2.3k citations · 7.4k across the 34 of their papers we have counts for
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Perfect match: Improved cross-modal embeddings for audio-visual synchronisation
Soo-Whan Chung, Joon Son Chung, Hong-Goo Kang
This paper proposes a new strategy for learning powerful cross-modal embeddings for audio-to-video synchronization. Here, we set up the problem as one of cross-modal retrieval, whe…
LRS3-TED: a large-scale dataset for visual speech recognition
Triantafyllos Afouras, Joon Son Chung, Andrew Zisserman
This paper introduces a new multi-modal dataset for visual and audio-visual speech recognition. It includes face tracks from over 400 hours of TED and TEDx videos, along with the c…
Deep Audio-Visual Speech Recognition
Triantafyllos Afouras, Joon Son Chung, Andrew Senior +2
The goal of this work is to recognise phrases and sentences being spoken by a talking face, with or without the audio. Unlike previous works that have focussed on recognising a lim…
VoxCeleb2: Deep Speaker Recognition
Joon Son Chung, Arsha Nagrani, Andrew Zisserman
The objective of this paper is speaker recognition under noisy and unconstrained conditions. We make two key contributions. First, we introduce a very large-scale audio-visual spea…
Deep Lip Reading: a comparison of models and an online application
Triantafyllos Afouras, Joon Son Chung, Andrew Zisserman
The goal of this paper is to develop state-of-the-art models for lip reading -- visual speech recognition. We develop three architectures and compare their accuracy and training ti…
The Conversation: Deep Audio-Visual Speech Enhancement
Triantafyllos Afouras, Joon Son Chung, Andrew Zisserman
Our goal is to isolate individual speakers from multi-talker simultaneous speech in videos. Existing works in this area have focussed on trying to separate utterances from known sp…