Visual speech, referring to the visual domain of speech, has attracted increasing attention
due to its wide applications, such as public security, medical treatment, military defense, and …

The objective of this paper is to separate a target speaker's speech from a mixture of two
speakers using a deep audio-visual speech separation network. Unlike previous works that …

The goal of this work is zero-shot text-to-speech synthesis, with speaking styles and voices
learnt from facial characteristics. Inspired by the natural fact that people can imagine the …

In this paper, we address the problem of separating individual speech signals from videos
using audio-visual neural processing. Most conventional approaches utilize frame-wise …

The large amount of audiovisual content being shared online today has drawn substantial
attention to the prospect of audiovisual self-supervised learning. Recent works have focused …

Traditional speaker diarization seeks to detect``who spoke when''according to speaker
characteristics. Extending to target speech diarization, we detect``when target event …

In this paper, we address the problem of lip-voice synchronisation in videos containing
human face and voice. Our approach is based on determining if the lips motion and the …

The goal of this work is to train discriminative cross-modal embeddings without access to
manually annotated data. Recent advances in self-supervised learning have shown that …

In this work, we present a novel audio-visual dataset for active speaker detection in the wild.
A speaker is considered active when his or her face is visible and the voice is audible …

Numerous studies have investigated the effectiveness of audio-visual multimodal learning
for speech enhancement (AVSE) tasks, seeking a solution that uses visual data as auxiliary …