This work is focused on the development of Visual Speech recognition systems within sparse data domains. The use of Visual Speech recognition as this basis for a Liveness Verification system is discussed. This thesis also explores the adaptation of models trained within one domain to be used with data from another (e.g. adaptation from RGB to IR).
Date of Award | Dec 2022 |
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Original language | English |
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Awarding Institution | - Queen's University Belfast
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Supervisor | Darryl Stewart (Supervisor) & Ming Ji (Supervisor) |
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- Lipreading
- visual speech recognition
- speech recognition
- liveness verification
- biometrics
Visual speech recognition in sparse data domains
McShane, P. (Author). Dec 2022
Student thesis: Doctoral Thesis › Doctor of Philosophy