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Restoring speech following total removal of the larynx by a learned transformation from sensor data to acoustics

Gilbert, James M.; Gonzalez, Jose A.; Cheah, Lam A.; Ell, Stephen R.; Green, Phil; Moore, Roger K.; Holdsworth, Ed

Authors

Jose A. Gonzalez

Lam A. Cheah

Stephen R. Ell

Phil Green

Roger K. Moore

Ed Holdsworth



Abstract

Total removal of the larynx may be required to treat laryngeal cancer: speech is lost. This article shows that it may be possible to restore speech by sensing movement of the remaining speech articulators 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 technique involves attaching small, unobtrusive magnets to the lips and tongue and monitoring changes in the magnetic field induced by their movement.

Journal Article Type Article
Publication Date 2017-03
Journal Journal of the Acoustical Society of America
Print ISSN 0001-4966
Electronic ISSN 1520-8524
Publisher Acoustical Society of America
Peer Reviewed Peer Reviewed
Volume 141
Issue 3
Pages EL307-EL313
APA6 Citation Gilbert, J. M., Gonzalez, J. A., Cheah, L. A., Ell, S. R., Green, P., Moore, R. K., & Holdsworth, E. (2017). Restoring speech following total removal of the larynx by a learned transformation from sensor data to acoustics. The Journal of the Acoustical Society of America, 141(3), EL307-EL313. https://doi.org/10.1121/1.4978364
DOI https://doi.org/10.1121/1.4978364
Keywords Speech restoration; Permanent magnetic articulography; Machine learning
Publisher URL http://asa.scitation.org/doi/10.1121/1.4978364
Additional Information received: 2016-10-17; revised: 2017-01-22; accepted: 2017-02-21; published: 2017-03-21

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© 2017 Acoustical Society of America



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