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Contrasting the interaction structure of an email and a telephone corpus: A machine learning approach to annotation of dialogue function units

  • Columbia University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

We present a dialogue annotation scheme for both spoken and written interaction, and use it in a telephone transaction corpus and an email corpus. We train classifiers, comparing regular SVM and structured SVM against a heuristic baseline. We provide a novel application of structured SVM to predicting relations between instance pairs.

Original languageEnglish
Title of host publicationProceedings of the SIGDIAL 2009 Conference
Subtitle of host publication10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
PublisherAssociation for Computational Linguistics (ACL)
Pages357-366
Number of pages10
ISBN (Print)9781932432640
StatePublished - 2009
Event10th Annual Meeting of the Special Interest Group on Discourse and Dialogue, SIGDIAL 2009 - London, United Kingdom
Duration: Sep 11 2009Sep 12 2009

Publication series

NameProceedings of the SIGDIAL 2009 Conference: 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue

Conference

Conference10th Annual Meeting of the Special Interest Group on Discourse and Dialogue, SIGDIAL 2009
Country/TerritoryUnited Kingdom
CityLondon
Period09/11/0909/12/09

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