Neural Networks Using Full-Band and Subband Spatial Features for Mask Based Source Separation

dc.contributor.author	Bohlender, Alexander
dc.contributor.author	Spriet, Ann
dc.contributor.author	Tirry, Wouter
dc.contributor.author	Madhu, Nilesh
dc.contributor.imecauthor	Bohlender, Alexander
dc.contributor.imecauthor	Madhu, Nilesh
dc.contributor.orcidimec	Bohlender, Alexander::0000-0003-1819-0482
dc.contributor.orcidimec	Madhu, Nilesh::0000-0001-9131-3309
dc.date.accessioned	2022-06-10T09:59:01Z
dc.date.available	2022-04-18T02:09:30Z
dc.date.available	2022-06-10T09:59:01Z
dc.date.issued	2021
dc.identifier.eisbn	978-9-0827-9706-0
dc.identifier.issn	2076-1465
dc.identifier.uri	https://imec-publications.be/handle/20.500.12860/39636
dc.publisher	EUROPEAN ASSOC SIGNAL SPEECH & IMAGE PROCESSING-EURASIP
dc.source.beginpage	346
dc.source.conference	29th European Signal Processing Conference (EUSIPCO)
dc.source.conferencedate	AUG 23-27, 2021
dc.source.conferencelocation	Dublin
dc.source.endpage	350
dc.source.journal	na
dc.source.numberofpages	5
dc.subject.keywords	DOA ESTIMATION
dc.subject.keywords	SPEECH
dc.subject.keywords	SIGNALS
dc.title	Neural Networks Using Full-Band and Subband Spatial Features for Mask Based Source Separation
dc.type	Proceedings paper
dspace.entity.type	Publication
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