Improving detection of Alzheimer’s Disease using automatic speech recognition to identify high-quality segments for more robust feature extraction

Pan, Y., Mirheidari, B., Reuber, M. orcid.org/0000-0002-4104-6705 et al. (3 more authors) (2020) Improving detection of Alzheimer’s Disease using automatic speech recognition to identify high-quality segments for more robust feature extraction. In: Proceedings of Interspeech 2020. Interspeech 2020, 25-29 Oct 2020, Shanghai, China. International Speech Communication Association (ISCA) , pp. 4961-4965.

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2020 ISCA. Reproduced in accordance with the publisher's self-archiving policy.
Dates:
  • Published (online): 25 October 2020
  • Published: 25 October 2020
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > Sheffield Centre for Health and Related Research
The University of Sheffield > Sheffield Teaching Hospitals
Funding Information:
FunderGrant number
EUROPEAN COMMISSION - HORIZON 2020766287 - TAPAS
Depositing User: Symplectic Sheffield
Date Deposited: 17 Sep 2021 12:06
Last Modified: 17 Sep 2021 12:06
Status: Published
Publisher: International Speech Communication Association (ISCA)
Refereed: Yes
Identification Number: https://doi.org/10.21437/interspeech.2020-2698

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