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. © 2008 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
APA
Murray, G., & Renals, S. (2008). Detecting action items in meetings. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5237 LNCS, pp. 208–213). Springer Verlag. https://doi.org/10.1007/978-3-540-85853-9_19
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