Extractive speech summarization - From the view of decision theory

Shih Hsiang Lin, Yao Ming Yeh, Berlin Chen

研究成果: 會議貢獻類型會議論文同行評審

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
頁面1684-1687
頁數4
出版狀態已發佈 - 2010 十二月 1
事件11th Annual Conference of the International Speech Communication Association: Spoken Language Processing for All, INTERSPEECH 2010 - Makuhari, Chiba, 日本
持續時間: 2010 九月 262010 九月 30

其他

其他11th Annual Conference of the International Speech Communication Association: Spoken Language Processing for All, INTERSPEECH 2010
國家日本
城市Makuhari, Chiba
期間2010/09/262010/09/30

ASJC Scopus subject areas

  • Language and Linguistics
  • Speech and Hearing

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