Exploring the Structure of Broadcast News for Topic Segmentation

  • Authors:
  • Rui Amaral;Isabel Trancoso

  • Affiliations:
  • Instituto Superior Técnico, and Instituto Politécnico de Setúbal, and L2F - Spoken Language Systems Lab, INESC-ID, Portugal;Instituto Superior Técnico, and L2F - Spoken Language Systems Lab, INESC-ID, Portugal

  • Venue:
  • Human Language Technology. Challenges of the Information Society
  • Year:
  • 2009

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Abstract

This paper describes our on-going work toward the improvement of Broadcast News story segmentation module. We have tried to improve our baseline algorithm by further exploring the typical structure of a broadcast news show, first by training a CART and then by integrating it in a 2-stage algorithm that is able to deal with shows with double anchors. In order to deal with shows with a thematic anchor, a more complex approach is adopted including a topic classification stage. The automatic segmentation is currently being compared with the manual segmentation done by a professional media watch company. The results are very promising so far, specially taking into account that no video information is used.