Estimating verbal expressions of task and social cohesion in meetings by quantifying paralinguistic mimicry

Conference Paper (2017)
Author(s)

Marjolein C. Nanninga (External organisation)

Y. Zhang (TU Delft - Pattern Recognition and Bioinformatics)

Nale Lehmann-Willenbrock (Universiteit van Amsterdam)

Zoltán Szlávik (Vrije Universiteit Amsterdam)

Hayley Hung (TU Delft - Pattern Recognition and Bioinformatics)

Research Group
Pattern Recognition and Bioinformatics
DOI related publication
https://doi.org/10.1145/3136755.3136811
More Info
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Publication Year
2017
Language
English
Research Group
Pattern Recognition and Bioinformatics
Pages (from-to)
206-215
ISBN (print)
978-1-4503-5543-8

Abstract

In this paper we propose a novel method of estimating verbal expressions of task and social cohesion by quantifying the dynamic alignment of nonverbal behaviors in speech. As team cohesion has been linked to team effectiveness and productivity, automatically estimating team cohesion can be a useful tool for assessing meeting quality and broader team functioning. In total, more than 20 hours of business meetings (3-8 people) were recorded and annotated for behavioral indicators of group cohesion, distinguishing between social and task cohesion. We hypothesized that behaviors commonly referred to as mimicry can be indicative of verbal expressions of social and task cohesion. Where most prior work targets mimicry of dyads, we investigated the effectiveness of quantifying group-level phenomena. A dynamic approach was adopted in which both the cohesion expressions and the paralinguistic mimicry were quantified on small time windows. By extracting features solely related to the alignment of paralinguistic speech behavior, we found that 2-minute high and low social cohesive regions could be classified with a 0.71 Area under the ROC curve, performing on par with the state-of-the-art where turn-taking features were used. Estimating task cohesion was more challenging, obtaining an accuracy of 0.64 AUC, outperforming the state-of-the-art. Our results suggest that our proposed methodology is successful in quantifying group-level paralinguistic mimicry. As both the state-of-the-art turn-taking features and mimicry features performed worse on estimating task cohesion, we conclude that social cohesion is more openly expressed by nonverbal vocal behavior than task cohesion

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