4.7 Article

Synthesizing Obama: Learning Lip Sync from Audio

Journal

ACM TRANSACTIONS ON GRAPHICS
Volume 36, Issue 4, Pages -

Publisher

ASSOC COMPUTING MACHINERY
DOI: 10.1145/3072959.3073640

Keywords

Audio; Face Synthesis; LSTM; RNN; Pig data. Videos; Audiovisual Speech; Uncanny Valley; Lip Sync

Funding

  1. Samsung
  2. Google
  3. Intel
  4. University of Washington Animation Research Labs

Ask authors/readers for more resources

Given audio of President Barack Obama, we synthesize a high quality video of him speaking with accurate lip sync, composited into a target video clip. Trained on many hours of his weekly address footage, a recurrent neural network learns the mapping from raw audio features to mouth shapes. Given the mouth shape at each time instant, we synthesize high quality mouth texture, and composite it with proper 3D pose matching to change what he appears to be saying in a target video to match the input audio track. Our approach produces photorealistic results.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available