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Remote smartphone-based speech collection: Acceptance and barriers in individuals with major depressive disorder

Dineley, J; Lavelle, G; Leightley, D; Matcham, F; Siddi, S; Peñarrubia-María, MT; White, KM; ... Cummins, N; + view all (2021) Remote smartphone-based speech collection: Acceptance and barriers in individuals with major depressive disorder. In: Proceedings of Interspeech 2021. (pp. pp. 631-635). International Speech Communication Association (ISCA): Brno, Czechia. Green open access

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Abstract

The ease of in-the-wild speech recording using smartphones has sparked considerable interest in the combined application of speech, remote measurement technology (RMT) and advanced analytics as a research and healthcare tool. For this to be realised, the acceptability of remote speech collection to the user must be established, in addition to feasibility from an analytical perspective. To understand the acceptance, facilitators, and barriers of smartphone-based speech recording, we invited 384 individuals with major depressive disorder (MDD) from the Remote Assessment of Disease and Relapse - Central Nervous System (RADAR-CNS) research programme in Spain and the UK to complete a survey on their experiences recording their speech. In this analysis, we demonstrate that study participants were more comfortable completing a scripted speech task than a free speech task. For both speech tasks, we found depression severity and country to be significant predictors of comfort. Not seeing smartphone notifications of the scheduled speech tasks, low mood and forgetfulness were the most commonly reported obstacles to providing speech recordings.

Type: Proceedings paper
Title: Remote smartphone-based speech collection: Acceptance and barriers in individuals with major depressive disorder
Event: Interspeech 2021
ISBN-13: 9781713836902
Open access status: An open access version is available from UCL Discovery
DOI: 10.21437/Interspeech.2021-1240
Publisher version: http://doi.org/10.21437/Interspeech.2021-1240
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology
URI: https://discovery.ucl.ac.uk/id/eprint/10139611
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