Efficient Probabilistic Tracking of User Goal and Dialog History for Spoken Dialog Systems

@inproceedings{Raux2011EfficientPT,
  title={Efficient Probabilistic Tracking of User Goal and Dialog History for Spoken Dialog Systems},
  author={Antoine Raux and Yi Ma},
  booktitle={INTERSPEECH},
  year={2011}
}
In this paper, we describe Dynamic Probabilistic Ontology Trees, a new probabilistic model to track dialog state in a dialog system. Our model captures both the user goal and the history of user dialog acts using a unified Bayesian Network. We perform efficient inference using a form of blocked Gibbs sampling designed to exploit the structure of the model. Evaluation on a corpus of dialogs from the CMU Let’s Go system shows that our approach significantly outperforms a deterministic baseline… CONTINUE READING
Highly Cited
This paper has 34 citations. REVIEW CITATIONS
23 Citations
8 References
Similar Papers

Similar Papers

Loading similar papers…