Spoken document understanding and organization

Lin Shan Lee*, Berlin Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

119 Citations (Scopus)


Spoken documents associated with the network content are critical for retrieval and browsing. An overview is given of various technology areas reaching towards this goal in a unified context. Technology areas covered include named-entity (NE) extraction, segmentation, and information extraction for the spoken documents as well as automatic summarization, title generation, and topic analysis and organization. The relevant problems and issues, general principles, and basic approaches for each area are briefly reviewed. A framework for properly integrating all these different technology areas is proposed, in which four different levels of processes are defined and bottom-up and top-down relationships are discussed. An initial prototype system for such purposes has been developed by National Taiwan University. The resultant system used broadcast news in Mandarin Chinese as example spoken documents.

Original languageEnglish
Pages (from-to)42-60
Number of pages19
JournalIEEE Signal Processing Magazine
Issue number5
Publication statusPublished - 2005 Sept

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics


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