Direct Speech Reconstruction From Articulatory Sensor Data by Machine Learning

Gonzalez, J.A. orcid.org/0000-0002-5531-8994, Cheah, L.A., Gomez, A.M. et al. (5 more authors) (2017) Direct Speech Reconstruction From Articulatory Sensor Data by Machine Learning. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 25 (12). pp. 2362-2374. ISSN 2329-9290

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Keywords: Silent speech interfaces; articulatory-to-acoustic mapping; speech rehabilitation; permanent magnet articulography; speech synthesis
Dates:
  • Published: 23 November 2017
  • Accepted: 25 September 2017
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:
FunderGrant number
UNIVERSITY OF HULLCN/64(116)
NATIONAL INSTITUTE FOR HEALTH RESEARCHII-AR-0410-12027
WHITE ROSE UNIVERSITY CONSORTIUMNONE
Depositing User: Symplectic Sheffield
Date Deposited: 19 Mar 2018 14:57
Last Modified: 28 Jun 2018 14:55
Published Version: https://doi.org/10.1109/TASLP.2017.2757263
Status: Published
Publisher: IEEE
Refereed: Yes
Identification Number: https://doi.org/10.1109/TASLP.2017.2757263
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