Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/37639

Title: Augmentative and alternative communication (AAC) advances: A review of configurations for individuals with a speech disability
Authors: Elsahar, Yasmin
Hu, Sijung
Bouazza-Marouf, Kaddour
Kerr, David
Mansor, Annysa
Keywords: Augmentative and alternative communication
Assistive technologies
Sensing modalities
Signal processing
Voice communication
Machine learning
Mobile health
Speech disability
Issue Date: 2019
Publisher: © the Authors. Published by MDPI AG
Citation: ELSAHAR, Y. ... et al., 2019. Augmentative and alternative communication (AAC) advances: A review of configurations for individuals with a speech disability. Sensors, 19(8): 1911.
Abstract: High-tech augmentative and alternative communication (AAC) methods are on a constant rise; however, the interaction between the user and the assistive technology is still challenged for an optimal user experience centered around the desired activity. This review presents a range of signal sensing and acquisition methods utilized in conjunction with the existing high-tech AAC platforms for individuals with a speech disability, including imaging methods, touch-enabled systems, mechanical and electro-mechanical access, breath-activated methods, and brain–computer interfaces (BCI). The listed AAC sensing modalities are compared in terms of ease of access, affordability, complexity, portability, and typical conversational speeds. A revelation of the associated AAC signal processing, encoding, and retrieval highlights the roles of machine learning (ML) and deep learning (DL) in the development of intelligent AAC solutions. The demands and the affordability of most systems hinder the scale of usage of high-tech AAC. Further research is indeed needed for the development of intelligent AAC applications reducing the associated costs and enhancing the portability of the solutions for a real user’s environment. The consolidation of natural language processing with current solutions also needs to be further explored for the amelioration of the conversational speeds. The recommendations for prospective advances in coming high-tech AAC are addressed in terms of developments to support mobile health communicative applications.
Description: This is an Open Access Article. It is published by MDPI under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/
Version: Published
DOI: 10.3390/s19081911
URI: https://dspace.lboro.ac.uk/2134/37639
Publisher Link: https://doi.org/10.3390/s19081911
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

Files associated with this item:

File Description SizeFormat
sensors-19-01911.pdfPublished version836.29 kBAdobe PDFView/Open


SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.