User Modeling for Task Oriented Dialogues

Izzeddin Gur, Dilek Hakkani-Tur, Gokhan Tur, Pararth Shah

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We introduce end-to-end neural network based models for simulating users of task-oriented dialogue systems. User simulation in dialogue systems is crucial from two different perspectives: (i) automatic evaluation of different dialogue models, and (ii) training task-oriented dialogue systems. We design a hierarchical sequence-to-sequence model that first encodes the initial user goal and system turns into fixed length representations using Recurrent Neural Networks (RNN). It then encodes the dialogue history using another RNN layer. At each turn, user responses are decoded from the hidden representations of the dialogue level RNN. This hierarchical user simulator (HUS) approach allows the model to capture undiscovered parts of the user goal without the need of an explicit dialogue state tracking. We further develop several variants by utilizing a latent variable model to inject random variations into user responses to promote diversity in simulated user responses and a novel goal regularization mechanism to penalize divergence of user responses from the initial user goal. We evaluate the proposed models on movie ticket booking domain by systematically interacting each user simulator with various dialogue system policies trained with different objectives and users.

Original languageEnglish (US)
Title of host publication2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Electronic)9781538643341
StatePublished - Jul 2 2018
Externally publishedYes
Event2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Athens, Greece
Duration: Dec 18 2018Dec 21 2018

Publication series

Name2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Proceedings


Conference2018 IEEE Spoken Language Technology Workshop, SLT 2018

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Linguistics and Language


Dive into the research topics of 'User Modeling for Task Oriented Dialogues'. Together they form a unique fingerprint.

Cite this