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2011
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Automatic minute generation for parliamentary speech using conditional random fields

8 years 9 months ago
Automatic minute generation for parliamentary speech using conditional random fields
We show a novel approach of automatically generating minutes style extractive summaries for parliamentary speech. Minutes are structured summaries consisting of sequences of business items with sub-summaries. We propose to model minute structures as a rhetorical syntax tree. We also propose to use a single Conditional Random Field classifier to carry out the chunking and parsing of a parliamentary speech according to this syntax tree, and extracting salient sentences, all in one step, to form a meeting minute automatically. We show that this one step minute generation system outperforms a more traditional two step system where a first classifier is used for chunking and parsing and a second classifier is used for sentence extraction, from 69.5% to 73.2% in ROUGE-L measure. We also show comparative results from different features in the classifier and found that acoustic features contribute similarly to the final performance as N-gram features from ASR output.
Justin Jian Zhang, Pascale Fung, Ricky Ho Yin Chan
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Justin Jian Zhang, Pascale Fung, Ricky Ho Yin Chan
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