Improved spoken document summarization with coverage modeling techniques

Kuan Yu Chen, Shih Hung Liu, Berlin Chen, Hsin Min Wang

研究成果: 書貢獻/報告類型會議論文篇章

3 引文 斯高帕斯(Scopus)

摘要

Extractive summarization aims at selecting a set of indicative sentences from a source document as a summary that can express the major theme of the document. A general consensus on extractive summarization is that both relevance and coverage are critical issues to address. The existing methods designed to model coverage can be characterized by either reducing redundancy or increasing diversity in the summary. Maximal margin relevance (MMR) is a widely-cited method since it takes both relevance and redundancy into account when generating a summary for a given document. In addition to MMR, there is only a dearth of research concentrating on reducing redundancy or increasing diversity for the spoken document summarization task, as far as we are aware. Motivated by these observations, two major contributions are presented in this paper. First, in contrast to MMR, which considers coverage by reducing redundancy, we propose two novel coverage-based methods, which directly increase diversity. With the proposed methods, a set of representative sentences, which not only are relevant to the given document but also cover most of the important sub-themes of the document, can be selected automatically. Second, we make a step forward to plug in several document/sentence representation methods into the proposed framework to further enhance the summarization performance. A series of empirical evaluations demonstrate the effectiveness of our proposed methods.

原文英語
主出版物標題2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面6010-6014
頁數5
ISBN(電子)9781479999880
DOIs
出版狀態已發佈 - 2016 五月 18
事件41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, 中国
持續時間: 2016 三月 202016 三月 25

出版系列

名字ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2016-May
ISSN(列印)1520-6149

其他

其他41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
國家/地區中国
城市Shanghai
期間2016/03/202016/03/25

ASJC Scopus subject areas

  • 軟體
  • 訊號處理
  • 電氣與電子工程

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