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Advancing Electromyographic Continuous Speech Recognition: Signal Preprocessing and Modeling

Wand, Michael

Abstract:
Speech is the natural medium of human communication, but audible speech can be overheard by bystanders and excludes speech-disabled people. This work presents a speech recognizer based on surface electromyography, where electric potentials of the facial muscles are captured by surface electrodes, allowing speech to be processed nonacoustically. A system which was state-of-the-art at the beginning of this thesis is substantially improved in terms of accuracy, flexibility, and robustness.

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Volltext §
DOI: 10.5445/IR/1000041117
Coverbild
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Hochschulschrift
Jahr 2014
Sprache Englisch
Identifikator urn:nbn:de:swb:90-411174
KITopen-ID: 1000041117
Verlag KIT, Karlsruhe
Abschlussart Dissertation
Fakultät Fakultät für Informatik (INFORMATIK)
Institut Institut für Anthropomatik und Robotik (IAR)
Prüfungsdaten 14.01.2014
Referent/Betreuer Prof. T. Schultz
Schlagworte Electromyography, EMG-based Speech Recognition, Silent Speech interfaces
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KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
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