Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …

YourTTS brings the power of a multilingual approach to the task of zero-shot multi-speaker
TTS. Our method builds upon the VITS model and adds several novel modifications for zero …

Voice conversion is a process where the essence of a speaker's identity is seamlessly
transferred to another speaker, all while preserving the content of their speech. This usage is …

To the best of our knowledge, we first present a live system that generates personalized
photorealistic talking-head animation only driven by audio signals at over 30 fps. Our system …

Text style transfer is an important task in natural language generation, which aims to control
certain attributes in the generated text, such as politeness, emotion, humor, and many …

We present a neural analysis and synthesis (NANSY) framework that can manipulate the
voice, pitch, and speed of an arbitrary speech signal. Most of the previous works have …

We present a method that generates expressive talking-head videos from a single facial
image with audio as the only input. In contrast to previous attempts to learn direct mappings …

Self-supervised learning in speech involves training a speech representation network on a
large-scale unannotated speech corpus, and then applying the learned representations to …

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 …

While recent advances in deep neural networks have made it possible to render high-quality
images, generating photo-realistic and personalized talking head remains challenging. With …