Deep learning features for robust detection of acoustic events in sleep-disordered breathing

Romero, H., Ma, N., Brown, G. orcid.org/0000-0001-8565-5476 et al. (2 more authors) (2019) Deep learning features for robust detection of acoustic events in sleep-disordered breathing. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP-2019). IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 12-17 May 2019, Brighton, UK. IEEE ISBN 9781479981311

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Item Type: Proceedings Paper
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Keywords: Sleep-disordered breathing; deep learning; hidden Markov model; bottleneck features; corpus
Dates:
  • Published: April 2019
  • Published (online): 17 April 2019
  • Accepted: 4 February 2019
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:
Funder
Grant number
INNOVATE UK (TSB)
KTP009905
PASSION FOR LIFE HEALTHCARE (UK) LIMITED
C002
Depositing User: Symplectic Sheffield
Date Deposited: 12 Feb 2019 13:37
Last Modified: 17 Apr 2020 00:38
Status: Published
Publisher: IEEE
Refereed: Yes
Identification Number: 10.1109/ICASSP.2019.8683099
Open Archives Initiative ID (OAI ID):

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