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The Conversation: Deep Audio-Visual Speech Enhancement
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 speakers in controlled environments. In this
paper, we propose a deep audio-visual speech enhancement network that is able
to separate a speaker's voice given lip regions in the corresponding video, by
predicting both the magnitude and the phase of the target signal. The method is
applicable to speakers unheard and unseen during training, and for
unconstrained environments. We demonstrate strong quantitative and qualitative
results, isolating extremely challenging real-world examples.Comment: To appear in Interspeech 2018. We provide supplementary material with
interactive demonstrations on
http://www.robots.ox.ac.uk/~vgg/demo/theconversatio
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