A realistic 3D articulatory animation system for emotional visual pronunciation

This paper proposes a realistic 3D articulatory animation system for emotional visual pronunciation driven by the emotional articulatory movement trajectory. Firstly, the articulatory movements, recorded by Electro-Magnetic Articulatory (EMA), are trained by Hidden Markov Model (HMM) while the fully context-dependent model is taken into account by making full use of the rich linguistic features. Secondly, owing to the independency in the manipulation of articulators, the articulatory movements are more remarkably adjusted to express different emotions. Thirdly, the emotional speech is generated by adjusting the neutral speech parameters, such as fundamental frequency (F0), duration and intensity, based on Praat. Then the corresponding articulatory movements are synthesized by the HMM prediction rules which are used to drive the head mesh model along with the emotional speech simultaneously. The experiments intend to synthesize accurate emotional speech synchronized animation of articulators based on the system at phoneme level.