Detecting Action Items in Meetings

  • Authors:
  • Gabriel Murray;Steve Renals

  • Affiliations:
  • University of British Columbia, Vancouver, Canada;University of Edinburgh, Edinburgh, Scotland

  • Venue:
  • MLMI '08 Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

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.