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Volumn , Issue , 2010, Pages 5302-5305

Learning deep rhetorical structure for extractive speech summarization

Author keywords

Lecture speech summarization; Rhetorical structure

Indexed keywords

DEEP LEARNING; ITERATIVE METHODS; TEXT PROCESSING;

EID: 78049390752     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2010.5494970     Document Type: Conference Paper
Times cited : (5)

References (12)
  • 1
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    • J.J. Zhang, H.Y. Chan, and P. Fung, "Improving lecture speech summarization using rhetorical information," ASRU2007, pp. 195-200, 2007.
    • (2007) ASRU2007 , pp. 195-200
    • Zhang, J.J.1    Chan, H.Y.2    Fung, P.3
  • 2
    • 0040078056 scopus 로고    scopus 로고
    • Summarizing scientific articles: Experiments with relevance and rhetorical status
    • S. Teufel and M. Moens, "Summarizing scientific articles: experiments with relevance and rhetorical status," Computational Linguistics, vol. 28, no. 4, pp. 409-445, 2002.
    • (2002) Computational Linguistics , vol.28 , Issue.4 , pp. 409-445
    • Teufel, S.1    Moens, M.2
  • 3
    • 84867215960 scopus 로고    scopus 로고
    • Class Lecture Summarization Taking into Account Consecutiveness of Important Sentences
    • Y. Furui, K. Yamamoto, N. Kitaoka, and S. Nakagawa, "Class Lecture Summarization Taking into Account Consecutiveness of Important Sentences," Proceedings of Interspeech 2008, pp. 2438-2441, 2008.
    • (2008) Proceedings of Interspeech 2008 , pp. 2438-2441
    • Furui, Y.1    Yamamoto, K.2    Kitaoka, N.3    Nakagawa, S.4
  • 4
    • 42949097256 scopus 로고    scopus 로고
    • One story, one flow: Hidden Markov Story Models for multilingual multidocument summarization
    • P. Fung and G. Ngai, "One story, one flow: Hidden Markov Story Models for multilingual multidocument summarization," ACMTransactions on Speech and Language Processing (TSLP), vol. 3, no. 2, pp. 1-16, 2006.
    • (2006) ACMTransactions on Speech and Language Processing (TSLP) , vol.3 , Issue.2 , pp. 1-16
    • Fung, P.1    Ngai, G.2
  • 5
    • 85029434098 scopus 로고    scopus 로고
    • Catching the drift: Probabilistic content models, with applications to generation and summarization
    • R. Barzilay and L. Lee, "Catching the drift: Probabilistic content models, with applications to generation and summarization," Proceedings of HLT-NAACL, pp. 113-120, 2004.
    • (2004) Proceedings of HLT-NAACL , pp. 113-120
    • Barzilay, R.1    Lee, L.2
  • 6
    • 51449090158 scopus 로고    scopus 로고
    • Rhetorical-State Hidden Markov Models for Extractive Speech Summarization
    • P. Fung, R. Chan, and J.J Zhang, "Rhetorical-State Hidden Markov Models For Extractive Speech Summarization," ICASSP2008. Proceedings, pp. 4957-4960, 2008.
    • (2008) ICASSP2008. Proceedings , pp. 4957-4960
    • Fung, P.1    Chan, R.2    Zhang, J.J.3
  • 8
    • 79951784751 scopus 로고    scopus 로고
    • Automatic summarization of broadcast news using structural features
    • S. Maskey and J. Hirschberg, "Automatic summarization of broadcast news using structural features," Proceedings of Eurospeech 2003, 2003.
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    • Maskey, S.1    Hirschberg, J.2
  • 9
    • 56149107139 scopus 로고    scopus 로고
    • Extractive Chinese Spoken Document Summarization Using Probabilistic Ranking Models
    • YT Chen et al., "Extractive Chinese Spoken Document Summarization Using Probabilistic Ranking Models," Proc. ISCSLP, 2006.
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  • 12
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    • Active Learning of Extractive Reference Summaries for Lecture Speech Summarization
    • J.J. Zhang and P. Fung, "Active Learning of Extractive Reference Summaries for Lecture Speech Summarization," ACL-IJCNLP 2009, p. 23.
    • ACL-IJCNLP 2009 , pp. 23
    • Zhang, J.J.1    Fung, P.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.