Learning what to say and how to say it: Joint optimisation of spoken dialogue management and natural language generation

Computer Speech and Language

Volumn 25, Issue 2, 2011, Pages 210-221

  Lemon, Oliver ^a  

^a HERIOT WATT UNIVERSITY   (United Kingdom)

Author keywords

Dialogue systems; Natural Language Generation; Reinforcement Learning

Indexed keywords

ADAPTIVE INFORMATION PRESENTATION; AUTOMATIC-LEARNING; DIALOGUE MANAGEMENT; DIALOGUE SYSTEMS; GENERALISATION; MULTIMODAL DIALOGUE SYSTEMS; NATURAL LANGUAGE GENERATION; OPTIMISATIONS; SPOKEN DIALOGUE;

REINFORCEMENT LEARNING; SPEECH PROCESSING;

OPTIMIZATION;

EID: 78049528068     PISSN: 08852308     EISSN: 10958363     Source Type: Journal    
DOI: 10.1016/j.csl.2010.04.005     Document Type: Article

References (43)

1. R. Barzilay, and M. Lapata Collective content selection for concept-to-text generation Proceedings of EMNLP 2005
2. G. Carenini, and J.D. Moore Generating and evaluating evaluative arguments Artificial Intelligence 170 11 2006 925 952
3. Cuayáhuitl, H, 2009. Hierarchical reinforcement learning for spoken dialogue systems. PhD Thesis. Edinburgh University, School of Informatics.
4. V. Demberg, and J.D. Moore Information presentation in spoken dialogue systems Proceedings of EACL 2006
5. P.A. Duboue, and K.R. McKeown Statistical acquisition of content selection rules for natural language generation Proceedings of EMNLP 2003
6. M. Frampton, and O. Lemon Learning more effective dialogue strategies using limited dialogue move features Proceedings of ACL Sydney 2006 185 192
7. S. Garrod, and M. Pickering Toward a mechanistic psychology of dialogue: the interactive alignment model Proceedings of BI-dialog 2001
8. K. Georgila, J. Henderson, and O. Lemon User simulation for spoken dialogue systems: Learning and evaluation Proceedings of Interspeech/ICSLP 2006 1065 1068
9. J. Henderson, O. Lemon, and K. Georgila Hybrid reinforcement/supervised learning of dialogue policies from fixed datasets Computational Linguistics 34 4 2008 487 512
10. A. Isard, J. Oberlander, I. Androutsopoulos, and C. Matheson Speaking the users' languages IEEE Intelligent Systems Magazine 18 1 2003 40 45
11. Janarthanam, S., Lemon, O., 2010. Learning to Adapt to Unknown Users: Referring Expression Generation in Spoken Dialogue Systems. In: Proceedings of Association for Computational Linguistics.
12. S. Janarthanam, and O. Lemon A User Simulation Model for learning Lexical Alignment Policies in Spoken Dialogue Systems European Workshop on Natural Language Generation 2009
13. S. Janarthanam, and O. Lemon A wizard-of-oz environment to study referring expression generation in a situated spoken dialogue task European Workshop on Natural Language Generation 2009
14. S. Janarthanam, and O. Lemon User simulations for online adaptation and knowledge-alignment in Troubleshooting dialogue systems Proceedings of SEMdial 2008 149 156
15. A. Koller, and M. Stone Sentence generation as planning Proceedings of ACL 2007
16. S. Larsson Coordinating on ad-hoc semantic systems in dialogue Proceedings of DECALOG 2007
17. O. Lemon, and X. Liu Dialogue policy learning for combinations of noise and user simulation: transfer results SIGdial 2007
18. O. Lemon, X. Liu, D. Shapiro, and C. Tollander Hierarchical reinforcement learning of dialogue policies in a development environment for dialogue systems: REALL-DUDE Proceedings of Brandial, the 10th SemDial Workshop on the Semantics and Pragmatics of Dialogue (demonstration systems) 2006
19. E. Levin, and R. Pieraccini A stochastic model of computer-human interaction for learning dialogue strategies Proceedings of Eurospeech 1997
