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Abstract
  • We propose here an HMM-based trajectory formation system
    that predicts articulatory trajectories of a talking face from phonetic input. In order to add flexibility to the
    acoustic/gestural alignment and take into account anticipatory gestures, a phasing model has been developed that predicts the delays between the acoustic boundaries of allophones to be synthesized and the gestural boundaries of HMM triphones.
    The HMM triphones and the phasing model are trained
    simultaneously using an iterative analysis-synthesis loop.
    Convergence is obtained within a few iterations. We demonstrate here that the phasing model improves
    significantly the prediction error and captures subtle context-dependent anticipatory phenomena.
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