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This paper compares several feature extraction approaches based on Gaussian mixture model (GMM) for support vector machine (SVM) in text-independent speaker verification. Because of excellent scalability, GMM can be used to extract fixed number of typical feature vectors from various length speech data. Experiments with different GMM-based features in SVM speaker verification system were performed...
This paper combines Gaussian mixture model-universal background model (GMM-UBM) and support vector machine (SVM) through post processing the GMM-UBM scores of different dimension feature parameter with SVM in speaker verification. Because different dimension feature makes different contribution to recognition performance and SVM has good discriminability, this combining approach yields significant...
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