  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.
