Incremental Joint Modelling for Dialogue State Tracking

Anh Duong Trinh, Robert J. Ross, John D. Kelleher


Dialogue State Tracking is an important task in dialogue management as it provides a mechanism to monitor dialogue contributions. In this paper we introduce an Incremental Joint Model as a new approach to the task. Our tracker is capable of incrementally tracking Dialogue States. We base our model and analysis on the datasets provided in the Second Dialogue State Tracking Challenge (DSTC2). Our early stage evaluations are based on comparisons of our tracker with both the baseline model provide by the DSTC2 and also LecTrack: a state-of-the-art incremental LSTM-based tracker. The main finding of our experiments is that moving from an utterance based to incremental word based tracker results in better performance for our RNN based joint task models.


Cite as: Trinh, A.D., Ross, R.J., Kelleher, J.D. (2017) Incremental Joint Modelling for Dialogue State Tracking. Proc. SEMDIAL 2017 (SaarDial) Workshop on the Semantics and Pragmatics of Dialogue, 168-169.


@inproceedings{Trinh2017,
  author={Anh Duong Trinh and Robert J. Ross and John D. Kelleher},
  title={Incremental Joint Modelling for Dialogue State Tracking},
  year=2017,
  booktitle={Proc. SEMDIAL 2017 (SaarDial) Workshop on the Semantics and Pragmatics of Dialogue},
  pages={168--169}
}