Contextual Semantic Processing for a Spanish Dialogue System Using Markov Logic

Semantic processing is vital in a dialogue system for the language understanding stage. Recent approaches of semantic processing rely on machine learning methods to perform the task. These are more robust to errors from the speech recogniser. Although these approaches are built on the domain of the dialogue system they do not incorporate contextual information available in the dialogue system. In this paper, we explore the use of contextual information in the form of expectations of a dialogue system to perform semantic processing in a Spoken Dialogue System. We show the benefits on doing so, and propose a Markov Logic model which incorporates such information.