Deep Speaker Vector Normalization with Maximum Gaussianality Training
Deep speaker embedding represents the state-of-the-art technique for speaker recognition. A key problem with this approach is that the resulting deep speaker vectors tend to be irregularly distributed...
In previous research, we proposed a deep normalization approach based on a new discriminative normalization flow (DNF) model, by which the distributions of individual speakers are arguably transformed to homogeneous Gaussians. This normalization was demonstrated to be effective, but despite this remarkable success, we empirically found that the latent codes produced by the DNF model are generally neither homogeneous nor Gaussian, although the model has assumed so. In