Combining Multiple Knowledge Sources for Discourse Segmentation

Details Combining Multiple Knowledge Sources for Discourse Segmentation Combining Multiple Knowledge Sources for Discourse Segmentation

1995-05-10

arxiv.org/abs/cmp-lg/9505025v1

Computer Science

Computation and Language

8 pages. Self-contained latex source. To appear in Proceedings of the 33rd ACL, 1995. (This replacement version revised so tha

Scientific paper

We predict discourse segment boundaries from linguistic features of utterances, using a corpus of spoken narratives as data. We present two methods for developing segmentation algorithms from training data: hand tuning and machine learning. When multiple types of features are used, results approach human performance on an independent test set (both methods), and using cross-validation (machine learning).

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