Discovering Dialog Rules by means of an Evolutionary Approach Griol Barres, David Callejas Carrión, Zoraida Dialog management Spoken dialog systems Dialog rules Evolving classifiers 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. 2020-01-20T09:03:12Z 2020-01-20T09:03:12Z 2019 info:eu-repo/semantics/conferenceObject INTERSPEECH 2019 September 15–19, 2019 [http://dx.doi.org/10.21437/Interspeech.2019-2230] http://hdl.handle.net/10481/58919 http://dx.doi.org/10.21437/Interspeech.2019-2230 eng H2020/823907 info:eu-repo/semantics/openAccess ISCA