This proposal introduces a Dialogue Challenge for building end-to-end task-completion dialogue systems, with the goal of encouraging the dialogue research community to collaborate and benchmark on standard datasets and unified experimental environment. In this special session, we will release human-annotated conversational data in three domains (movie-ticket booking, restaurant reservation, and taxi booking), as well as an experiment platform with built-in simulators in each domain, for training and evaluation purposes. The final submitted systems will be evaluated both in simulated setting and by human judges.
[1]
Jianfeng Gao,et al.
End-to-End Task-Completion Neural Dialogue Systems
,
2017,
IJCNLP.
[2]
Steve J. Young,et al.
The Hidden Agenda User Simulation Model
,
2009,
IEEE Transactions on Audio, Speech, and Language Processing.
[3]
Jianfeng Gao,et al.
A User Simulator for Task-Completion Dialogues
,
2016,
ArXiv.