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Automatic Summarization of Broadcast News using Structural Features

Hirschberg, Julia Bell; Maskey, Sameer Raj

We present a method for summarizing broadcast news that is not affected by word errors in an automatic speech recognition transcription, using information about the structure of the news program. We construct a directed graphical model to represent the probability distribution and dependencies among the structural features which we train by finding the values of parameters of the conditional probability tables. We then rank segments of the test set and extract the highest ranked ones as a summary. We present the procedure and preliminary test results.

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More About This Work

Academic Units
Computer Science
Publisher
Proceedings of Eurospeech 2003
Published Here
May 17, 2013
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