A Chinese spoken dialogue system for train information

In this paper a Chinese spoken dialogue system developed for train information retrieval is presented. After a brief description of the system architecture and the individual modules, a dialogue manager, which integrates user plan inference with the topic tree model, is proposed. Also dialogue strategies based on this mechanism, including consistent information sharing across multiple topics, reliable user response expectation and proper system prompt design, are presented and explained in detail. Experiments show that sentence meaning understanding error rate decreased by 23.5% with the guide of user plan inference. Preliminary subjective evaluation shows that the users are interested and willing to talk with the system although there´s still much to be improved.