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MultiWOZ 2.0 (Budzianowski et al., 2018) is a recently released multi-domaindialogue dataset spanning 7 distinct domains and containing over 10,000dialogues. Though immensely useful and one of the largest resources of its kindto-date, MultiWOZ 2.0 has a few shortcomings. Firstly, there is substantialnoise in the dialogue state annotations and dialogue utterances whichnegatively impact the performance of state-tracking models. Secondly, follow-upwork (Lee et al., 2019) has augmented the original dataset with user dialogueacts. This leads to multiple co-existent versions of the same dataset withminor modifications. In this work we tackle the aforementioned issues byintroducing MultiWOZ 2.1. To fix the noisy state annotations, we usecrowdsourced workers to re-annotate state and utterances based on the originalutterances in the dataset. This correction process results in changes to over32% of state annotations across 40% of the dialogue turns. In addition, we fix146 dialogue utterances by canonicalizing slot values in the utterances to thevalues in the dataset ontology. To address the second problem, we combined thecontributions of the follow-up works into MultiWOZ 2.1. Hence, our dataset alsoincludes user dialogue acts as well as multiple slot descriptions per dialoguestate slot. We then benchmark a number of state-of-the-art dialogue statetracking models on the MultiWOZ 2.1 dataset and show the joint state trackingperformance on the corrected state annotations. We are publicly releasingMultiWOZ 2.1 to the community, hoping that this dataset resource will allow formore effective models across various dialogue subproblems to be built in thefuture.

MultiWOZ 2.1: A Consolidated Multi-Domain Dialogue Dataset with State Corrections and State Tracking Baselines