Policy Learning for Domain Selection in an Extensible Multi-domain Spoken Dialogue System

@inproceedings{Wang2014PolicyLF,
  title={Policy Learning for Domain Selection in an Extensible Multi-domain Spoken Dialogue System},
  author={Zhuoran Wang and Hongliang Chen and Guanchun Wang and Hao Tian and Hua Wu and Haifeng Wang},
  booktitle={EMNLP},
  year={2014}
}
This paper proposes a Markov Decision Process and reinforcement learning based approach for domain selection in a multidomain Spoken Dialogue System built on a distributed architecture. In the proposed framework, the domain selection problem is treated as sequential planning instead of classification, such that confirmation and clarification interaction mechanisms are supported. In addition, it is shown that by using a model parameter tying trick, the extensibility of the system can be… CONTINUE READING
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An overview of end-to-end language understanding and dialog management for personal digital assistants

2016 IEEE Spoken Language Technology Workshop (SLT) • 2016
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