Abstract
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 on 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.- Anthology ID:
- 2020.tacl-1.19
- Volume:
- Transactions of the Association for Computational Linguistics, Volume 8
- Month:
- Year:
- 2020
- Address:
- Cambridge, MA
- Editors:
- Mark Johnson, Brian Roark, Ani Nenkova
- Venue:
- TACL
- SIG:
- Publisher:
- MIT Press
- Note:
- Pages:
- 281–295
- Language:
- URL:
- https://preview.aclanthology.org/add_missing_videos/2020.tacl-1.19/
- DOI:
- 10.1162/tacl_a_00314
- Cite (ACL):
- Qi Zhu, Kaili Huang, Zheng Zhang, Xiaoyan Zhu, and Minlie Huang. 2020. CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset. Transactions of the Association for Computational Linguistics, 8:281–295.
- Cite (Informal):
- CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset (Zhu et al., TACL 2020)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2020.tacl-1.19.pdf
- Code
- thu-coai/CrossWOZ + additional community code
- Data
- CrossWOZ, ATIS, MultiWOZ