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.
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Amaral, R., Trancoso, I. (2009). Exploring the Structure of Broadcast News for Topic Segmentation. In: Vetulani, Z., Uszkoreit, H. (eds) Human Language Technology. Challenges of the Information Society. LTC 2007. Lecture Notes in Computer Science(), vol 5603. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04235-5_1
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DOI: https://doi.org/10.1007/978-3-642-04235-5_1
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