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Multi-task learning of social psychology assessments and nonverbal features for automatic leadership identification

Authors:

Francesca Capozzi,

Cristina Becchio,

Vittorio MurinoAuthors Info & Claims

ICMI '17: Proceedings of the 19th ACM International Conference on Multimodal Interaction

Pages 451 - 455

https://doi.org/10.1145/3136755.3136812

Published: 03 November 2017 Publication History

Abstract

In social psychology, the leadership investigation is performed using questionnaires which are either i) self-administered or ii) applied to group participants to evaluate other members or iii) filled by external observers. While each of these sources is informative, using them individually might not be as effective as using them jointly. This paper is the first attempt which addresses the automatic identification of leaders in small-group meetings, by learning effective models using nonverbal audio-visual features and the results of social psychology questionnaires that reflect assessments regarding leadership. Learning is based on Multi-Task Learning which is performed without using ground-truth data (GT), but using the results of questionnaires (having substantial agreement with GT), administered to external observers and the participants of the meetings, as tasks. The results show that joint learning results in better performance as compared to single task learning and other baselines.

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Jiayu Zhou, Jianhui Chen, and Jieping Ye. 2011. MALSAR: Multi-tAsk Learning via StructurAl Regularization. Arizona State University. http://www.public.asu. edu/~jye02/Software/MALSAR Abstract 1 Introduction 2 Related Work: SSP 3 Related Work: Social Psychology 4 Dataset 5 Proposed Method 5.1 Multi-Task Learning 5.2 Audio-visual Nonverbal Features 6 Experimental Setting 7 Results 8 Conclusions References

Cited By

Thakur SBEYAN CMorerio PDel Bue A(2021)Predicting Gaze from Egocentric Social Interaction Videos and IMU DataProceedings of the 2021 International Conference on Multimodal Interaction10.1145/3462244.3479954(717-722)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1145/3462244.3479954
Morgan MBhattacharya IRadke RBraasch J(2021)Classifying the emotional speech content of participants in group meetings using convolutional long short-term memory networkThe Journal of the Acoustical Society of America10.1121/10.0003433149:2(885-894)Online publication date: Feb-2021
https://doi.org/10.1121/10.0003433
Yu ZWang ZYu ZWang Z(2020)Group Behavior RecognitionHuman Behavior Analysis: Sensing and Understanding10.1007/978-981-15-2109-6_6(139-218)Online publication date: 1-Mar-2020
https://doi.org/10.1007/978-981-15-2109-6_6
Show More Cited By

Index Terms

Multi-task learning of social psychology assessments and nonverbal features for automatic leadership identification
1. Applied computing
  1. Law, social and behavioral sciences
    1. Psychology

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Published In

cover image ACM Conferences

ICMI '17: Proceedings of the 19th ACM International Conference on Multimodal Interaction

November 2017

676 pages

ISBN:9781450355438

DOI:10.1145/3136755

General Chairs:
Edward Lank
University of Waterloo, Canada
,
Alessandro Vinciarelli
University of Glasgow, UK
,
Program Chairs:
Eve Hoggan
Aarhus University, Denmark
,
Sriram Subramanian
University of Sussex, UK
,
Stephen A. Brewster
University of Glasgow, UK

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 November 2017

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ICMI '17

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SIGCHI

ICMI '17: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION

November 13 - 17, 2017

Glasgow, UK

Acceptance Rates

ICMI '17 Paper Acceptance Rate 65 of 149 submissions, 44%;

Overall Acceptance Rate 453 of 1,080 submissions, 42%

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Cited By

Thakur SBEYAN CMorerio PDel Bue A(2021)Predicting Gaze from Egocentric Social Interaction Videos and IMU DataProceedings of the 2021 International Conference on Multimodal Interaction10.1145/3462244.3479954(717-722)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1145/3462244.3479954
Morgan MBhattacharya IRadke RBraasch J(2021)Classifying the emotional speech content of participants in group meetings using convolutional long short-term memory networkThe Journal of the Acoustical Society of America10.1121/10.0003433149:2(885-894)Online publication date: Feb-2021
https://doi.org/10.1121/10.0003433
Yu ZWang ZYu ZWang Z(2020)Group Behavior RecognitionHuman Behavior Analysis: Sensing and Understanding10.1007/978-981-15-2109-6_6(139-218)Online publication date: 1-Mar-2020
https://doi.org/10.1007/978-981-15-2109-6_6
Bhattacharya IFoley MKu CZhang NZhang TMine CLi MJi HRiedl CWelles BRadke RZink MToni LBegen A(2019)The unobtrusive group interaction (UGI) corpusProceedings of the 10th ACM Multimedia Systems Conference10.1145/3304109.3325816(249-254)Online publication date: 18-Jun-2019
https://dl.acm.org/doi/10.1145/3304109.3325816
Miller C(2018)Using Parallel Episodes of Speech to Represent and Identify Interaction Dynamics for Group MeetingsProceedings of the Group Interaction Frontiers in Technology10.1145/3279981.3279983(1-7)Online publication date: 16-Oct-2018
https://dl.acm.org/doi/10.1145/3279981.3279983
Bhattacharya ID'Mello SGeorgiou PScherer SProvost ESoleymani MWorsley M(2018)Unobtrusive Analysis of Group Interactions without CamerasProceedings of the 20th ACM International Conference on Multimodal Interaction10.1145/3242969.3264973(501-505)Online publication date: 2-Oct-2018
https://dl.acm.org/doi/10.1145/3242969.3264973
Bhattacharya IFoley MZhang NZhang TKu CMine CJi HRiedl CWelles BRadke RD'Mello SGeorgiou PScherer SProvost ESoleymani MWorsley M(2018)A Multimodal-Sensor-Enabled Room for Unobtrusive Group Meeting AnalysisProceedings of the 20th ACM International Conference on Multimodal Interaction10.1145/3242969.3243022(347-355)Online publication date: 2-Oct-2018
https://dl.acm.org/doi/10.1145/3242969.3243022
Niewiadomski RChauvigne LMancini MCamurri A(2018)Towards a model of nonverbal leadership in unstructured joint physical activityProceedings of the 5th International Conference on Movement and Computing10.1145/3212721.3212816(1-8)Online publication date: 28-Jun-2018
https://dl.acm.org/doi/10.1145/3212721.3212816
Müller PHuang MZhang XBulling ASharif BKrejtz K(2018)Robust eye contact detection in natural multi-person interactions using gaze and speaking behaviourProceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications10.1145/3204493.3204549(1-10)Online publication date: 14-Jun-2018
https://dl.acm.org/doi/10.1145/3204493.3204549

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