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 …

As ChatGPT goes viral, generative AI (AIGC, aka AI-generated content) has made headlines
everywhere because of its ability to analyze and create text, images, and beyond. With such …

Generating talking head videos through a face image and a piece of speech audio still
contains many challenges. ie, unnatural head movement, distorted expression, and identity …

While accurate lip synchronization has been achieved for arbitrary-subject audio-driven
talking face generation, the problem of how to efficiently drive the head pose remains …

As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …

Generating high-fidelity talking head video by fitting with the input audio sequence is a
challenging problem that receives considerable attentions recently. In this paper, we …

In this work, we investigate the problem of lip-syncing a talking face video of an arbitrary
identity to match a target speech segment. Current works excel at producing accurate lip …

We propose a neural talking-head video synthesis model and demonstrate its application to
video conferencing. Our model learns to synthesize a talking-head video using a source …

Generating expressive talking heads is essential for creating virtual humans. However,
existing one-or few-shot methods focus on lip-sync and head motion, ignoring the emotional …

One-shot talking face generation should synthesize high visual quality facial videos with
reasonable animations of expression and head pose, and just utilize arbitrary driving audio …