Dialogue act prediction using stochastic context-free grammar induction

Authors:
Jeroen Geertzen
Affiliations:
University of Cambridge, UK
Venue:
CLAGI '09 Proceedings of the EACL 2009 Workshop on Computational Linguistic Aspects of Grammatical Inference
Year:
2009

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Abstract

This paper presents a model-based approach to dialogue management that is guided by data-driven dialogue act prediction. The statistical prediction is based on stochastic context-free grammars that have been obtained by means of grammatical inference. The prediction performance of the method compares favourably to that of a heuristic baseline and to that of n-gram language models. The act prediction is explored both for dialogue acts without realised semantic content (consisting only of communicative functions) and for dialogue acts with realised semantic content.