Learning dialog act processing

Authors:
Stefan Wermter;Matthias Löchel
Affiliations:
University of Hamburg, Hamburg, Germany;University of Hamburg, Hamburg, Germany
Venue:
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Year:
1996

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Abstract

In this paper we describe a new approach for learning dialog act processing. In this approach we integrate a symbolic semantic segmentation parser with a learning dialog act network. In order to support the unforeseeable errors and variations of spoken language we have concentrated on robust data-driven learning. This approach already compares favorably with the statistical average plausibility method, produces a segmentation and dialog act assignment for all utterances in a robust manner, and reduces knowledge engineering since it can be bootstrapped from rather small corpora. Therefore, we consider this new approach as very promising for learning dialog act processing.