Exploring features and classifiers for dialogue act segmentation

  • Den Akker H
  • Schulz C
  • 8


    Mendeley users who have this article in their library.
  • 4


    Citations of this article.


This paper takes a classical machine learning approach to the task of dialogue act segmentation. A thorough empirical evaluation of features, both used in other studies as well as new ones, is performed. An explorative study to the e ectiveness of di erent classi cation methods is done by looking at 29 di erent classi ers implemented in WEKA. The output of the developed classi er is examined closely and points of possible improvement are given.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Get full text


  • Harm Op Den Akker

  • Christian Schulz

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free