Using Dialog Corrections to Improve Speech Recognition

Abstract

We propose a preliminary method for automatically correcting errors in spoken dialogue systems. Current spoken dialogue systems usually show a rather static and rigid behavior regarding recognition errors, therefore a feasible method of correcting system errors might be helpful to successfully support user requests. Moreover, a correction differs from non-correction prosodically [1]. Generally a user correction exhibits a greater prosodic difference the more distant it is from the initial error. In this case it is recognized more poorly, and it involves a longer human-machine interaction because this often leds to the same recognition errors. This pape