Combining Multiple Knowledge Sources for Discourse Segmentation

Diane J. Litman; Rebecca J. Passonneau

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arXiv · cmp-lg/9505025

Combining Multiple Knowledge Sources for Discourse Segmentation

Diane J. Litman·Rebecca J. Passonneau

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Abstract

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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Diane J. Litman, Rebecca J. Passonneau. 1995-05-10. Combining Multiple Knowledge Sources for Discourse Segmentation. https://arxiv.org/abs/cmp-lg/9505025

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