Robust Speaker Modeling for Speaker Verification in Noisy Environments

The present chapter explores robust speaker modeling methods for speaker verification in noisy environment. The focus is specifically laid on building hybrid classifiers based on the combination of generative and discriminative models (e.g., Gaussian Mixture Models (GMMs) and Support Vector Machines (SVMs)). For improving the performance of the proposed speaker verification systems, utterance partitioning methods are used. The discussion is closely followed by state-of-the-art variants of GMM supervector based approaches (i.e., i-vectors) and algorithms for combining robust classifiers.

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