: towards a new generation of databases. Speech communication, 2003.
13. Esposito, A., Riviello, M.T., Di Maio, G.: The COST 2102 Italian Audio and Video Emotional Database. Proceedings of WIRN 2009, May 28-30, Vietri sul Mare, 2009.
14. Nakatsu, R., Solomides, A., Tosa, N., "Emotion recognition and its application to computer agents with spontaneous interactive capabilities". Proc. Int. Conf. Multimedia Computing and Systems (ICMCS '99). Vol. 2. Florence, pp. 804-808, 1999.
15. http://emotion-research.net/wiki/Databases.
16. Burkhardt, F., Paeschke, A., Rolfes, M., Sendlmeier, W., Weiss, B.: A Database of German Emotional Speech, Proceedings of Interspeech, pp. 1517-1520, 2005.
17. Skowronski, M., Harris, J.; Improving the Filterbank of a Classic Speech Feature Extraction Algorithm. IEEE Int. Symposium on Circuits and System, Bangok, pp 281-284, 2003
18. Hermansky, H.: Perceptual Linear Predictive (PLP) Analysis of Speech. Journal of Acoustic Socienty, US, no. 4, pp. 1738-1753, 1990.
19. Mammone J., Xiaoyu Z., Ravi P.: Robust Speaker Recognition: a Feature-based Approach. Vol. 13. IEEE Signal Processing Magazine, 1996.
20. Bong-Wan, K., Dae-Lim, C., Yong-Ju, L.: Speech/Music Discrimination Using Mel-Cepstrum Modulation Energy, Springer Berlin / Heidelberg, pp. 406-414. ISSN 0302-9743, 2007.
21. Sarikaya, R., Hansen, J.H.L: High Resoultion Speech Feature Parameterization for /monophone Based Stressed Speech Recognition. IEEE Signal Processing Letters, 2000.
22. Mporas I., Ganchev T., Siafarikas, M., Fakotakis, N.: Comparison of Speech Features on the Speech Recognition Task. Journal of Computer Science, pp: 608-616, 2007.
23. Peng, H., Long, F., Ding, C.: Feature selection based on mutual information: criteria of max-dependency, max-relevance, and minredundancy. EEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 27, No. 8, pp.1226-1238, 2005.
24. Atassi, H., Riviello, M.T., Smekal, Z. Hussain, A., Esposito, A.: Emotional Vocal Expressions Recognition using the COST 2102 Italian Database of Emotional Speech. Lecture Notes in Computer Science, 2010.