Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Individuals with a Speech Disability

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.

Brain–Computer Interface (BCI) Control of a Virtual Assistant in a Smartphone to Manage Messaging Applications

“…A key point of AT is that it must be adapted to the abilities of the patient. Therefore, AT should be able to be controlled through those output channels that the patient still has preserved, such as the voice, the eye gaze, movements of a finger, the head, the cheek, or the tongue; these examples of AT systems rely on the use of input instruments such as microphones, eye-trackers, mechanical keyboards, head-pointing devices or low-pressure sensors, respectively [ 5 ]. A drawback to note is that, in severe and progressive motor limitations (as is the case in ALS), most of these examples of AT may no longer be useful because they depend on some type of muscular channel that may be affected in the patient, in either the initial or final stages of the disease.…”

The adult multidisciplinary respiratory neuromuscular clinic

“…In progressive conditions, patients' speech is likely to deteriorate to a point where verbal communication is not possible. Ensuring access to augmented communication therapies for these individuals is vital to optimise quality of life and health [ 87 , 88 ]. In addition, different modes of ventilation impact on speech quality and so close coordination with the respiratory physician is important to ensure that speech is optimised with evolving ventilatory therapies [ 89 ].…”

Proceedings of the 1st Workshop on NLP for Positive Impact

“…In addition to providing more communication methods, research has proven that AAC technology can actually improve language development skills in children (Light et al, 2019). These systems vary in technical sophistication from picture boards corresponding to concepts to tablets or application based speech-generating devices (Elsahar et al, 2019). Figure 1 depicts two such devices, both of which include touch-based text displays.…”