Human voices can be used to authenticate the identity of the speaker, but the automatic
speaker verification (ASV) systems are vulnerable to voice spoofing attacks, such as …

The voice conversion challenge is a bi-annual scientific event held to compare and
understand different voice conversion (VC) systems built on a common dataset. In 2020, we …

Automatic methods to predict listener opinions of synthesized speech remain elusive since
listeners, systems being evaluated, characteristics of the speech, and even the instructions …

We present an unsupervised non-parallel many-to-many voice conversion (VC) method
using a generative adversarial network (GAN) called StarGAN v2. Using a combination of …

Recent advancements in AI, especially deep learning, have contributed to a significant
increase in the creation of new realistic-looking synthetic media (video, image, and audio) …

Significant advancements made in the generation of deepfakes have caused security and
privacy issues. Attackers can easily impersonate a person's identity in an image by replacing …

The recent emergence of deepfakes has brought manipulated and generated content to the
forefront of machine learning research. Automatic detection of deepfakes has seen many …

Shared challenges provide a venue for comparing systems trained on common data using a
standardized evaluation, and they also provide an invaluable resource for researchers when …

In this paper, we present UR-AIR system submission to the logical access (LA) and the
speech deepfake (DF) tracks of the ASVspoof 2021 Challenge. The LA and DF tasks focus …

The rise in demand of voice biometric systems also increases the threat from various kinds
of spoofing attacks from unauthorized users. The latest ASVspoof 2021 challenge devotes to …