Effect of Kinematics and Fluency in Adversarial Synthetic Data Generation for ASL Recognition With RF Sensors

• Published in: IEEE transactions on aerospace and electronic systems Vol. 58; no. 4; pp. 2732 - 2745
• Main Authors: Rahman, Mohammad Mahbubur, Malaia, Evie A., Gurbuz, Ali Cafer, Griffin, Darrin J., Crawford, Chris, Gurbuz, Sevgi Zubeyde
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation; Adversarial learning; ASL; Auditory system; Deep learning; Doppler effect; Frequency modulation; Generative adversarial networks; Kinematics; Machine learning; micro-Doppler (<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX"> mu D</tex-math> </inline-formula> </named-content>); Natural language processing; radar; Radio frequency; Recognition; Sensors; sign language; Synthetic data; Training

RF sensors have been recently proposed as a new modality for sign language processing technology. They are noncontact, effective in the dark, and acquire a direct measurement of signing kinematic via exploitation of the micro-Doppler effect. First, this work provides an in depth comparative examinat...