Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
A Bayesian method for constructing Bayesian belief networks from databases
Proceedings of the seventh conference (1991) on Uncertainty in artificial intelligence
Robots for kids
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Development of an Autonomous Quadruped Robot for Robot Entertainment
Autonomous Robots - Special issue on autonomous agents
Bayesian Artificial Intelligence
Bayesian Artificial Intelligence
A Bayesian approach for user modeling in dialogue systems
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
A Biphase-Bayesian-Based Method of Emotion Detection from Talking Voice
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
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This paper proposes a method for sensitivity communication robots which infer their dialogist’s emotion. The method is based on the Bayesian approach: by using a Bayesian modeling for prosodic features. In this research, we focus the elements of emotion included in dialogist’s voice. Thus, as training datasets for learning Bayesian networks, we extract prosodic feature quantities from emotionally expressive voice data. Our method learns the dependence and its strength between dialogist’s utterance and his emotion, by building Bayesian networks. Bayesian information criterion, one of the information theoretical model selection method, is used in the building Bayesian networks. The paper finally proposes a reasoner to infer dialogist’s emotion by using a Bayesian network for prosodic features of the dialogist’s voice. The paper also reports some empirical reasoning performance.