Paper: Segmented And Unsegmented Dialogue-Act Annotation With Statistical Dialogue Models

ACL ID P06-2073
Title Segmented And Unsegmented Dialogue-Act Annotation With Statistical Dialogue Models
Venue Annual Meeting of the Association of Computational Linguistics
Session Poster Session
Year 2006
Authors

Dialoguesystemsareoneofthemostchal- lenging applications of Natural Language Processing. In recent years, some statis- tical dialogue models have been proposed to cope with the dialogue problem. The evaluation of these models is usually per- formed by using them as annotation mod- els. Many of the works on annotation use information such as the complete se- quence of dialogue turns or the correct segmentation of the dialogue. This in- formation is not usually available for dia- logue systems. In this work, we propose a statistical model that uses only the infor- mation that is usually available and per- forms the segmentation and annotation at the same time. The results of this model revealthegreatinfluencethattheavailabil- ity of a correct segmentation has in ob- taining an accurate annot...