@misc{10481/58919, year = {2019}, url = {http://hdl.handle.net/10481/58919}, abstract = {Designing the rules for the dialog management process is oneof the most resources-consuming tasks when developing a dialog system. Although statistical approaches to dialog management are becoming mainstream in research and industrial contexts, still many systems are being developed following the rule-based or hybrid paradigms. For example, when developers require deterministic system responses to keep total control on the decisions made by the system, or because the infrastructure employed is designed for rule-based systems using technologies currently used in commercial platforms. In this paper, we propose the use of evolutionary algorithms to automatically obtain the dialog rules that are implicit in a dialog corpus. Our proposal makes it possible to exploit the benefits of statistical approaches to build rule-based systems. Our proposal has been evaluated with a practical spoken dialog system, for which we have automatically obtained a set of fuzzy rules to successfully manage the dialog.}, organization = {The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 823907 (MENHIR project:https://menhir-project.eu)}, publisher = {ISCA}, keywords = {Dialog management}, keywords = {Spoken dialog systems}, keywords = {Dialog rules}, keywords = {Evolving classifiers}, title = {Discovering Dialog Rules by means of an Evolutionary Approach}, doi = {http://dx.doi.org/10.21437/Interspeech.2019-2230}, author = {Griol Barres, David and Callejas Carrión, Zoraida}, }