The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …

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 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 …

In the past few years, deep learning-based models have been very successful in achieving
state-of-the-art results in many tasks in computer vision, speech recognition, and natural …

The speech representations learned from large-scale unlabeled data have shown better
generalizability than those from supervised learning and thus attract a lot of interest to be …

We explore the application of deep residual learning and dilated convolutions to the
keyword spotting task, using the recently-released Google Speech Commands Dataset as …

Adversarial attacks against commercial black-box speech platforms, including cloud speech
APIs and voice control devices, have received little attention until recent years. Constructing …

Once a popular theme of futuristic science fiction or far-fetched technology forecasts, digital
home assistants with a spoken language interface have become a ubiquitous commodity …

In neural network based speaker verification, speaker embedding is expected to be
discriminative between speakers while the intra-speaker distance should remain small. A …

We present a thorough analysis of the systems developed by the JHU-MIT consortium in the
context of NIST speaker recognition evaluation 2018. In the previous NIST evaluation, in …