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A new strategy of feature classification method for speaker recognition based on the grid-density clustering is presented. According to the concept of density-based and grid-distance-based distribution in the Mel-frequency cepstrum domain, the feature vectors of each speaker were self-adaptively classified into L clusters with less overlapped. With these convex and non-interwoven clusters, the Gaussian...
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selection, feature transformation (or feature projection) and projected clustering. Being widely used in many applications, these methods aim to capture global patterns and are typically performed in the full feature space. In...
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