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In this paper, a new method called Maximum Likelihood General Regression (MLGR) is introduced for speaker adaptation. Gaussian means of a speaker independent (SI) model are adapted to the data of a new speaker by assuming a non-linear mapping from the SI Gaussian means to the adapted Gaussian means. MLGR performs a non-linear regression between ML estimates of the means and the SI means using General...
In this paper, a new method called Maximum Likelihood Neural Regression (MLNR) is introduced for Rapid Speaker Adaptation (RSA). MLNR, which is conceptually simple, adapts the Gaussian means of a speaker independent (SI) model to the data of a new speaker by assuming a non-linear mapping from the SI Gaussian means to the adapted Gaussian means. It performs a non-linear regression between maximum likelihood...
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