Towards an ontology-driven adaptive dialogue framework

Abstract

In this paper, we describe the principles and technologies that underpin the development of an adaptive dialogue manager framework, tailored to carrying out human-agent conversations in a natural, robust and exible manner. Our research focus is twofold. First, the investigation of dialogue strategies that can handle dynamically created user and system actions, while still enabling the agent to adapt its actions to various and possibly changing contexts. Second, the utilisation of rich semantic annotations for capturing background knowledge, as well as conversation topics and semantics of user utterances extracted through language analysis. The resulting annotations comprise the situational descriptions upon which reasoning takes place to recognise the conversation context and compile appropriate responses.