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ACL
2006

Minimum Cut Model for Spoken Lecture Segmentation

11 years 7 months ago
Minimum Cut Model for Spoken Lecture Segmentation
We consider the task of unsupervised lecture segmentation. We formalize segmentation as a graph-partitioning task that optimizes the normalized cut criterion. Our approach moves beyond localized comparisons and takes into account longrange cohesion dependencies. Our results demonstrate that global analysis improves the segmentation accuracy and is robust in the presence of speech recognition errors.
Igor Malioutov, Regina Barzilay
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where ACL
Authors Igor Malioutov, Regina Barzilay
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