Gonzalez, J.A., Cheah, L.A., Gilbert, J.M. et al. (4 more authors) (2017) Voice restoration after laryngectomy based on magnetic sensing of articulator movement and statistical articulation-to-speech conversion. In: Communications in Computer and Information Science. BIOSTEC 2016 9th International Joint Conference on Biomedical Engineering Systems and Technologies, 21-23 Feb 2016, Rome. https://doi.org/10.1007/978-3-319-54717-6_17, 690 . , pp. 295-316. ISBN 9783319547169
Abstract
© Springer International Publishing AG 2017.In this work, we present a silent speech system that is able to generate audible speech from captured movement of speech articulators. Our goal is to help laryngectomy patients, i.e. patients who have lost the ability to speak following surgical removal of the larynx most frequently due to cancer, to recover their voice. In our system, we use a magnetic sensing technique known as Permanent Magnet Articulography (PMA) to capture the movement of the lips and tongue by attaching small magnets to the articulators and monitoring the magnetic field changes with sensors close to the mouth. The captured sensor data is then transformed into a sequence of speech parameter vectors from which a time-domain speech signal is finally synthesised. The key component of our system is a parametric transformation which represents the PMA-tospeech mapping. Here, this transformation takes the form of a statistical model (a mixture of factor analysers, more specifically) whose parameters are learned from simultaneous recordings of PMA and speech signals acquired before laryngectomy. To evaluate the performance of our system on voice reconstruction, we recorded two PMA-and-speech databases with different phonetic complexity for several non-impaired subjects. Results show that our system is able to synthesise speech that sounds as the original voice of the subject and also is intelligible. However, more work still need to be done to achieve a consistent synthesis for phonetically-rich vocabularies.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 Springer. This is an author produced version of a paper subsequently published in Biomedical Engineering Systems and Technologies. Uploaded in accordance with the publisher's self-archiving policy |
Keywords: | Silent speech interfaces; Speech rehabilitation; Speech synthesis; Permanent magnet articulography |
Dates: |
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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 15:04 |
Last Modified: | 19 Dec 2022 13:35 |
Status: | Published |
Series Name: | https://doi.org/10.1007/978-3-319-54717-6_17 |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-319-54717-6_17 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:114026 |