LREC 2006 - Proceedings sorted by papers

Title	Learning Database Content for Spoken Dialogue System Design
Authors	J. Polifroni, M. Walker
Abstract	Spoken dialogue systems are common interfaces to backend data in information retrieval domains. As more data is made available on the Web and IE technology matures, dialogue systems, whether they be speech- or text-based, will be more in demand to provide user-friendly access to this data. However, dialogue systems must become both easier to configure, as well as more informative than the traditional form-based systems that are currently available. We present techniques in this paper to address the issue of automating both content selection for use in summary responses and in system initiative queries.
Keywords	Machine learning, content selection, dialogue systems
Full paper	Learning Database Content for Spoken Dialogue System Design

Title

Learning Database Content for Spoken Dialogue System Design

Authors

J. Polifroni, M. Walker

Abstract

Spoken dialogue systems are common interfaces to backend data in information retrieval domains. As more data is made available on the Web and IE technology matures, dialogue systems, whether they be speech- or text-based, will be more in demand to provide user-friendly access to this data. However, dialogue systems must become both easier to configure, as well as more informative than the traditional form-based systems that are currently available. We present techniques in this paper to address the issue of automating both content selection for use in summary responses and in system initiative queries.

Keywords

Machine learning, content selection, dialogue systems

Full paper

Learning Database Content for Spoken Dialogue System Design