Abstract
This paper addresses three important issues in automatic prediction of user satisfaction transitions in dialogues. The first issue concerns the individual differences in user satisfaction ratings and how they affect the possibility of creating a user-independent prediction model. The second issue concerns how to determine appropriate evaluation criteria for predicting user satisfaction transitions. The third issue concerns how to train suitable prediction models. We present our findings for these issues on the basis of the experimental results using dialogue data in two domains.
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Higashinaka, R., Minami, Y., Dohsaka, K., Meguro, T. (2010). Issues in Predicting User Satisfaction Transitions in Dialogues: Individual Differences, Evaluation Criteria, and Prediction Models. In: Lee, G.G., Mariani, J., Minker, W., Nakamura, S. (eds) Spoken Dialogue Systems for Ambient Environments. IWSDS 2010. Lecture Notes in Computer Science(), vol 6392. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16202-2_5
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DOI: https://doi.org/10.1007/978-3-642-16202-2_5
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