Detecting Action Items in Meetings

  • Gabriel Murray
  • Steve Renals
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5237)


We present a method for detecting action items in spontaneous meeting speech. Using a supervised approach incorporating prosodic, lexical and structural features, we can classify such items with a high degree of accuracy. We also examine how well various feature subclasses can perform this task on their own.


Feature Subset Automatic Speech Recognition Action Item Prosodic Feature Automatic Speech Recognition System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Gabriel Murray
    • 1
  • Steve Renals
    • 2
  1. 1.University of British ColumbiaVancouverCanada
  2. 2.University of EdinburghEdinburghScotland

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