A statistical user simulation technique for the improvement of a spoken dialog system

Abstract

In this paper, we present a statistical approach for the automatic generation of dialogs by means of a user simulator. This technique can be used to generate dialogs with reduced effort, facilitating the evaluation and improvement of spoken dialog systems. In our approach for user simulation, the user answer is selected taking into account the history of the dialog and the last system turn, as well as the objective(s) set for the dialog. The user model is automatically learned from a training corpus that is labeled in terms of dialog acts. This methodology has been evaluated within the framework of the DIHANA project, whose goal is the design and development of a dialog system to access a railway information system using spontaneous speech in Spanish. © Springer-Verlag Berlin Heidelberg 2007.