Learning dialog act processing

In this paper we describe a new approach for learning dialog act processing. In this approach we integrate a symbolic semantic segmentation parse,: 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 plansibility method, produces a segmentation and dialog act assignment for all utteranccs in a robust manner, and redaces 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.

• Type: Conference
• Year: 1996
• Where: COLING
• Authors: Stefan Wermter, Matthias Lochel
• Keywords: COLING 1996, COLING 2008, Dialog Act, Dialog Act Network, Dialog Act Processing