Natural gradient works efficiently in learning
Neural Computation
A computational architecture for conversation
UM '99 Proceedings of the seventh international conference on User modeling
A family of algorithms for approximate bayesian inference
A family of algorithms for approximate bayesian inference
Dynamic bayesian networks: representation, inference and learning
Dynamic bayesian networks: representation, inference and learning
Spoken dialogue management using probabilistic reasoning
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Partially observable Markov decision processes for spoken dialog systems
Computer Speech and Language
Applying POMDPs to dialog systems in the troubleshooting domain
NAACL-HLT-Dialog '07 Proceedings of the Workshop on Bridging the Gap: Academic and Industrial Research in Dialog Technologies
Training a real-world POMDP-based dialogue system
NAACL-HLT-Dialog '07 Proceedings of the Workshop on Bridging the Gap: Academic and Industrial Research in Dialog Technologies
EACL '06 Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations
Agenda-based user simulation for bootstrapping a POMDP dialogue system
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
Journal of Artificial Intelligence Research
Planning and acting in partially observable stochastic domains
Artificial Intelligence
Tractable inference for complex stochastic processes
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Scaling POMDPs for Spoken Dialog Management
IEEE Transactions on Audio, Speech, and Language Processing
Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
Phrase-based statistical language generation using graphical models and active learning
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Towards relational POMDPs for adaptive dialogue management
ACLstudent '10 Proceedings of the ACL 2010 Student Research Workshop
Probabilistic ontology trees for belief tracking in dialog systems
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Representing uncertainty about complex user goals in statistical dialogue systems
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Effective handling of dialogue state in the hidden information state POMDP-based dialogue manager
ACM Transactions on Speech and Language Processing (TSLP)
ACM Transactions on Speech and Language Processing (TSLP)
Reinforcement learning for parameter estimation in statistical spoken dialogue systems
Computer Speech and Language
An empirical evaluation of a statistical dialog system in public use
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
Learning automata-based approach to learn dialogue policies in large state space
International Journal of Intelligent Information and Database Systems
A case base planning approach for dialogue generation in digital movie design
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
A statistical spoken dialogue system using complex user goals and value directed compression
EACL '12 Proceedings of the Demonstrations at the 13th Conference of the European Chapter of the Association for Computational Linguistics
A belief tracking challenge task for spoken dialog systems
SDCTD '12 NAACL-HLT Workshop on Future Directions and Needs in the Spoken Dialog Community: Tools and Data
An unsupervised approach to user simulation: toward self-improving dialog systems
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
The effect of cognitive load on a statistical dialogue system
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Reinforcement learning of question-answering dialogue policies for virtual museum guides
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Landmark-based location belief tracking in a spoken dialog system
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Probabilistic dialogue models with prior domain knowledge
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Exploiting machine-transcribed dialog corpus to improve multiple dialog states tracking methods
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Integrating incremental speech recognition and POMDP-based dialogue systems
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Social signal and user adaptation in reinforcement learning-based dialogue management
Proceedings of the 2nd Workshop on Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action and Communication
Spoken language processing: where do we go from here?
Your Virtual Butler
Gaussian Processes for POMDP-Based Dialogue Manager Optimization
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
| Hi-index | 0.00 |
This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on the partially observable Markov decision process (POMDP), which provides a well-founded, statistical model of spoken dialogue management. However, exact belief state updates in a POMDP model are computationally intractable so approximate methods must be used. This paper presents a tractable method based on the loopy belief propagation algorithm. Various simplifications are made, which improve the efficiency significantly compared to the original algorithm as well as compared to other POMDP-based dialogue state updating approaches. A second contribution of this paper is a method for learning in spoken dialogue systems which uses a component-based policy with the episodic Natural Actor Critic algorithm. The framework proposed in this paper was tested on both simulations and in a user trial. Both indicated that using Bayesian updates of the dialogue state significantly outperforms traditional definitions of the dialogue state. Policy learning worked effectively and the learned policy outperformed all others on simulations. In user trials the learned policy was also competitive, although its optimality was less conclusive. Overall, the Bayesian update of dialogue state framework was shown to be a feasible and effective approach to building real-world POMDP-based dialogue systems.