Towards robust paralinguistic assessment for real-world mobile health (mHealth) monitoring: an initial study of reverberation effects on speech

Fuente: arXiv
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Main Authors: Dineley, Judith, Carr, Ewan, Matcham, Faith, Downs, Johnny, Dobson, Richard, Quatieri, Thomas F, Cummins, Nicholas
Format: Preprint
Published: 2023
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author Dineley, Judith
Carr, Ewan
Matcham, Faith
Downs, Johnny
Dobson, Richard
Quatieri, Thomas F
Cummins, Nicholas
author_facet Dineley, Judith
Carr, Ewan
Matcham, Faith
Downs, Johnny
Dobson, Richard
Quatieri, Thomas F
Cummins, Nicholas
contents Speech is promising as an objective, convenient tool to monitor health remotely over time using mobile devices. Numerous paralinguistic features have been demonstrated to contain salient information related to an individual's health. However, mobile device specification and acoustic environments vary widely, risking the reliability of the extracted features. In an initial step towards quantifying these effects, we report the variability of 13 exemplar paralinguistic features commonly reported in the speech-health literature and extracted from the speech of 42 healthy volunteers recorded consecutively in rooms with low and high reverberation with one budget and two higher-end smartphones and a condenser microphone. Our results show reverberation has a clear effect on several features, in particular voice quality markers. They point to new research directions investigating how best to record and process in-the-wild speech for reliable longitudinal health state assessment.
format Preprint
id arxiv_https___arxiv_org_abs_2305_12514
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Towards robust paralinguistic assessment for real-world mobile health (mHealth) monitoring: an initial study of reverberation effects on speech
Dineley, Judith
Carr, Ewan
Matcham, Faith
Downs, Johnny
Dobson, Richard
Quatieri, Thomas F
Cummins, Nicholas
Sound
Audio and Speech Processing
Speech is promising as an objective, convenient tool to monitor health remotely over time using mobile devices. Numerous paralinguistic features have been demonstrated to contain salient information related to an individual's health. However, mobile device specification and acoustic environments vary widely, risking the reliability of the extracted features. In an initial step towards quantifying these effects, we report the variability of 13 exemplar paralinguistic features commonly reported in the speech-health literature and extracted from the speech of 42 healthy volunteers recorded consecutively in rooms with low and high reverberation with one budget and two higher-end smartphones and a condenser microphone. Our results show reverberation has a clear effect on several features, in particular voice quality markers. They point to new research directions investigating how best to record and process in-the-wild speech for reliable longitudinal health state assessment.
title Towards robust paralinguistic assessment for real-world mobile health (mHealth) monitoring: an initial study of reverberation effects on speech
topic Sound
Audio and Speech Processing
url https://arxiv.org/abs/2305.12514