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- W2380573072 abstract "Visual information can improve speech perception. But how to synthesis the realistic mouth shape is a complex problem. After studying the rule of lip movement in speaking, a dominance blending dynamic viseme model for visual speech synthesis is proposed in this paper. Furthermore, considering the characteristic of Chinese speech, a systemic learning method is given to learn the model parameters from training data, which is more reliable than desire parameters according to subjective experience. Experimental results show that the dynamic viseme model and learning method are effective." @default.
- W2380573072 created "2016-06-24" @default.
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- W2380573072 date "2003-01-01" @default.
- W2380573072 modified "2023-09-22" @default.
- W2380573072 title "A Dynamic Viseme Model and Parameter Estimation" @default.
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