Merging Intention and Emotion to Develop Adaptive Dialogue Systems
In this paper we propose a method for merging intentional and emotional information in spoken dialogue systems in order to make dialogue managers more efficient and adaptive. The prediction of the user intention and emotion is carried out for each user turn in the dialogue by means of a module conceived as an intermediate phase between natural language understanding and dialogue management in the architecture of these systems. We have applied and evaluated our method in the UAH system, for which the evaluation results show that merging both sources of information improves system performance as well as its perceived quality.
KeywordsSpoken Dialogue Systems Emotion Processing
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