| Paper ID | HLT-3.3 |
| Paper Title |
ACTION STATE UPDATE APPROACH TO DIALOGUE MANAGEMENT |
| Authors |
Svetlana Stoyanchev, Simon Keizer, Rama Doddipatla, Toshiba Cambridge Research Laboratory, United Kingdom |
| Session | HLT-3: Dialogue Systems 1: General Topics |
| Location | Gather.Town |
| Session Time: | Tuesday, 08 June, 14:00 - 14:45 |
| Presentation Time: | Tuesday, 08 June, 14:00 - 14:45 |
| Presentation |
Poster
|
| Topic |
Human Language Technology: [HLT-DIAL] Discourse and Dialog |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
Utterance interpretation is one of the main functions of a dialogue manager, which is the key component of a dialogue system. We propose the action state update approach (ASU) for utterance interpretation, featuring a statistically trained binary classifier used to detect dialogue state update actions in the text of a user utterance. Our goal is to interpret referring expressions in user input without a domain-specific natural language understanding component. For training the model, we use active learning to automatically select simulated training examples. With both user-simulated and interactive human evaluations, we show that the ASU approach successfully interprets user utterances in a dialogue system, including those with referring expressions. |
