The PARADISE Evaluation Framework: Issues and Findings
Computational Linguistics
Partially observable Markov decision processes for spoken dialog systems
Computer Speech and Language
A statistical approach to spoken dialog systems design and evaluation
Speech Communication
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
Evaluation of a hierarchical reinforcement learning spoken dialogue system
Computer Speech and Language
Multimodal Interactive Pattern Recognition and Applications
Multimodal Interactive Pattern Recognition and Applications
An unsupervised approach to user simulation: toward self-improving dialog systems
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
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The new Interactive Pattern Recognition (IPR) framework has been recently proposed. This proposal lets a human interact with a Pattern Recognition system allowing the system to learn from the interaction as well as adapt it to the human behavior. The aim of this paper is to apply the principles of IPR to the design of Spoken Dialog Systems (SDS). We propose a new formulation to present SDS as an IPR problem. To this end some extensions to the IPR approach are proposed. Additionally a user model based on the IPR paradigm is also defined. We applied the proposed formulation to compose a preliminary graphical model that has been experimentally developed to deal with a Spanish dialog task. An initial maximum likelihood strategy for the dialog manager actions along with a stochastic simulation of user behavior have allowed to get new dialogs. The preliminary evaluation of these results allowed us to consider this formulation as a promising framework to deal with SDS.