Abstract
There are many paradigms available for designing a dialogue manager, each claiming various advantages. Four major approaches—finite state systems, Bayesian networks, MDPs and POMDPs—were described in the introduction. These approaches must be evaluated to establish which performs best in real world interactions. The purpose of this chapter is to discuss such an evaluation.
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Notes
- 1.
Inference was done with the expectation propagation algorithm and hyperparameters were chosen with type II maximum likelihood. GP models also require the choice of a covariance function for which the Matern class (with \(\nu =\frac{3}{2}\)) was chosen.
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Thomson, B. (2013). Evaluation. In: Statistical Methods for Spoken Dialogue Management. Springer Theses. Springer, London. https://doi.org/10.1007/978-1-4471-4923-1_6
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DOI: https://doi.org/10.1007/978-1-4471-4923-1_6
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