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CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset

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Publicado en:Transactions of the Association for Computational Linguistics vol. 8 (2020), p. 281
Autor principal: Zhu, Qi
Otros Autores: Huang, Kaili, Zhang, Zheng, Zhu, Xiaoyan, Huang, Minlie
Publicado:
MIT Press Journals, The
Materias:
Simulation
Datasets
Human-computer interaction
Annotations
Dialogue
Modelling
Computational linguistics
Linguistics
Interactive computer systems
Hotels & motels
Natural language
Utterances
Models
Tracking
Restaurants
Dependency
Acceso en línea:Citation/Abstract
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Resumen: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.
ISSN:2307-387X
DOI:10.1162/tacl_a_00314
Fuente:Advanced Technologies & Aerospace Database