Divided POMDP method for complex menu problems in spoken dialogue systems

In this paper, a problem in spoken dialogue systems namely the menu problem, is introduced and solved by a POMDP model. To overcome the large size of the menu problem, a new method for achieving an optimal policy called divided POMDP method is introduced. Conditions for the problem to be solved by the proposed method are specified and the problem properties resulting in the given conditions are presented. The proposed method is evaluated using a typical menu problem with different menu sizes and it is shown that this method is superior to the conventional methods such as FRTDP for the problems it is capable to solve. Moreover, it converges faster in getting to an optimal policy.

[1]  S. Young,et al.  Scaling POMDPs for Spoken Dialog Management , 2007, IEEE Transactions on Audio, Speech, and Language Processing.

[2]  Joelle Pineau,et al.  Point-based value iteration: An anytime algorithm for POMDPs , 2003, IJCAI.

[3]  Steve J. Young,et al.  Error simulation for training statistical dialogue systems , 2007, 2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU).

[4]  Hui Ye,et al.  The Hidden Information State Approach to Dialog Management , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[5]  Hui Ye,et al.  Agenda-Based User Simulation for Bootstrapping a POMDP Dialogue System , 2007, NAACL.

[6]  Reid G. Simmons,et al.  Focused Real-Time Dynamic Programming for MDPs: Squeezing More Out of a Heuristic , 2006, AAAI.

[7]  Hui Ye,et al.  Training a real-world POMDP-based Dialog System , 2007, HLT-NAACL 2007.

[8]  Steve J. Young,et al.  USING POMDPS FOR DIALOG MANAGEMENT , 2006, 2006 IEEE Spoken Language Technology Workshop.

[9]  Steve J. Young,et al.  Partially observable Markov decision processes for spoken dialog systems , 2007, Comput. Speech Lang..