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dc.contributor.authorWoods, Kevin Jing Poh
dc.contributor.authorMcDermott, Joshua H.
dc.date.accessioned2018-12-17T16:53:00Z
dc.date.available2018-12-17T16:53:00Z
dc.date.issued2018-03
dc.identifier.issn0027-8424
dc.identifier.issn1091-6490
dc.identifier.urihttp://hdl.handle.net/1721.1/119661
dc.description.abstractThe cocktail party problem requires listeners to infer individual sound sources from mixtures of sound. The problem can be solved only by leveraging regularities in natural sound sources, but little is known about how such regularities are internalized. We explored whether listeners learn source “schemas”—the abstract structure shared by different occurrences of the same type of sound source—and use them to infer sources from mixtures. We measured the ability of listeners to segregate mixtures of time-varying sources. In each experiment a subset of trials contained schema-based sources generated from a common template by transformations (transposition and time dilation) that introduced acoustic variation but preserved abstract structure. Across several tasks and classes of sound sources, schema-based sources consistently aided source separation, in some cases producing rapid improvements in performance over the first few exposures to a schema. Learning persisted across blocks that did not contain the learned schema, and listeners were able to learn and use multiple schemas simultaneously. No learning was evident when schema were presented in the task-irrelevant (i.e., distractor) source. However, learning from task-relevant stimuli showed signs of being implicit, in that listeners were no more likely to report that sources recurred in experiments containing schema-based sources than in control experiments containing no schema-based sources. The results implicate a mechanism for rapidly internalizing abstract sound structure, facilitating accurate perceptual organization of sound sources that recur in the environment.en_US
dc.description.sponsorshipJames S. McDonnell Foundation (Scholar Award)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant BCS-1454094)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant 1R01DC014739-01A1)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Training Grant T32DC000038)en_US
dc.publisherProceedings of the National Academy of Sciencesen_US
dc.relation.isversionofhttp://dx.doi.org/10.1073/PNAS.1801614115en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourcePNASen_US
dc.titleSchema learning for the cocktail party problemen_US
dc.typeArticleen_US
dc.identifier.citationWoods, Kevin J. P., and Josh H. McDermott. “Schema Learning for the Cocktail Party Problem.” Proceedings of the National Academy of Sciences 115, no. 14 (March 21, 2018): E3313–E3322.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.mitauthorWoods, Kevin Jing Poh
dc.contributor.mitauthorMcDermott, Joshua H.
dc.relation.journalProceedings of the National Academy of Sciencesen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2018-12-04T15:51:33Z
dspace.orderedauthorsWoods, Kevin J. P.; McDermott, Josh H.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-3965-2503
mit.licensePUBLISHER_POLICYen_US


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