We propose novel deep speaker representation learning that considers perceptual similarity among speakers for multi-speaker generative modeling. Following its success in accurate discriminative modeling of individuality, knowledge (i.e., using neural networks) has been introduced to However, the conventional algorithm does not necessarily learn embeddings suitable such modeling, which may resul...

Speaker verification system has gained great popularity in recent years, especially with the development of deep neural networks and Internet Things. However, security speaker based on not been well investigated. In this paper, we propose an attack to spoof state-of-the-art generalized end-to-end (GE2E) loss function for misclassifying illegal users into authentic user. Specifically, design a n...