Insights on Modelling Physiological, Appraisal, and Affective Indicators of Stress using Audio Features

Andreas Triantafyllopoulos, Sandra Zankert, Alice Baird, Julian Konzok, Brigitte M. Kudielka, Bjorn W. Schuller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Stress is a major threat to well-being that manifests in a variety of physiological and mental symptoms. Utilising speech samples collected while the subject is undergoing an induced stress episode has recently shown promising results for the automatic characterisation of individual stress responses. In this work, we introduce new findings that shed light onto whether speech signals are suited to model physiological biomarkers, as obtained via cortisol measurements, or self-assessed appraisal and affect measurements. Our results show that different indicators impact acoustic features in a diverse way, but that their complimentary information can nevertheless be effectively harnessed by a multi-tasking architecture to improve prediction performance for all of them.

Original languageEnglish
Title of host publication44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2619-2622
Number of pages4
ISBN (Electronic)9781728127828
DOIs
StatePublished - 2022
Externally publishedYes
Event44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022 - Glasgow, United Kingdom
Duration: 11 Jul 202215 Jul 2022

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2022-July
ISSN (Print)1557-170X

Conference

Conference44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
Country/TerritoryUnited Kingdom
CityGlasgow
Period11/07/2215/07/22

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