ISCA Archive Interspeech 2005
ISCA Archive Interspeech 2005

Using symbolic prominence to help design feature subsets for topic classification and clustering of natural human-human conversations

Constantinos Boulis, Mari Ostendorf

In this work, we use the output of a symbolic prominence classifier rather than acoustic cues of prominence, to improve the tasks of clustering and classification of spontaneous conversations to topics. In our experiments, we combine the output of a prominence classifier with lexical feature selection and combination methods to build improved feature subsets. Evaluated for the task of topic classification on a subset of Switchboard-I, the combination method offered a 11% relative reduction of classification error compared to using lexical-only feature selection methods; similar gains are reported for clustering.


doi: 10.21437/Interspeech.2005-299

Cite as: Boulis, C., Ostendorf, M. (2005) Using symbolic prominence to help design feature subsets for topic classification and clustering of natural human-human conversations. Proc. Interspeech 2005, 425-428, doi: 10.21437/Interspeech.2005-299

@inproceedings{boulis05_interspeech,
  author={Constantinos Boulis and Mari Ostendorf},
  title={{Using symbolic prominence to help design feature subsets for topic classification and clustering of natural human-human conversations}},
  year=2005,
  booktitle={Proc. Interspeech 2005},
  pages={425--428},
  doi={10.21437/Interspeech.2005-299}
}