A comparative study of probabilistic ranking models for spoken document summarization

Shih Hsiang Lin, Yi Ting Chen, Hsin Min Wang, Berlin Chen

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

The purpose of extractive document summarization is to automatically select a number of indicative sentences, passages, or paragraphs from the original document according to a target summarization ratio and then sequence them to form a concise summary. In the paper, we present a comparative study of various supervised and unsupervised probabilistic ranking models for spoken document summarization on the Chinese broadcast news. Moreover, we also investigate the possibility of using unsupervised summarizers to boost the performance of supervised summarizers when manual labels are not available for the training of supervised summarizers. Encouraging results were initially demonstrated.

原文英語
主出版物標題2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
頁面5025-5028
頁數4
DOIs
出版狀態已發佈 - 2008 九月 16
事件2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, 美国
持續時間: 2008 三月 312008 四月 4

出版系列

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

其他

其他2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
國家/地區美国
城市Las Vegas, NV
期間2008/03/312008/04/04

ASJC Scopus subject areas

  • 軟體
  • 訊號處理
  • 電氣與電子工程

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