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Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App

The human auditory system is adept at detecting sound sources of interest from a complex mixture of several other simultaneous sounds. The ability to selectively attend to the speech of one speaker whilst ignoring other speakers and background noise is of vital biological significance—the capacity t...

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Detalles Bibliográficos
Autores principales: Teki, Sundeep, Kumar, Sukhbinder, Griffiths, Timothy D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4838209/
https://www.ncbi.nlm.nih.gov/pubmed/27096165
http://dx.doi.org/10.1371/journal.pone.0153916
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author Teki, Sundeep
Kumar, Sukhbinder
Griffiths, Timothy D.
author_facet Teki, Sundeep
Kumar, Sukhbinder
Griffiths, Timothy D.
author_sort Teki, Sundeep
collection PubMed
description The human auditory system is adept at detecting sound sources of interest from a complex mixture of several other simultaneous sounds. The ability to selectively attend to the speech of one speaker whilst ignoring other speakers and background noise is of vital biological significance—the capacity to make sense of complex ‘auditory scenes’ is significantly impaired in aging populations as well as those with hearing loss. We investigated this problem by designing a synthetic signal, termed the ‘stochastic figure-ground’ stimulus that captures essential aspects of complex sounds in the natural environment. Previously, we showed that under controlled laboratory conditions, young listeners sampled from the university subject pool (n = 10) performed very well in detecting targets embedded in the stochastic figure-ground signal. Here, we presented a modified version of this cocktail party paradigm as a ‘game’ featured in a smartphone app (The Great Brain Experiment) and obtained data from a large population with diverse demographical patterns (n = 5148). Despite differences in paradigms and experimental settings, the observed target-detection performance by users of the app was robust and consistent with our previous results from the psychophysical study. Our results highlight the potential use of smartphone apps in capturing robust large-scale auditory behavioral data from normal healthy volunteers, which can also be extended to study auditory deficits in clinical populations with hearing impairments and central auditory disorders.
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spelling pubmed-48382092016-04-29 Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App Teki, Sundeep Kumar, Sukhbinder Griffiths, Timothy D. PLoS One Research Article The human auditory system is adept at detecting sound sources of interest from a complex mixture of several other simultaneous sounds. The ability to selectively attend to the speech of one speaker whilst ignoring other speakers and background noise is of vital biological significance—the capacity to make sense of complex ‘auditory scenes’ is significantly impaired in aging populations as well as those with hearing loss. We investigated this problem by designing a synthetic signal, termed the ‘stochastic figure-ground’ stimulus that captures essential aspects of complex sounds in the natural environment. Previously, we showed that under controlled laboratory conditions, young listeners sampled from the university subject pool (n = 10) performed very well in detecting targets embedded in the stochastic figure-ground signal. Here, we presented a modified version of this cocktail party paradigm as a ‘game’ featured in a smartphone app (The Great Brain Experiment) and obtained data from a large population with diverse demographical patterns (n = 5148). Despite differences in paradigms and experimental settings, the observed target-detection performance by users of the app was robust and consistent with our previous results from the psychophysical study. Our results highlight the potential use of smartphone apps in capturing robust large-scale auditory behavioral data from normal healthy volunteers, which can also be extended to study auditory deficits in clinical populations with hearing impairments and central auditory disorders. Public Library of Science 2016-04-20 /pmc/articles/PMC4838209/ /pubmed/27096165 http://dx.doi.org/10.1371/journal.pone.0153916 Text en © 2016 Teki et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Teki, Sundeep
Kumar, Sukhbinder
Griffiths, Timothy D.
Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App
title Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App
title_full Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App
title_fullStr Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App
title_full_unstemmed Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App
title_short Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App
title_sort large-scale analysis of auditory segregation behavior crowdsourced via a smartphone app
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4838209/
https://www.ncbi.nlm.nih.gov/pubmed/27096165
http://dx.doi.org/10.1371/journal.pone.0153916
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