Extractive speech summarization - From the view of decision theory

Shih Hsiang Lin*, Yao Ming Yeh, Berlin Chen

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

6 引文 斯高帕斯(Scopus)

摘要

Extractive speech summarization can be thought of as a decision-making process where the summarizer attempts to select a subset of informative sentences from the original document. Meanwhile, a sentence being selected as part of a summary is typically determined by three primary factors: significance, relevance and redundancy. To meet these specifications, we recently presented a novel probabilistic framework stemming from the Bayes decision theory for extractive speech summarization. It not only inherits the merits of several existing summarization techniques but also provides a flexible mechanism to render the redundancy and coherence relationships among sentences and between sentences and the whole document, respectively. In this paper, we propose several new approaches to the ranking strategy and modeling paradigm involved in such a framework. All experiments reported were carried out on a broadcast news speech summarization task; very promising results were demonstrated.

原文英語
主出版物標題Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010
發行者International Speech Communication Association
頁面1684-1687
頁數4
出版狀態已發佈 - 2010

出版系列

名字Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010

ASJC Scopus subject areas

  • 語言與語言學
  • 言語和聽力

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