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This paper proposes a novel multi-feature fusion approach using Multi-GMM supervector and Support Vector Machine for text-independent speaker verification. By the UBMMAP framework, the variable number of feature vectors (MFCC, LPCC) can be transformed into a vector (GMM supervector). Concatenating the GMM supervectors from different features, a new Multi-GMM supervector is formed for SVM. Experiments...
Based on the experimental data of passenger car driving on the real road in Beijing, the long-time trip is taken as the study object in this paper. The design method of transient driving cycles with non-vanishing endpoints microtrips for passenger car is developed, which overcomes the limitation of the current design method of transient driving cycle. Finally, the passenger car transient driving cycle...
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...
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