Abstract: Described is a speech recognition dialog management system that allows more open-ended conversations between virtual agents and people than are possible using just agent-directed dialogs. The system uses both novel dialog context switching and learning algorithms based on spoken interactions with people. The context switching is performed through processing multiple dialog goals in a last-in-first-out (LIFO) pattern. The recognition accuracy for these new flexible conversations is improved through automated learning from processing errors and addition of new grammars.

Abstract: A speech dialog management system where each dialog is capable of supporting one or more turns of conversation between a user and virtual agent using any one or combination of a communications interface and data interface. The system includes compiled application libraries, which determine the recognition, response, and flow control in a dialog with a user. A process of execution of a compiled application library runs throughout the conversation, putting itself into a dormant state in between processing of the communications from the user. A script manager brokers information between the processes of execution of the compiled application libraries and many communications with users.