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

Lookup NU author(s): Sundeep Teki, Dr Sukhbinder Kumar, Professor Tim Griffiths

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

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.


Publication metadata

Author(s): Teki S, Kumar S, Griffiths TD

Publication type: Article

Publication status: Published

Journal: PLoS One

Year: 2016

Volume: 11

Issue: 4

Print publication date: 01/01/2016

Online publication date: 20/04/2016

Acceptance date: 06/04/2016

ISSN (electronic): 1932-6203

Publisher: Public Library of Science

URL: http://dx.doi.org/10.1371/journal.pone.0153916

DOI: 10.1371/journal.pone.0153916

PubMed id: 27096165


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