MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling

被引:0
作者
Budzianowski, Pawel [1 ]
Wen, Tsung-Hsien [2 ,3 ]
Tseng, Bo-Hsiang [1 ]
Casanueva, Iiiigo [1 ]
Ultes, Stefan [1 ]
Ramadan, Osman [1 ]
Gasic, Milica [1 ]
机构
[1] Univ Cambridge, Dept Engn, Cambridge, England
[2] PolyAI, London, England
[3] Univ Cambridge, Cambridge, England
来源
2018 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING (EMNLP 2018) | 2018年
基金
英国工程与自然科学研究理事会;
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Even though machine learning has become the major scene in dialogue research community, the real breakthrough has been blocked by the scale of data available. To address this fundamental obstacle, we introduce the Multi-Domain Wizard-of-Oz dataset (MultiWOZ), a fully-labeled collection of human-human written conversations spanning over multiple domains and topics. At a size of 10k dialogues, it is at least one order of magnitude larger than all previous annotated task-oriented corpora. The contribution of this work apart from the open-sourced dataset labelled with dialogue belief states and dialogue actions is two-fold: firstly, a detailed description of the data collection procedure along with a summary of data structure and analysis is provided. The proposed data-collection pipeline is entirely based on crowd-sourcing without the need of hiring professional annotators; secondly, a set of benchmark results of belief tracking, dialogue act and response generation is reported, which shows the usability of the data and sets a baseline for future studies.
引用
收藏
页码:5016 / 5026
页数:11
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