Artificial intelligence enabled smart mask for speech recognition for future hearing devices.

Autor: Hameed H; James Watt School of Engineering, University of Glasgow, Glasgow, G12 8QQ, UK., Lubna; James Watt School of Engineering, University of Glasgow, Glasgow, G12 8QQ, UK.; University of Engineering & Technology, UETP, Peshawar, Pakistan., Usman M; School of Computing, Engineering and Built Environment, Glasgow Caledonian University, Glasgow, G4 0BA, UK., Kazim JUR; James Watt School of Engineering, University of Glasgow, Glasgow, G12 8QQ, UK., Assaleh K; Department of Electrical and Computer Engineering, College of Engineering and Information Technology, Ajman University, Ajman, UAE.; Artificial Intelligence Research Center (AIRC), Ajman University, Ajman, UAE., Arshad K; Department of Electrical and Computer Engineering, College of Engineering and Information Technology, Ajman University, Ajman, UAE.; Artificial Intelligence Research Center (AIRC), Ajman University, Ajman, UAE., Hussain A; School of Computing, Edinburgh Napier University, Edinburgh, Scotland, UK., Imran M; James Watt School of Engineering, University of Glasgow, Glasgow, G12 8QQ, UK., Abbasi QH; James Watt School of Engineering, University of Glasgow, Glasgow, G12 8QQ, UK. qammer.abbasi@glasgow.ac.uk.; Artificial Intelligence Research Center (AIRC), Ajman University, Ajman, UAE. qammer.abbasi@glasgow.ac.uk.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2024 Dec 03; Vol. 14 (1), pp. 30112. Date of Electronic Publication: 2024 Dec 03.
DOI: 10.1038/s41598-024-81904-y
Abstrakt: In recent years, Lip-reading has emerged as a significant research challenge. The aim is to recognise speech by analysing Lip movements. The majority of Lip-reading technologies are based on cameras and wearable devices. However, these technologies have well-known occlusion and ambient lighting limitations, privacy concerns as well as wearable device discomfort for subjects and disturb their daily routines. Furthermore, in the era of coronavirus (COVID-19), where face masks are the norm, vision-based and wearable-based technologies for hearing aids are ineffective. To address the fundamental limitations of camera-based and wearable-based systems, this paper proposes a Radio Frequency Identification (RFID)-based smart mask for a Lip-reading framework capable of reading Lips under face masks, enabling effective speech recognition and fostering conversational accessibility for individuals with hearing impairment. The system uses RFID technology to make Radio Frequency (RF) sensing-based Lip-reading possible. A smart RFID face mask is used to collect a dataset containing three different classes of vowels (A, E, I, O, U), Consonants (F, G, M, S), and words (Fish, Goat, Meal, Moon, Snake). The collected data are fed into well-known machine-learning models for classification. A high classification accuracy is achieved by individual classes and combined datasets. On the RFID combined dataset, the Random Forest model achieves a high classification accuracy of 80%.
Competing Interests: Declarations. Competing interests: The authors declare no competing interests.
(© 2024. The Author(s).)
Databáze: MEDLINE
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