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

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arxiv 1810.00278 v3 pith:NRHUVB26 submitted 2018-09-29 cs.CL

Pawe{l} Budzianowski , Tsung-Hsien Wen , Bo-Hsiang Tseng , Iñigo Casanueva , Stefan Ultes , Osman Ramadan , Milica Gašić This is my paper
classification cs.CL
keywords dialoguedatadatasetbeliefcollectionmulti-domainmultiwoztask-oriented
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

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 $10$k 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.

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