ISCA Archive Eurospeech 1999
ISCA Archive Eurospeech 1999

Story segmentation and topic detection for recognized speech

S. Dharanipragada, Martin Franz, J. S. McCarley, Salim Roukos, T. Ward

In this paper we present algorithms for story segmentation, topic detection, and topic tracking. The algorithmsuse a combination of machine learning, statistical naturallanguage processing and information retrieval techniques.The story segmentation algorithm is a two stage algorithm that uses a decision tree based probabilistic modelin the first stage and incorporates aspects of our topicdetection system via an information-retrieval based refinement scheme in the second stage. The topic detectionand tracking algorithm is an incremental clustering algorithm that employs a novel dynamic cluster-dependentsimilarity measure between documents and clusters. Per-formance of these algorithms are measured on the 1998DARPA sponsored Topic Detection and Tracking Phase2 (TDT2) evaluation task.


doi: 10.21437/Eurospeech.1999-535

Cite as: Dharanipragada, S., Franz, M., McCarley, J.S., Roukos, S., Ward, T. (1999) Story segmentation and topic detection for recognized speech. Proc. 6th European Conference on Speech Communication and Technology (Eurospeech 1999), 2435-2438, doi: 10.21437/Eurospeech.1999-535

@inproceedings{dharanipragada99_eurospeech,
  author={S. Dharanipragada and Martin Franz and J. S. McCarley and Salim Roukos and T. Ward},
  title={{Story segmentation and topic detection for recognized speech}},
  year=1999,
  booktitle={Proc. 6th European Conference on Speech Communication and Technology (Eurospeech 1999)},
  pages={2435--2438},
  doi={10.21437/Eurospeech.1999-535}
}