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Our framework uses Microsoft Text-to-Speech (TTS) engine for text analysis and speech synthesis. First, the text stream is fed into the TTS engine. TTS parses the text and generates the corresponding phoneme sequence, the timing information of phonemes, and the synthesized speech stream. Each phoneme is mapped to a viseme based on a lookup table. Each viseme is a key frame. Therefore, the text is translated in to a key frame sequence. A temporal trajectory is then synthesized based on the key frame sequence using the technique described in Section 2.

7. (a): The generic model in iFACE. (b): A personalized face model based on the CyberwareTM scanner data. (c): The feature points defined on generic model. , 2002], we used MUs to animate models generated by iFACE. We dealt with the MU fitting problem by constructing a mapping between MUs and the face deformation model of iFACE. This technique allowed a key-frame based face animation system to use MUs. First we 28 3D FACE PROCESSING: MODELING, ANALYSIS AND SYNTHESIS selected a set of training facial shapes with known MUPs.

2002] pose the trajectory modeling problem as a regularization problem [Wahba, 1990]. The goal is to synthesize a Learning Geometric 3D Facial Motion Model 21 trajectory which minimizes an objective function consisting of a target term and a smoothness term. The target term is a distance function between the trajectory and the given key shapes. The optimization of the objective function yields multivariate additive quintic splines [Wahba, 1990]. The results produced by this approach could look under-articulated.

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An object-oriented database programming environment for Oberon by Supcik J.

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