On2L - A Framework for Incremental Ontology Learning in Spoken Dialog Systems

An open-domain spoken dialog system has to deal with the challenge of lacking lexical as well as conceptual knowledge. As the real world is constantly changing, it is not possible to store all necessary knowledge beforehand. Therefore, this knowledge has to be acquired during the run time of the system, with the help of the out-of-vocabulary information of a speech recognizer. As every word can have various meanings depending on the context in which it is uttered, additional context information is taken into account, when searching for the meaning of such a word. In this paper, I will present the incremental ontology learning framework On2L. The defined tasks for the framework are: the hypernym extraction from Internet texts for unknown terms delivered by the speech recognizer; the mapping of those and their hypernyms into ontological concepts and instances; and the following integration of them into the system's ontology.

• Type: Conference
• Year: 2006
• Where: ACL
• Authors: Berenike Loos
• Keywords: ACL 2006, ACL 2007, Ontology Learning Framework, Speech Recognizer, Spoken Dialog System