TY - JOUR
AU - Hameed, Hira
AU - Usman, Muhammad
AU - Tahir, Ahsen
AU - Hussain, Amir
AU - Abbas, Hasan
AU - Cui, Tie Jun
AU - Imran, Muhammad Ali
AU - Abbasi, Qammer H.
PY - 2022
DA - September
TI - Pushing the limits of remote RF sensing by reading lips under the face mask
JO - Nature Communications
VL - 13
DO - https://doi.org/10.1038/s41467-022-32231-1
AB - The problem of Lip-reading has become an important research challenge in recent years. The goal is to recognise speech from lip movements. Most of the Lip-reading technologies developed so far are camera-based, which require video recording of the target. However, these technologies have well-known limitations of occlusion and ambient lighting with serious privacy concerns. Furthermore, vision-based technologies are not useful for multi-modal hearing aids in the coronavirus (COVID-19) environment, where face masks have become a norm. This paper aims to solve the fundamental limitations of camera-based systems by proposing a radio frequency (RF) based Lip-reading framework, having an ability to read lips under face masks. The framework employs Wi-Fi and radar technologies as enablers of RF sensing based Lip-reading. A dataset comprising of vowels A, E, I, O, U and empty (static/closed lips) is collected using both technologies, with a face mask. The collected data is used to train machine learning (ML) and deep learning (DL) models. A high classification accuracy of 95% is achieved on the Wi-Fi data utilising neural network (NN) models. Moreover, similar accuracy is achieved by VGG16 deep learning model on the collected radar-based dataset.
PB - Springer Nature
UR - https://eprints.gla.ac.uk/275725/
KW - Coronavirus (COVID-19)
KW - Digital health and technology
KW - Minority groups
ER