COVID-19: Affect recognition through voice analysis during the winter lockdown in Scotland

Sofia de la Fuente Garcia, Fasih Haider, Saturnino Luz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

The COVID-19 pandemic has led to unprecedented restrictions in people's lifestyle which have affected their psychological wellbeing. In this context, this paper investigates the use of social signal processing techniques for remote assessment of emotions. It presents a machine learning method for affect recognition applied to recordings taken during the COVID-19 winter lockdown in Scotland (UK). This method is exclusively based on acoustic features extracted from voice recordings collected through home and mobile devices (i.e. phones, tablets), thus providing insight into the feasibility of monitoring people's psychological wellbeing remotely, automatically and at scale. The proposed model is able to predict affect with a concordance correlation coefficient of 0.4230 (using Random Forest) and 0.3354 (using Decision Trees) for arousal and valence respectively.Clinical relevance- In 2018/2019, 12% and 14% of Scottish adults reported depression and anxiety symptoms. Remote emotion recognition through home devices would support the detection of these difficulties, which are often underdiagnosed and, if untreated, may lead to temporal or chronic disability.

Original languageEnglish
Title of host publication2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Pages2326-2329
Number of pages4
Volume2021
DOIs
Publication statusPublished - 1 Nov 2021
Event43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, Mexico
Duration: 1 Nov 20215 Nov 2021

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISSN (Print)2375-7477

Conference

Conference43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
Country/TerritoryMexico
CityVirtual, Online
Period1/11/215/11/21

Keywords / Materials (for Non-textual outputs)

  • COVID-19
  • Communicable Disease Control
  • Humans
  • Pandemics
  • SARS-CoV-2
  • Scotland

Fingerprint

Dive into the research topics of 'COVID-19: Affect recognition through voice analysis during the winter lockdown in Scotland'. Together they form a unique fingerprint.

Cite this