A belief tracking challenge task for spoken dialog systems

SDCTD 2012 - NAACL-HLT Workshop on Future Directions and Needs in the Spoken Dialog Community: Tools and Data

Volumn , Issue , 2012, Pages 23-24

  Williams, Jason D ^a  

^a MICROSOFT RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

'CURRENT; DESIGN ISSUES; EVALUATION DESIGN; SPOKEN DIALOGUE; SPOKEN DIALOGUE SYSTEM; TASK-BASED;

EID: 84987794710     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

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2. D Bohus and AI Rudnicky. 2006. A 'K hypotheses + other' belief updating model. In Proc AAAI Workshop on Statistical and Empirical Approaches for Spoken Dialogue Systems, Boston.
3. H Higashinaka, M Nakano, and K Aikawa. 2003. Corpus-based discourse understanding in spoken dialogue systems. In Proc ACL, Sapporo.
4. N Mehta, R Gupta, A Raux, D Ramachandran, and S Krawczyk. 2010. Probabilistic ontology trees for belief tracking in dialog systems. In Proc SIGdial Workshop on Discourse and Dialogue, Tokyo, Japan.
5. T Paek and E Horvitz. 2000. Conversation as action under uncertainty. In Proc Conf on Uncertainty in Artificial Intelligence (UAI), Stanford, California, pages 455-464.
6. A Raux. 2011. Informal meeting on a belief tracking challenge at interspeech.
7. B Thomson and SJ Young. 2010. Bayesian update of dialogue state: A POMDP framework for spoken dialogue systems. Computer Speech and Language, 24(4):562-588.
8. JD Williams and SJ Young. 2007. Partially observable Markov decision processes for spoken dialog systems. Computer Speech and Language, 21(2):393-422.
9. JD Williams. 2010. Incremental Partition Recombiantion for Efficient Tracking of Multiple Dialogue States. In ICASSP, Dallas, TX.
10. JD Williams. 2011. An empirical evaluation of a statistical dialog system in public use. In Proc SIGDIAL, Portland, Oregon, USA.
11. SJ Young, M Gašić, S Keizer, F Mairesse, J Schatzmann, B Thomson, and K Yu. 2009. The hidden information state model: a practical framework for POMDP-based spoken dialogue management. Computer Speech and Language.