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In dyadic human interactions, mutual influence -a person's influence on the interacting partner's behaviors -is shown to be important and could be incorporated into the modeling framework in characterizing, and automatically recognizing the participants' states. We propose a Dynamic Bayesian Network (DBN) to explicitly model the conditional dependency between two interacting partners' emotion states in a dialog using data from the IEMOCAP corpus of expressive dyadic spoken interactions. Also,doi:10.21437/interspeech.2009-480 fatcat:gzdx6xqxazdg7fwqi5zjk7s4ai