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Fine-grained hidden markov modeling for broadcast-news story segmentation
2001
Proceedings of the first international conference on Human language technology research - HLT '01
unpublished
Preserved Fulltext
We present the design and development of a Hidden Markov Model for the division of news broadcasts into story segments. Model topology, and the textual features used, are discussed, together with the non-parametric estimation techniques that were employed for obtaining estimates for both transition and observation probabilities. Visualization methods developed for the analysis of system performance are also presented.
doi:10.3115/1072133.1072181
fatcat:dn3445n235a7xnxlj3qnlsycbe