Referenced Items are not available for this document.
Speech emotion recognition is a challenging yet important speech technology. In this paper, the GMM supervector based SVM is applied to this field with spectral features. A GMM is trained for each emotional utterance, and the corresponding GMM supervector is used as the input feature for SVM. Experimental results on an emotional speech database demonstrate that the GMM supervector based SVM outperforms standard GMM on speech emotion recognition
Published in:
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
(Volume:4
)
Date of Conference: 15-20 April 2007
- Page(s):
- IV-413 - IV-416
- ISSN :
- 1520-6149
- E-ISBN :
- 1-4244-0728-1
- Print ISBN:
- 1-4244-0727-3
- INSPEC Accession Number:
- 9497596
- Conference Location :
- Honolulu, HI
- Digital Object Identifier :
- 10.1109/ICASSP.2007.366937
- Product Type:
- Conference Publications
About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
