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16

ICASSP
2008
IEEE

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Rhetorical-State Hidden Markov Models for extractive speech summarization

13 years 10 months ago

Rhetorical-State Hidden Markov Models for extractive speech summarization

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We propose an extractive summarization system with a novel non-generative probabilistic framework for speech summarization. One of the most underutilized features in extractive summarization is rhetorical information – semantically cohesive units that are hidden in spoken documents. We propose Rhetorical-State Hidden Markov Models (RSHMMs) to automatically decode this underlying

Pascale Fung, Ricky Ho Yin Chan, Justin Jian Zhang

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Extractive Summarization | ICASSP 2008 | Non-generative Probabilistic Framework | Signal Processing | Speech Summarization |

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Added	30 May 2010
Updated	30 May 2010
Type	Conference
Year	2008
Where	ICASSP
Authors	Pascale Fung, Ricky Ho Yin Chan, Justin Jian Zhang

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