A hierarchical framework for speech emotion recognition

IEEE International Symposium on Industrial Electronics

Volumn 1, Issue , 2006, Pages 515-519

  You, Mingyu ^a   Chen, Chun ^a   Bu, Jiajun ^a   Liu, Jia ^a   Tao, Jianhua ^b  

^a ZHEJIANG UNIVERSITY   (China)

^b INSTITUTE OF AUTOMATION   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DISCRIMINANT ANALYSIS; FACE RECOGNITION; FEATURE EXTRACTION; INDUSTRIAL ELECTRONICS; PATTERN RECOGNITION; SPEECH RECOGNITION;

DIMENSIONALITY REDUCTION; INTERNATIONAL SYMPOSIUM; LINEAR DISCRIMINANT ANALYSISLDA); OVERALL PERFORMANCE; PRINCIPAL COMPONENTS; SPEECH EMOTION RECOGNITION;

PRINCIPAL COMPONENT ANALYSIS;

EID: 44349117651     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISIE.2006.295649     Document Type: Conference Paper

References (9)

1. D. Ververidis, C. Kotropoulos, and I. Pitas, "Automatic emotional speech classification," Pro. IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 1, pp. 593-596, May 2004.
2. W. Zhao, R. Chellappa, and A. Krishnaswamy, "Discriminant analysis of principal components for face recognition," Proc. the 3rd IEEE International Conference on Automatic Face and Gesture Recognition, vol. 1, pp. 336-341, April 1998.
3. C. M. Lee, S. S. Narayanan, and R. Pieraccini, "Classifying emotions in human-machine spoken dialogs," Proc. IEEE International Conference on Multimedia and Expo, vol. 1, pp. 737-740, Auguest 2002.
4. J. R. Beveridge, K. She, B. Draper, and G. H. Givens, "A nonparametric statistical comparison of principal component and linear discriminant subspaces for face recognition," Proc. IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 535-542, December 2001.
5. X. Wang and K. K. Paliwal, "Using minimum classification error training in dimensionality reduction," Proc. IEEE Signal Processing Society Workshop on Neural Networks for Signal Processing, vol. 1, pp. 338-345, December 2000.
6. Z. J. Chuang and C. H. Wu, "Emotion recognition using acoustic features and textual content," Proc. IEEE International Conference on Multimedia and Expo, vol. 1, pp. 53-56, June 2004.
7. N. Cristianini and J. Shawe-Taylor, An Introduction To Support Vector Machines, Cambridge University Press, 2000.
8. J. Duchene and S. Leclercq, "An optimal transformation for discriminant principal component analysis," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 10, No.6, November 1988.
9. K. Delac, M. Grgic, and S. Grgic, "A comparative study of pea, ica and Ida," Proc. the 5th EURASIP Conference focused on Speech and Image Processing, Multimedia Communications and Services, vol. 1, pp. 99-106, June 2005.