Ninth International Conference on Spoken Language Processing

Pittsburgh, PA, USA
September 17-21, 2006

Efficient Interactive Retrieval of Spoken Documents with Key Terms Ranked by Reinforcement Learning

Yi-cheng Pan, Jia-yu Chen, Yen-shin Lee, Yi-sheng Fu, Lin-shan Lee

National Taiwan University, Taiwan

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.

Full Paper

Bibliographic reference.  Pan, Yi-cheng / Chen, Jia-yu / Lee, Yen-shin / Fu, Yi-sheng / Lee, Lin-shan (2006): "Efficient interactive retrieval of spoken documents with key terms ranked by reinforcement learning", In INTERSPEECH-2006, paper 1577-Mon2WeO.4.