20. E. Levin, R. Pieraccini, and W. Eckert A stochastic model of human-machine interaction for learning dialog strategies IEEE Transactions on Speech and Audio Processing 8 1 2000 11 23
21. J. Moore, M.E. Foster, O. Lemon, and M. White Generating tailored, comparative descriptions in spoken dialogue Proceedings of FLAIRS 2004
22. J. Moore, M.E. Foster, O. Lemon, and M. White Generating tailored, comparative descriptions in spoken dialogue The 17th International FLAIRS Conference (Florida Artifical Intelligence Research Society) 2004
23. A. Oh, and A. Rudnicky Stochastic natural language generation for spoken dialog systems, Computer Speech & Language 16 3/4 2002 387 407
24. T. Paek, and D.M. Chickering The Markov assumption in spoken dialogue management. Proceedings of the 6th SIGdial Workshop on Discourse and Dialogue 2005
25. E. Reiter, and R. Dale Building Natural Language Generation Systems 2000 CUP
26. Rieser, V, 2008. Bootstrapping Reinforcement Learning-based Dialogue Strategies from Wizard-of-Oz data. PhD Thesis, Saarbruecken Dissertations in Computational Linguistics and Language Technology,Vol. 28.
27. V. Rieser, and O. Lemon Cluster-based user simulations for learning dialogue strategies and the SUPER evaluation metric Proceedings of Interspeech/ICSLP 2006 1766 1769
28. V. Rieser, and O. Lemon Automatic learning and evaluation of user-centered objective functions for dialogue system optimisation Proceedings of LREC 2008
29. V. Rieser, and O. Lemon Learning Effective Multimodal Dialogue Strategies from Wizard-of-Oz data: Bootstrapping and Evaluation. Proceedings of ACL 2008
30. V. Rieser, and O. Lemon Natural language generation as planning under uncertainty for spoken dialogue systems EACL 2009
31. V. Rieser, and O. Lemon Learning human multimodal clarification strategies for use in dialogue systems Journal of Natural Language Engineering 16 1 2009 3 23
32. Rieser, V., Lemon, O., Liu, X., 2010. Optimising Information Presentation for Spoken Dialogue Systems. In: Proceedings of Association for Computational Linguistics.
33. S. Singh, M. Kearns, D. Litman, and M. Walker Reinforcement learning for spoken dialogue systems Advances in Neural Information Processing Systems 2000
34. S. Singh, D. Litman, M. Kearns, and M. Walker Optimizing dialogue management with reinforcement learning: experiments with the NJFun system Journal of Artificial Intelligence Research (JAIR) 16 2002 105 133
35. A. Stent, R. Prasad, and M. Walker Trainable sentence planning for complex information presentation in spoken dialog systems Association for Computational Linguistics 2004
36. M. Stone, C. Doran, B. Webber, T. Bleam, and M. Palmer Microplanning with communicative intentions: the SPUD system Computational Intelligence 19 4 2003 311 381
37. R. Sutton, and A. Barto Reinforcement Learning 1998 MIT Press
38. M. Walker, O. Rambow, and M. Rogati Spot: a trainable sentence planner Proceedings of the NAACL 2001
39. M. Walker, A. Stent, F. Mairesse, and R. Prasad Individual and domain adaptation in sentence planning for dialogue Journal of Artificial Intelligence Research (JAIR) 30 2007 413 456
40. M. Walker, S. Whittaker, A. Stent, P. Maloor, J. Moore, M. Johnston, and G. Vasireddy User tailored generation in the match multimodal dialogue system Cognitive Science 28 2004 811 840
41. M.A. Walker, J.C. Fromer, and S. Narayanan Learning optimal dialogue strategies: a case study of a spoken dialogue agent for email. Proceedings of ACL 1998
42. M.A. Walker, C.A. Kamm, and D.J. Litman Towards Developing General Models of Usability with PARADISE Natural Language Engineering 6 3 2000
43. S. Young Probabilistic methods in spoken dialogue systems Philosophical Transactions of the Royal Society (Series A) 358 1769 2000 1389 1402