6th SIGdial Workshop on Discourse and Dialogue

Lisbon, Portugal
September 2-3, 2005

A Corpus Collection and Annotation Framework for Learning Multimodal Clarification Strategies

Verena Rieser (1), Ivana Kruijff-Korbayová (1), Oliver Lemon (2)

(1) Department of Computational Linguistics, Saarland University Saarbrücken, Germany
(2)School of Informatics, University of Edinburgh, UK

Current dialogue systems are fairly poor in generating the wide range of clarification strategies as found in human-human dialogue. The overall aim of this work is to learn when and how to best employ different types of clarification strategies in multimodal dialogue systems. This paper describes a framework for learning multimodal clarification strategies for an in-car MP3 music player dialogue system. The framework consists of three major parts. First we collect data on multimodal clarification strategies in a wizard-of-oz study. Second we extract feature in the stateaction space to learn an initial policy from this data. Third we specify a reward function to refine that policy using extensions of existing evaluation schemes.

Full Paper

Bibliographic reference.  Rieser, Verena / Kruijff-Korbayová, Ivana / Lemon, Oliver (2005): "A corpus collection and annotation framework for learning multimodal clarification strategies", In SIGdial6-2005, 97-106.