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Training and domain adaptation for supervised text segmentation
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Manual Annotation of Opinion Categories in Meetings
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Abstract:
This paper applies the categories from an opinion annotation scheme developed for monologue text to the genre of multiparty meetings. We describe modifications to the coding guidelines that were required to extend the categories to the new type of data, and present the results of an inter-annotator agreement study. As researchers have found with other types of annotations in speech data, inter-annotator agreement is higher when the annotators both read and listen to the data than when they only read the transcripts. Previous work exploited prosodic clues to perform automatic detection of speaker emotion (Liscombe et al. 2003). Our findings suggest that doing so to recognize opinion categories would be a promising line of work.
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URL: http://d-scholarship.pitt.edu/23276/
http://dl.acm.org/citation.cfm?id=1641991.1641998
http://d-scholarship.pitt.edu/23276/1/licence.txt
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OpinionFinder: a system for subjectivity analysis
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Wilson, Theresa; Hoffmann, Paul; Somasundaran, Swapna; Kessler, Jason; Wiebe, Janyce; Choi, Yejin; Cardie, Claire; Patwardhan, Siddharth; Riloff, Ellen M.. - : Association for Computational Linguistics, 2005
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