Latent topic modeling of word co-occurrence information for spoken document retrieval

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

23 引文 斯高帕斯(Scopus)

摘要

In this paper, we present a word topic model (WTM) approach, discovering the co-occurrence relationship between words as well as the long-span latent topic information, for spoken document retrieval (SDR). A given document as a whole is modeled as a composite WTM model for generating an observed query. The underlying characteristics and different kinds of model structures are extensively investigated, while the performance of WTM is thoroughly analyzed and verified by comparison with a few existing retrieval models on the TDT-2 SDR task. We also attempt to incorporate part-of-speech (POS) weighting into the representations of the query observations and the WTM models for obtaining better retrieval performance.

原文英語
主出版物標題2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009
頁面3961-3964
頁數4
DOIs
出版狀態已發佈 - 2009 九月 23
事件2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, 臺灣
持續時間: 2009 四月 192009 四月 24

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2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
國家/地區臺灣
城市Taipei
期間2009/04/192009/04/24

ASJC Scopus subject areas

  • 軟體
  • 訊號處理
  • 電氣與電子工程

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