Massachusetts Institute of Technology

Antoine F Ezzat

Tomaso A Poggio

A method and apparatus for videorealistic, speech animation is disclosed. A human subject is recorded using a video camera as he/she utters a predetermined speech corpus. After processing the corpus automatically, a visual speech module is learned from the data that is capable of synthesizing the human subject's mouth uttering entirely novel utterances that were not recorded in the original video. The synthesized utterance is re-composited onto a background sequence which contains natural head and eye movement. The final output is videorealistic in the sense that it looks like a video camera recording of the subject. The two key components of this invention are 1) a multidimensional morphable model (MMM) to synthesize new, previously unseen mouth configurations from a small set of mouth image prototypes; and 2) a trajectory synthesis technique based on regularization, which is automatically trained from the recorded video corpus, and which is capable of synthesizing trajectories in MMM space corresponding to any desired utterance.

Trainable videorealistic speech animation

A method and apparatus of converting input text into an audio-visual speech stream resulting in a talking face image enunciating the text. This method of converting input text into an audio-visual speech stream comprises the steps of: recording a visual corpus of a human-subject, building a viseme interpolation database, and synchronizing the talking face image with the text stream. In a preferred embodiment, viseme transitions are automatically calculated using optical flow methods, and morphing techniques are employed to result in smooth viseme transitions. The viseme transitions are concatenated together and synchronized with the phonemes according to the timing information. The audio-visual speech stream is then displayed in real time, thereby displaying a photo-realistic talking face.

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Cambridge, MA, United States of America

Antoine F Ezzat