A dynamic viseme model for personalizing a talking head
Zhiming Wang, Cai Lianhong, Haizhou Ai · 2003
Personalizing a talking head means not only to personalize a head model but also to personalize his talking manner. In this paper, we propose a dynamic viseme model for visual speech synthesis that can deal with co-articulation problem and various pauses in continuous speech. Facial animation parameters (FAPs) defined in MPEG-4 are estimated according to the tracked feature points from two orthogonal views via a mirror setup. Individual talking manner described by model parameters is learnt from FAP data to implement a personalized talking head.