Efficient interactive retrieval of spoken documents with key terms ranked by reinforcement learning
Yicheng Pan, Jiayu Chen, Yen-shin Lee, Yi-sheng Fu, Lin-shan Lee · 2006
Unlike written documents, spoken documents are difficult to display on the screen; it is also difficult for users to browse these documents during retrieval.It has been proposed recently to use interactive multi-modal dialogues to help the user navigate through a spoken document archive to retrieve the desired documents.This interaction is based on a topic hierarchy constructed by the key terms extracted from the retrieved spoken documents.In this paper, the efficiency of the user interaction in such a system is further improved by a key term ranking algorithm using Reinforcement Learning with simulated users.Significant improvements in retrieval efficiency, which are relatively robust to the speech recognition errors, are observed in preliminary evaluations.