Chinese spoken document summarization using probabilistic latent topical information

Berlin Chen*, Yao Ming Yeh, Yao Min Huang, Yi Ting 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

19 引文 斯高帕斯(Scopus)

摘要

The purpose of extractive 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 proposed the use of probabilistic latent topical information for extractive summarization of spoken documents. Various kinds of modeling structures and learning approaches were extensively investigated. In addition, the summarization capabilities were verified by comparison with the conventional vector space model and latent semantic indexing model, as well as the HMM model. The experiments were performed on the Chinese broadcast news collected in Taiwan. Noticeable performance gains were obtained.

原文英語
主出版物標題2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
出版狀態已發佈 - 2006 十二月 1
事件2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, 法国
持續時間: 2006 五月 142006 五月 19

出版系列

名字ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
1
ISSN(列印)1520-6149

其他

其他2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
國家/地區法国
城市Toulouse
期間2006/05/142006/05/19

ASJC Scopus subject areas

  • 軟體
  • 訊號處理
  • 電氣與電子工程

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