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ICASSP
2011
IEEE
13 years 13 days ago
Effective background data selection in SVM speaker recognition for unseen test environment: More is not always better
This study focuses on determining a procedure to select effective negative examples for development of improved Support Vector Machine (SVM) based speaker recognition. Selection o...
Jun-Won Suh, Yun Lei, Wooil Kim, John H. L. Hansen
BIOSIG
2003
145views Biometrics» more  BIOSIG 2003»
13 years 10 months ago
Pass Phrase Based Speaker Recognition for Authentication
: Speaker recognition in applications of our daily lives is not yet in widespread use. In order for biometric technology to make sense for real-world authentication applications an...
Heinz Hertlein, Robert Frischholz, Elmar Nöth
ICASSP
2011
IEEE
13 years 13 days ago
Soft frame margin estimation of Gaussian Mixture Models for speaker recognition with sparse training data
—Discriminative Training (DT) methods for acoustic modeling, such as MMI, MCE, and SVM, have been proved effective in speaker recognition. In this paper we propose a DT method fo...
Yan Yin, Qi Li
ICPR
2010
IEEE
14 years 3 months ago
Dimension-Decoupled Gaussian Mixture Model for Short Utterance Speaker Recognition
The Gaussian Mixture Model (GMM) is often used in conjunction with Mel-frequency cepstral coefficient (MFCC) feature vectors for speaker recognition. A great challenge is to use ...
Thilo Stadelmann, Bernd Freisleben
ICASSP
2008
IEEE
14 years 3 months ago
A multi-class MLLR kernel for SVM speaker recognition
Speaker recognition using support vector machines (SVMs) with features derived from generative models has been shown to perform well. Typically, a universal background model (UBM)...
Zahi N. Karam, William M. Campbell