Abstract
This paper describes a toolkit designed to automatically develop dialog managers for spoken dialog system based on evolving Fuzzy-rule-based (FRB) classifiers. The FRB-dialog toolkit allows to develop dialog managers selecting the next system action by considering a set of dynamic rules that are automatically obtained by means of the application of the FRB classification process. Our approach bridges the gap between the academic and industrial perspectives for developing dialog systems, taking into account the data supplied by the user throughout the complete dialog history without causing scalability problems, and also considering confidence measures provided by the recognition and understanding modules.
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Acknowledgements
This work was supported in part by Projects TRA2015-63708-R and TRA2016-78886-C3-1-R.
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Griol, D., de Miguel, A.S., Molina, J.M. (2017). FRB-Dialog: A Toolkit for Automatic Learning of Fuzzy-Rule Based (FRB) Dialog Managers. In: Martínez de Pisón, F., Urraca, R., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2017. Lecture Notes in Computer Science(), vol 10334. Springer, Cham. https://doi.org/10.1007/978-3-319-59650-1_26
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DOI: https://doi.org/10.1007/978-3-319-59650-1_26
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