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...
| Main Authors: | , , |
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| Format: | Journal article |
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Public Library of Science
2016
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| _version_ | 1826301785342476288 |
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| author | Teki, S Kumar, S Griffiths, T |
| author_facet | Teki, S Kumar, S Griffiths, T |
| author_sort | Teki, S |
| collection | OXFORD |
| 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. |
| first_indexed | 2024-03-07T05:37:37Z |
| format | Journal article |
| id | oxford-uuid:e4742bb8-5b88-4654-a9a4-830f34aac230 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T05:37:37Z |
| publishDate | 2016 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | oxford-uuid:e4742bb8-5b88-4654-a9a4-830f34aac2302022-03-27T10:16:44ZLarge-Scale analysis of auditory segregation behavior crowdsourced via a smartphone appJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:e4742bb8-5b88-4654-a9a4-830f34aac230Symplectic Elements at OxfordPublic Library of Science2016Teki, SKumar, SGriffiths, TThe 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. |
| spellingShingle | Teki, S Kumar, S Griffiths, T 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 |
| work_keys_str_mv | AT tekis largescaleanalysisofauditorysegregationbehaviorcrowdsourcedviaasmartphoneapp AT kumars largescaleanalysisofauditorysegregationbehaviorcrowdsourcedviaasmartphoneapp AT griffithst largescaleanalysisofauditorysegregationbehaviorcrowdsourcedviaasmartphoneapp |