MultiWOZ 2.4: A Multi-Domain Task-Oriented Dialogue Dataset with Essential Annotation Corrections to Improve State Tracking Evaluation
Fanghua Ye, Jarana Manotumruksa, Emine Yılmaz · 2022
The MultiWOZ 2.0 dataset has greatly stimulated the research of task-oriented dialogue systems.However, its state annotations contain substantial noise, which hinders a proper evaluation of model performance.To address this issue, massive efforts were devoted to correcting the annotations.Three improved versions (i.e., MultiWOZ 2.1-2.3)have then been released.Nonetheless, there are still plenty of incorrect and inconsistent annotations.This work introduces MultiWOZ 2.4, which refines the annotations in the validation set and test set of MultiWOZ 2.1.The annotations in the training set remain unchanged (same as MultiWOZ 2.1) to elicit robust and noise-resilient model training.We benchmark eight state-of-the-art dialogue state tracking models on MultiWOZ 2.4.All of them demonstrate much higher performance than on MultiWOZ 2.1 1 .Error Type Conversation Example MultiWOZ 2.1 MultiWOZ 2.4 (I) Context Mismatch Usr: Hello, I would like to book a taxi from restaurant 2 two to the museum of classical archaeology.taxi-destination=museum of archaelogy and anthropology taxi-destination=museum of classical archaeology Usr: I am looking for a restaurant that serves Portuguese food.rest.-food=Portugeserest.-food=Portuguese