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In speaker verification task requires some sort of background model for the system to make decision. Most of the cases, a speaker independent large Gaussian Universal Background Model (GMM-UBM) is used. In this paper, the authors propose to use a Speaker Cluster-wise UBM (SC-UBM) for a group of target speakers. In this method, the target speakers are clustered into group based on their similarity in Vocal Tract Length Normalization (VTLN) parameter. The VTLN parameter depends on the physiological structure of human speech production system.
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