A probabilistic generative framework for extractive broadcast news speech summarization

IEEE Transactions on Audio, Speech and Language Processing

Volumn 17, Issue 1, 2009, Pages 95-106

  Chen, Yi Ting ^a   Chen, Berlin ^a   Wang, Hsin Min ^b  

^a NATIONAL TAIWAN NORMAL UNIVERSITY   (Taiwan)

^b INSTITUTE OF INFORMATION SCIENCE   (Taiwan)

Author keywords

Extractive spoken document summarization; Language model (LM); Probabilistic generative framework; Relevance model (RM); Topical mixture model

Indexed keywords

EXTRACTIVE SPOKEN DOCUMENT SUMMARIZATION; LANGUAGE MODEL (LM); PROBABILISTIC GENERATIVE FRAMEWORK; RELEVANCE MODEL (RM); TOPICAL MIXTURE MODEL;

COMPUTATIONAL LINGUISTICS; LAGRANGE MULTIPLIERS; MIXTURES; SPEECH RECOGNITION;

PROBABILITY;

EID: 67149133555     PISSN: 15587916     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASL.2008.2005031     Document Type: Article

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