Speaker recognition is a task of identifying persons from their voices. Recently, deep
learning has dramatically revolutionized speaker recognition. However, there is lack of …

In the recent past, deep learning methods have demonstrated remarkable success for
supervised learning tasks in multiple domains including computer vision, natural language …

Deep learning is progressively gaining popularity as a viable alternative to i-vectors for
speaker recognition. Promising results have been recently obtained with Convolutional …

In this paper, we use data augmentation to improve performance of deep neural network
(DNN) embeddings for speaker recognition. The DNN, which is trained to discriminate …

This paper investigates replacing i-vectors for text-independent speaker verification with
embeddings extracted from a feedforward deep neural network. Long-term speaker …

Recently, deep neural networks that map utterances to fixed-dimensional embeddings have
emerged as the state-of-the-art in speaker recognition. Our prior work introduced x-vectors …

For speaker recognition, it is difficult to extract an accurate speaker representation from
speech because of its mixture of speaker traits and content. This paper proposes a …

Voice cloning is a highly desired feature for personalized speech interfaces. We introduce a
neural voice cloning system that learns to synthesize a person's voice from only a few audio …

We present Deep Speaker, a neural speaker embedding system that maps utterances to a
hypersphere where speaker similarity is measured by cosine similarity. The embeddings …

In this paper, we explore the encoding/pooling layer and loss function in the end-to-end
speaker and language recognition system. First, a unified and interpretable end-to-end …