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Support vector machine (SVM) has been shown powerful in binary classification problems. In order to accommodate SVM to speaker verification problem, the concept of sequence kernel has been developed, which maps variable-length speech data into fixed-dimension vectors. However, constructing a suitable sequence kernel for speaker verification is still an issue. In this paper, we propose a new sequence...
Speaker verification can be viewed as a task of modeling and testing two hypotheses: the null hypothesis and the alternative hypothesis. Since the alternative hypothesis involves unknown impostors, it is usually hard to characterize apriori. In this paper, we propose improving the characterization of the alternative hypothesis by designing two decision functions based, respectively, on a weighted...
Real-word applications often involve a binary hypothesis testing problem with one of the two hypotheses ill-defined and hard to be characterized precisely by a single measure. In this paper, we develop a framework that integrates multiple hypothesis testing measures into a unified decision basis, and apply kernel-based classification techniques, namely, kernel Fisher discriminant (KFD) and support...
This paper presents an effective method to combine speech recognition, speaker verification and face verification for biometric authentication. Our method provides a light-weight enrollment process and an easy-to-use verification interface. A multi-face/single-sentence strategy is used to combine voice and face verification modules, and support vector machine is employed for information fusion. Experimental...
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