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dc.contributor.author
Ceolini, Enea
dc.contributor.author
Liu, Shih-Chii
dc.date.accessioned
2018-02-12T13:30:05Z
dc.date.available
2017-10-06T04:39:07Z
dc.date.available
2017-11-15T13:56:55Z
dc.date.available
2018-02-12T13:30:05Z
dc.date.available
2018-01-11T02:29:20Z
dc.date.available
2018-02-12T13:22:25Z
dc.date.issued
2017
dc.identifier.isbn
978-1-5090-4117-6
en_US
dc.identifier.other
10.1109/ICASSP.2017.7952157
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/240215
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.subject
Recurrent Neural Network
en_US
dc.subject
LSTM RNNs
en_US
dc.subject
low precision networks
en_US
dc.subject
audio source separation
en_US
dc.subject
humancomputer interaction
en_US
dc.title
Impact of low-precision deep regression networks on single-channel source separation
en_US
dc.type
Conference Paper
dc.date.published
2017-06-19
ethz.book.title
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
en_US
ethz.pages.start
256
en_US
ethz.pages.end
260
en_US
ethz.event
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
en_US
ethz.event.location
New Orleans, LA, USA
en_US
ethz.event.date
March 5-9, 2017
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02533 - Institut für Neuroinformatik / Institute of Neuroinformatics
en_US
ethz.date.deposited
2017-10-06T04:39:09Z
ethz.source
SCOPUS
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2018-02-13T06:58:05Z
ethz.rosetta.lastUpdated
2018-02-13T06:58:05Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/192167
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/227365
ethz.COinS
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