Automatic Recognition of Emergent Social Roles in Small Group Interactions

This paper investigates the automatic recognition of social roles that emerge naturally in small groups. These roles represent a flexible classification scheme that can generalize across different scenarios of small group interaction. We systematically investigate various verbal and non-verbal cues...

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Bibliographic Details
Published in:IEEE transactions on multimedia 2015-05, Vol.17 (5), p.746-760
Main Authors: Sapru, Ashtosh, Bourlard, Herve
Format: Article
Language:English
Subjects:
Accuracy
Automation
Categories
Classification
Conditional random fields
crowdsourcing
Cues
Feature extraction
Fields (mathematics)
Hidden Markov models
Linguistics
Meetings
Multimedia
Psychology
Recognition
small group interactions
social roles
Speech
Speech recognition
Support vector machines
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Summary:This paper investigates the automatic recognition of social roles that emerge naturally in small groups. These roles represent a flexible classification scheme that can generalize across different scenarios of small group interaction. We systematically investigate various verbal and non-verbal cues extracted from turn-taking patterns, vocal expression, and linguistic style to model speakers behavior. The influence of social roles on the behavior cues exhibited by a speaker is modeled using a discriminative approach based on conditional random fields. Experiments performed on several hours of meeting data reveal that social role recognition using conditional random fields achieves an accuracy of 74% in classifying four social roles and outperforms the baseline method on all social role categories . Furthermore , we also demonstrate the effectiveness of our approach by evaluating it on previously unseen scenarios of small group interactions.
ISSN:1520-9210
1941-0077
DOI:10.1109/TMM.2015.2408437