  To advance multi-domain (cross-domain) dialogue modeling as well as alleviate
the shortage of Chinese task-oriented datasets, we propose CrossWOZ, the first
large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset. It
contains 6K dialogue sessions and 102K utterances for 5 domains, including
hotel, restaurant, attraction, metro, and taxi. Moreover, the corpus contains
rich annotation of dialogue states and dialogue acts at both user and system
sides. About 60% of the dialogues have cross-domain user goals that favor
inter-domain dependency and encourage natural transition across domains in
conversation. We also provide a user simulator and several benchmark models for
pipelined task-oriented dialogue systems, which will facilitate researchers to
compare and evaluate their models on this corpus. The large size and rich
annotation of CrossWOZ make it suitable to investigate a variety of tasks in
cross-domain dialogue modeling, such as dialogue state tracking, policy
learning, user simulation, etc.
