Predominantly, AAC users still use combinations of unaided low-tech methods together with an aided high-tech device as suitable for the context of usage and the person they are conversing with. Studies also show that, after testing several AAC systems, the potential of AAC might be limited by complex operational difficulties given the number of users who are simultaneously physically impaired and speech-disabled. In turn, an optimized use of high-tech AAC should be researched to provide a faster means of communication, in comparison to low-tech, by prioritizing the communicative needs of the users over the needs of the system. Moreover, the high costs and complicated training a user requires to operate most high-tech AAC devices could hinder the access to high-tech AAC, and thus the usability of speech generating devices. Low-tech AAC solutions are usually the first techniques tried by speech and language therapists, as the use of simplistic display boards and communication books is both cost-effective and easy to obtain. However, although high-tech AAC systems are rapidly evolving, several considerations are yet pertinent to the provision of effective solutions efficiently serving AAC users. The potential of AAC intervention has hence been substantial over the last 30 years, with the provision of innovative solutions to a wide range of users with a speech disability. AAC communication is also often classified as either un-aided or aided, given the dependence of the solution on the human body solely or the interaction with an external communicative aid for communication, respectively. A common attribute of modern day AAC solutions tends to rely on the translation of a user’s intended meanings into speech via speech generating devices (SGDs).
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Devices falling under this category, such as smart devices and dedicated AAC devices, integrate hardware and software to support a user’s communication needs. High-tech AAC encompasses the use of electronic devices to achieve an AAC target. Low-tech AAC utilizes basic tools, such as books and display boards with extended lexicons of images and phrases to aid the communication process. No-tech AAC is considered the oldest of the three AAC categories, given its reliance on the interpretation of facial expressions and voluntary motor movements, such as sign language, to deliver non-verbal messages. In the broad context of speech and language, speech is often associated with the motor movements responsible for the production of spoken words, whereas language is associated with the cognitive processing skills of communication.ĪAC solutions are classified into three categories: no-tech, low-tech, and high-tech AAC. Augmentative and alternative communication (AAC) incorporates a wide range of processes that augment, complement, or replace speech of individuals with complex communication needs. The loss of speech capabilities associated with extreme forms of paralysis and further medical complications has long been regarded as a barrier between the sufferers and the outside world. Recent studies show that up to 1% of the world population suffers a degree of speech, language or communication need (SLCN). The recommendations for prospective advances in coming high-tech AAC are addressed in terms of developments to support mobile health communicative applications. The consolidation of natural language processing with current solutions also needs to be further explored for the amelioration of the conversational speeds.
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 demands and the affordability of most systems hinder the scale of usage of high-tech AAC. 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 listed AAC sensing modalities are compared in terms of ease of access, affordability, complexity, portability, and typical conversational speeds. 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). 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.
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