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This paper presents a new approach for dynamically increasing the coverage of a Statistical Dialog Manager. A Stochastic Finite-State Transducer for dialog management is estimated using a dialog simulator. This corpus-based model can cover most typical user behavior; however, sometimes unexpected situations may arise. Whenever these situations occur, the Dialog Manager model has no information to determine the next action. To deal with this problem, an Online Dialog Simulator is used in order to obtain synthetic dialogs for re-estimating the model and allowing it the dialog to continue. This approach has been evaluated with real users in a sport facilities booking task.