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Knowledge- and Data-Driven Models of Multimodal Trajectories of Public Speaking Anxiety in Real and Virtual Settings

Authors:

Ehsanul Haque Nirjhar,

Amir H. Behzadan,

Theodora ChaspariAuthors Info & Claims

ICMI '21: Proceedings of the 2021 International Conference on Multimodal Interaction

Pages 712 - 716

https://doi.org/10.1145/3462244.3479964

Published: 18 October 2021 Publication History

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Abstract

Public speaking skills are essential to professional success. Yet, public speaking anxiety (PSA) is considered one of the most common social phobias. Understanding PSA can help communication experts identify effective ways to treat this communication-based disorder. Existing works on PSA rely on self-reports and aggregate multimodal measures which do not capture the temporal variation in PSA. This paper examines temporal trajectories of acoustic and physiological measures throughout the public speaking encounter with real and virtual audiences, and aims to model those in both knowledge- and data-driven ways. Knowledge-driven models leverage theoretically-grounded patterns through fitting interpretable parametric functions to the corresponding signals. Data-driven models consider the functional nature of multimodal signals via functional principal component analysis. Results indicate that the parameters of the proposed models can successfully estimate individuals’ trait anxiety in both real-life and virtual reality settings, and suggest that models trained on data obtained in virtual public speaking stimuli are able to estimate levels of PSA in real-life.

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Cited By

Nirjhar E(2023)Expression and Perception of Stress Through the Lens of Multimodal Signals: A Case Study in Interpersonal Communication Settings2023 11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)10.1109/ACIIW59127.2023.10388186(1-5)Online publication date: 10-Sep-2023
https://doi.org/10.1109/ACIIW59127.2023.10388186
Kimani EBickmore TPicard RGoodwin MJimison H(2022)Real-time Public Speaking Anxiety Prediction Model for Oral PresentationsCompanion Publication of the 2022 International Conference on Multimodal Interaction10.1145/3536220.3563686(30-35)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3536220.3563686

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Published In

cover image ACM Conferences

ICMI '21: Proceedings of the 2021 International Conference on Multimodal Interaction

October 2021

876 pages

ISBN:9781450384810

DOI:10.1145/3462244

Editors:
Zakia Hammal
Carnegie Mellon University
,
Carlos Busso
University of Texas at Dallas
,
Catherine Pelachaud
CNRS - ISIR, Sorbonne University
,
Sharon Oviatt
Monash University
,
Albert Ali Salah
Utrecht University and Boğaziçi University
,
Guoying Zhao
University of Oulu

Copyright © 2021 ACM.

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Published: 18 October 2021

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ICMI '21: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION

October 18 - 22, 2021

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Cited By

Nirjhar E(2023)Expression and Perception of Stress Through the Lens of Multimodal Signals: A Case Study in Interpersonal Communication Settings2023 11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)10.1109/ACIIW59127.2023.10388186(1-5)Online publication date: 10-Sep-2023
https://doi.org/10.1109/ACIIW59127.2023.10388186
Kimani EBickmore TPicard RGoodwin MJimison H(2022)Real-time Public Speaking Anxiety Prediction Model for Oral PresentationsCompanion Publication of the 2022 International Conference on Multimodal Interaction10.1145/3536220.3563686(30-35)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3536220.3563686

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