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dc.contributor.authorSaddler, Mark R
dc.contributor.authorFrancl, Andrew
dc.contributor.authorFeather, Jenelle
dc.contributor.authorQian, Kaizhi
dc.contributor.authorZhang, Yang
dc.contributor.authorMcDermott, Josh H
dc.date.accessioned2023-03-30T16:31:06Z
dc.date.available2023-03-30T16:31:06Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/150013
dc.language.isoen
dc.publisherInternational Speech Communication Associationen_US
dc.relation.isversionof10.21437/INTERSPEECH.2021-1973en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleSpeech Denoising with Auditory Modelsen_US
dc.typeArticleen_US
dc.identifier.citationSaddler, Mark R, Francl, Andrew, Feather, Jenelle, Qian, Kaizhi, Zhang, Yang et al. 2021. "Speech Denoising with Auditory Models." Interspeech 2021.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.relation.journalInterspeech 2021en_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2023-03-30T16:19:55Z
dspace.orderedauthorsSaddler, MR; Francl, A; Feather, J; Qian, K; Zhang, Y; McDermott, JHen_US
dspace.date.submission2023-03-30T16:19:56Z
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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