Paper: Robust Dialog Management with N-Best Hypotheses Using Dialog Examples and Agenda

ACL ID P08-1072
Title Robust Dialog Management with N-Best Hypotheses Using Dialog Examples and Agenda
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

This work presents an agenda-based approach to improve the robustness of the dialog man- ager by using dialog examples and n-best recognition hypotheses. This approach sup- ports n-best hypotheses in the dialog man- ager and keeps track of the dialog state us- ing a discourse interpretation algorithm with the agenda graph and focus stack. Given the agenda graph and n-best hypotheses, the system can predict the next system actions to maximize multi-level score functions. To evaluate the proposed method, a spoken dia- log system for a building guidance robot was developed. Preliminary evaluation shows this approach would be effective to improve the ro- bustness of example-based dialog modeling.