Papers with dialogue modelling
Semi-Supervised Bootstrapping of Dialogue State Trackers for Task-Oriented Modelling (D19-1)
Copied to clipboard
| Challenge: | Existing systems rely on modular, domain-focused frameworks for analyzing complex problems. |
| Approach: | They propose semi-supervised learning methods that can reduce the amount of required intermediate labelling by leveraging un-annotated data instead of transcribed utterances. |
| Outcome: | The proposed model reduces the amount of turn-level annotations by 30% while maintaining equivalent system performance. |
A Unifying View On Task-oriented Dialogue Annotation (2022.lrec-1)
Copied to clipboard
| Challenge: | Recent research attention in task-oriented dialogue systems focuses on end-to-end neural models. |
| Approach: | They present a dataset that combines annotated corpora from four domains to provide a unified ontology and annotation schema for task-oriented dialogues. |
| Outcome: | The proposed dataset improves language, information content and performance in dialogues with two recent models. |