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- W2079728812 abstract "Gaussian Mixture Models (GMMs) are the most widely used technique for voice modeling in automatic speaker recognition systems. In this paper, we introduce a variation of the traditional GMM approach that uses models with variable complexity (resolution). Termed Multi-resolution GMMs (MR-GMMs); this new approach yields more than a 50% reduction in the computational costs associated with proper speaker identification, as compared to the traditional GMM approach. We also explore the noise robustness of the new method by investigating MR-GMM performance under noisy audio conditions using a series of practical identification tests." @default.
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- W2079728812 date "2009-01-01" @default.
- W2079728812 modified "2023-10-16" @default.
- W2079728812 title "Automatic Speaker Recognition with Multi-Resolution Gaussian Mixture Models (MR-GMM)" @default.
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- W2079728812 doi "https://doi.org/10.5769/j200901001" @default.
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