MultiWOZ 2.3: A multi-domain task-oriented dialogue dataset enhanced with annotation corrections and co-reference annotation
This work addresses data quality issues for researchers and developers using MultiWOZ, but it is incremental as it builds on existing dataset versions.
The paper tackles annotation errors and inconsistencies in the MultiWOZ task-oriented dialogue dataset by introducing MultiWOZ 2.3, which corrects dialogue act and state annotations and adds co-reference features, resulting in significant performance improvements in natural language understanding and dialogue state tracking compared to previous versions.
Task-oriented dialogue systems have made unprecedented progress with multiple state-of-the-art (SOTA) models underpinned by a number of publicly available MultiWOZ datasets. Dialogue state annotations are error-prone, leading to sub-optimal performance. Various efforts have been put in rectifying the annotation errors presented in the original MultiWOZ dataset. In this paper, we introduce MultiWOZ 2.3, in which we differentiate incorrect annotations in dialogue acts from dialogue states, identifying a lack of co-reference when publishing the updated dataset. To ensure consistency between dialogue acts and dialogue states, we implement co-reference features and unify annotations of dialogue acts and dialogue states. We update the state of the art performance of natural language understanding and dialogue state tracking on MultiWOZ 2.3, where the results show significant improvements than on previous versions of MultiWOZ datasets (2.0-2.2).