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Automatic meeting participant role detection by dialogue patterns
University of Dublin, Trinity College, Ireland.ORCID iD: 0000-0003-3211-6529
2010 (English)In: Development of Multimodal Interfaces: Active Listening and Synchrony: Active Listening and Synchrony / [ed] Esposito, A.; Campbell, Nick; Vogel, Carl; Hussain, Amir; Nijholt, Anton, Springer, 2010Chapter in book (Refereed)
Abstract [en]

We introduce a new concept of ‘Vocalization Horizon’ for automatic

speaker role detection in general meeting recordings. We demonstrate

that classification accuracy reaches 38.5% when Vocalization

Horizon and other features (i.e. vocalization duration and start time) are

available. With another type of Horizon, the Pause - Overlap Horizon, the

classification accuracy reaches 39.5%. Pauses and overlaps are also useful

vocalization features for meeting structure analysis. In our experiments,

the Bayesian Network classifier outperforms other classifiers, and is proposed

for similar applications.

Place, publisher, year, edition, pages
Springer, 2010.
Series
Lecture Notes in Computer Science
National Category
Engineering and Technology
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-56970DOI: 10.1007/978-3-642-12397-9_27ISBN: 978-3-642-12396-2 (print)OAI: oai:DiVA.org:kau-56970DiVA: diva2:1120216
Available from: 2017-07-05 Created: 2017-07-05 Last updated: 2017-07-05

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Citation style
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