Speech interface for controlling an hi-fi audio system based on a Bayesian belief networks approach for dialog modeling

Abstract

This paper presents the development of a speech interface for controlling a high fidelity system from natural language sentences. A Bayesian Belief Network approach is proposed for dialog modeling. This solution is applied to infer the user’s goals corresponding to the processed utterances. Subsequently, from the inferred goals, missing or spurious concepts are automatically detected. This is used to drive the dialog prompting for missing concepts and clarifying for spurious concepts allowing more flexible and natural dialogs. A dialog strategy which makes use of the dialog history and the system’s state is also presented.