8th International Conference on Spoken Language Processing

Jeju Island, Korea
October 4-8, 2004

Learning Subject Drift for Topic Tracking

Fumiyo Fukumoto, Yoshimi Suzuki

University of Yamanashi, Japan

For topic tracking where data is collected over an extended period of time, the discussion of a topic, i.e. the subject in a story changes over time. This paper focuses on subject drift and presents a method for topic tracking on broadcast news stories to handle subject drift. The basic idea is to automatically extract the optimal positive training data of the target topic so as to include only the data which are sufficiently related to the current subject. The method was tested on the TDT1 and TDT2, and the results show the effectiveness of the method.

Full Paper

Bibliographic reference.  Fukumoto, Fumiyo / Suzuki, Yoshimi (2004): "Learning subject drift for topic tracking", In INTERSPEECH-2004, 573-576.