Academic Commons

Presentations (Communicative Events)

Classification of Discourse Functions of Affirmative Words in Spoken Dialogue: Presentation Powerpoint Slides

Hirschberg, Julia Bell; Gravano, Agustin; Benus, Stefan; Mitchell, Shira; Vovsha, Ilia

We present results of a series of machine learning experiments that address the classification of the discourse function of single affirmative cue words such as alright, okay and mm-hm in a spoken dialogue corpus. We suggest that a simple discourse/sentential distinction is not sufficient for such words and propose two additional classification sub-tasks: identifying (a) whether such words convey acknowledgment or agreement, and (b) whether they cue the beginning or end of a discourse segment. We also study the classification of each individual word into its most common discourse functions. We show that models based on contextual features extracted from the time-aligned transcripts approach the error rate of trained human aligners.


  • thumnail for IS07-Gravano.ppt IS07-Gravano.ppt application/ 941 KB Download File

More About This Work

Academic Units
Computer Science
Proceedings of Interspeech 2007
Published Here
August 6, 2013


Presentation paper is available at

Academic Commons provides global access to research and scholarship produced at Columbia University, Barnard College, Teachers College, Union Theological Seminary and Jewish Theological Seminary. Academic Commons is managed by the Columbia University Libraries.