Gilbert, J.M., Gonzalez Lopez, J.A. orcid.org/0000-0002-5531-8994, Cheah, L.A. et al. (4 more authors) (2017) Restoring speech following total removal of the larynx by a learned transformation from sensor data to acoustics. Journal of the Acoustical Society of America, 141 (3). EL307-EL307. ISSN 0001-4966
Abstract
Total removal of the larynx may be required to treat laryn- geal cancer: speech is lost. This article shows that it may be possible to restore speech by sensing movement of the remaining speech articula- tors and use machine learning algorithms to derive a transformation to convert this sensor data into an acoustic signal. The resulting “silent speech,” which may be delivered in real time, is intelligible and sounds natural. The identity of the speaker is recognisable. The sensing tech- nique involves attaching small, unobtrusive magnets to the lips and tongue and monitoring changes in the magnetic field induced by their movement.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2017 Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. The following article appeared in Journal of the Acoustical Society of America Vol 141, part 3 and may be found at https://doi.org/10.1121/1.4978364 |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 24 Mar 2017 11:27 |
Last Modified: | 21 Sep 2017 00:38 |
Published Version: | https://doi.org/10.1121/1.4978364 |
Status: | Published |
Publisher: | Acoustical Society of America |
Refereed: | Yes |
Identification Number: | 10.1121/1.4978364 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:114030 |