Facial expressions are a kind of nonverbal communication. They carry the state of emotion of a person. Facial expression plays an important role in face-to face human-computer communication. Automatic facial expression synthesis became popular research area nowadays. It can be used in many areas such that physiology, education, murder squad, analysis of tendency to crime to get a clue about mental signals of a person. Although considerable efforts have been made to enable computers to speak like human beings, how to express the rich semantic information through facial expression still remains a challenging problem. This paper presents a novel approach using artificial neural network. This paper proposes two different approaches with different methods for facial expressions synthesis based on artificial neural networks (ANN). Firstly, Modeling using Hidden Markov Models is proposed. Secondly, modeling using Recurrent Neural.

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Emotional Facial Expression Modeling Face Synthesis Facial Animation Hidden Markov Models Recurrent Neural Networks.