Kernel principal component analysis
Advances in kernel methods
Mixtures of probabilistic principal component analyzers
Neural Computation
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
A tutorial on text-independent speaker verification
EURASIP Journal on Applied Signal Processing
Journal of Cognitive Neuroscience
IEEE Transactions on Audio, Speech, and Language Processing
Analysis of Feature Extraction and Channel Compensation in a GMM Speaker Recognition System
IEEE Transactions on Audio, Speech, and Language Processing
Speaker Verification Using Support Vector Machines and High-Level Features
IEEE Transactions on Audio, Speech, and Language Processing
Compensation of Nuisance Factors for Speaker and Language Recognition
IEEE Transactions on Audio, Speech, and Language Processing
Modeling Prosodic Features With Joint Factor Analysis for Speaker Verification
IEEE Transactions on Audio, Speech, and Language Processing
State-of-the-Art Performance in Text-Independent Speaker Verification Through Open-Source Software
IEEE Transactions on Audio, Speech, and Language Processing
NIST Speaker Recognition Evaluations Utilizing the Mixer Corpora—2004, 2005, 2006
IEEE Transactions on Audio, Speech, and Language Processing
Speaker Recognition With Session Variability Normalization Based on MLLR Adaptation Transforms
IEEE Transactions on Audio, Speech, and Language Processing
Joint Factor Analysis Versus Eigenchannels in Speaker Recognition
IEEE Transactions on Audio, Speech, and Language Processing
Speaker and Session Variability in GMM-Based Speaker Verification
IEEE Transactions on Audio, Speech, and Language Processing
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
The complete gabor-fisher classifier for robust face recognition
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
Influence of the speech quality in telephony on the automated speaker recognition
CISST '11 Proceedings of the 5th WSEAS international conference on Circuits, systems, signal and telecommunications
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We propose a way of integrating likelihood ratio (LR) decision criterion with nuisance attribute projection (NAP) for Gaussian mixture model- (GMM-) based speaker verification. The experiments on the core test of the NIST speaker recognition evaluation (SRE) 2005 data show that the performance of the proposed approach is comparable to that of the standard approach of NAP which uses support vector machines (SVMs) as a decision criterion. Furthermore, we demonstrate that the two criteria provide complementary information that can significantly improve the verification performance if a score-level fusion of both approaches is carried out.